Dongheon Lee | Medical Image Analysis | Best Researcher Award

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Prof . Dr . Dongheon Lee | Medical Image Analysis | Best Researcher Award

Assistant Professor at Seoul National University / College of Medicine, South Korea

Dr. Dongheon Lee is an Assistant Professor in the Department of Radiology at Seoul National University College of Medicine, with a joint appointment in the Interdisciplinary Program in Bioengineering. He specializes in medical image analysis, deep learning, and computer vision, with a strong emphasis on clinically relevant AI systems. His academic journey is deeply rooted in bioengineering, having completed both his M.S. and Ph.D. at Seoul National University. Dr. Lee has a proven record of innovation, evidenced by multiple high-impact publications and patents, many of which contribute directly to enhancing diagnostic accuracy and clinical workflow. He has served in leadership roles, including Deputy Director at Chungnam National University’s research institutes and active committee memberships. His research has received several national and international accolades, demonstrating both depth and translational impact. He continues to drive forward advancements at the intersection of AI and medical practice, with a focus on diagnostic technologies and clinical decision support.

Professional Profile 

Education🎓 

Dr. Dongheon Lee’s educational foundation is built on interdisciplinary expertise in bioengineering and medical imaging. He earned his Ph.D. in Bioengineering from Seoul National University in 2020, under the mentorship of Professor Hee Chan Kim. His doctoral research, titled “Deep Learning Approaches for Clinical Performance Improvement: Applications to Colonoscopic Diagnosis and Robotic Surgical Skill Assessment”, reflects his early focus on practical, AI-based clinical solutions. Prior to that, he completed his M.S. in the same interdisciplinary program at Seoul National University in 2015, where he also concentrated on medical image analysis. His academic journey began with a B.S. degree in Electronic System Engineering from Hanyang University in 2013, providing him with a strong technical foundation in systems engineering and computational methods. This combination of engineering, medicine, and AI has shaped his approach to research and allowed him to work at the intersection of technology and clinical application with considerable effectiveness.

Professional Experience📝

Dr. Dongheon Lee has held multiple academic and research roles that showcase a steady progression in responsibility and impact. He currently serves as an Assistant Professor in the Department of Radiology at Seoul National University College of Medicine. Prior to this, he was an Assistant Professor in the Department of Biomedical Engineering at Chungnam National University from 2021 to 2025. During that time, he also served as Deputy Director at both the Biomedical Engineering Research Institute and the Big Data Center at Chungnam National University Hospital. Earlier in his career, Dr. Lee worked as a Research Assistant Professor and Research Specialist at the Biomedical Research Institute of Seoul National University Hospital. These roles have enabled him to gain comprehensive experience across clinical, academic, and data-intensive research environments. His career reflects a sustained commitment to developing AI solutions for healthcare, combining technical skill with clinical relevance in both research and educational settings.

Research Interest🔎

Dr. Dongheon Lee’s research interests lie at the intersection of medical image analysis, artificial intelligence, and computer vision, with a strong focus on clinical application. He is particularly invested in developing deep learning frameworks for diagnostic accuracy, disease classification, and surgical skill assessment. His work addresses real-world challenges in radiology and endoscopy, such as colorectal polyp detection and lung cancer screening, through robust AI-driven solutions. Dr. Lee is also deeply interested in uncertainty quantification, out-of-distribution detection, and the interpretability of AI models in clinical workflows. His research aims to make AI not only accurate but also explainable and trustworthy in medical environments. By integrating multimodal data and advanced visualization techniques, he seeks to improve human-AI collaboration in diagnosis and treatment planning. His ongoing projects involve 3D anatomical modeling, radiograph-based biological age estimation, and virtual simulation technologies, all of which reflect his mission to bridge engineering innovation with practical healthcare delivery.

Award and Honor🏆

Dr. Dongheon Lee has received multiple prestigious awards that underscore the impact and innovation of his research. In 2023, he was honored with the Medical Research Academic Award from Chungnam National University Hospital, recognizing his contributions to clinical imaging research. The same year, he was a winner in the MICCAI Grand Challenge (LDCTIQAC 2023), a significant achievement in the international medical image computing community. Earlier, in 2020, he received both the Outstanding Paper Award from Seoul National University Hospital and the ICT Colloquium Minister of Science and ICT Award, conferred by the Korean government and the Institute for Information & Communications Technology Planning & Evaluation (IITP). These awards highlight his excellence in both academic and applied domains, demonstrating a consistent ability to innovate in healthcare technologies. His achievements reflect strong peer recognition and align with his commitment to advancing artificial intelligence in real-world medical settings.

Research Skill🔬

Dr. Dongheon Lee possesses a robust and diverse set of research skills that bridge engineering, medical imaging, and artificial intelligence. He is highly proficient in deep learning model development for classification, detection, segmentation, and uncertainty estimation tasks, particularly in the context of radiological and endoscopic data. His expertise extends to algorithmic optimization, multi-modal data fusion, and computational modeling, with a focus on practical deployment in clinical workflows. Dr. Lee is experienced in designing and validating AI systems with real-world datasets, ensuring clinical relevance and regulatory compliance. He has also developed patented technologies for 3D anatomical mapping, lesion tracking, and endoscopic path guidance. Additionally, he demonstrates strong capabilities in interdisciplinary collaboration, leading cross-functional teams in bioengineering, computer science, and clinical departments. His skills in grant writing, manuscript preparation, and research leadership complement his technical acumen, enabling him to contribute meaningfully to both academic advancement and translational medical innovation.

Conclusion💡

Dr. Dongheon Lee is exceptionally qualified and stands out as a top-tier candidate for the Best Researcher Award. His research has made tangible impacts in clinical medicine, particularly through AI-driven diagnostics and medical imaging. The combination of high-impact publications, innovation through patents, and recognized academic leadership makes his profile exemplary.

With minor enhancements in global outreach and broader authorship representation, he could further solidify his stature as a global leader in biomedical AI.

Publications Top Noted✍

  • Title: Improved accuracy in optical diagnosis of colorectal polyps using convolutional neural networks with visual explanations
    Authors: EH Jin, D Lee, JH Bae, HY Kang, MS Kwak, JY Seo, JI Yang, SY Yang, …
    Year: 2020
    Citations: 137

  • Title: Evaluation of surgical skills during robotic surgery by deep learning-based multiple surgical instrument tracking in training and actual operations
    Authors: D Lee, HW Yu, H Kwon, HJ Kong, KE Lee, HC Kim
    Year: 2020
    Citations: 104

  • Title: CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates
    Authors: H Kim, D Lee, WS Cho, JC Lee, JM Goo, HC Kim, CM Park
    Year: 2020
    Citations: 49

  • Title: Vision-based tracking system for augmented reality to localize recurrent laryngeal nerve during robotic thyroid surgery
    Authors: D Lee, HW Yu, S Kim, J Yoon, K Lee, YJ Chai, JY Choi, HJ Kong, KE Lee, …
    Year: 2020
    Citations: 29

  • Title: Deep learning to optimize candidate selection for lung cancer CT screening: advancing the 2021 USPSTF recommendations
    Authors: JH Lee, D Lee, MT Lu, VK Raghu, CM Park, JM Goo, SH Choi, H Kim
    Year: 2022
    Citations: 28

  • Title: Preliminary study on application of augmented reality visualization in robotic thyroid surgery
    Authors: D Lee, HJ Kong, D Kim, JW Yi, YJ Chai, KE Lee, HC Kim
    Year: 2018
    Citations: 27

  • Title: Estimating maximal oxygen uptake from daily activity data measured by a watch-type fitness tracker: cross-sectional study
    Authors: SB Kwon, JW Ahn, SM Lee, J Lee, D Lee, J Hong, HC Kim, HJ Yoon
    Year: 2019
    Citations: 23

  • Title: Augmented reality to localize individual organ in surgical procedure
    Authors: D Lee, JW Yi, J Hong, YJ Chai, HC Kim, HJ Kong
    Year: 2018
    Citations: 23

  • Title: Online learning for the hyoid bone tracking during swallowing with neck movement adjustment using semantic segmentation
    Authors: D Lee, WH Lee, HG Seo, BM Oh, JC Lee, HC Kim
    Year: 2020
    Citations: 21

  • Title: Endoscopists performance in optical diagnosis of colorectal polyps in artificial intelligence studies
    Authors: S Pecere, G Antonelli, M Dinis‐Ribeiro, Y Mori, C Hassan, L Fuccio, …
    Year: 2022
    Citations: 17

  • Title: Low-dose computed tomography perceptual image quality assessment
    Authors: W Lee, F Wagner, A Galdran, Y Shi, W Xia, G Wang, X Mou, MA Ahamed, …
    Year: 2025
    Citations: 13

  • Title: Enhancing artificial intelligence-doctor collaboration for computer-aided diagnosis in colonoscopy through improved digital literacy
    Authors: Y Mori, EH Jin, D Lee
    Year: 2024
    Citations: 10

  • Title: Practical training approaches for discordant atopic dermatitis severity datasets: merging methods with soft-label and train-set pruning
    Authors: SI Cho, D Lee, B Han, JS Lee, JY Hong, JH Chung, DH Lee, JI Na
    Year: 2022
    Citations: 10

  • Title: Reliability of suprahyoid and infrahyoid electromyographic measurements during swallowing in healthy subjects
    Authors: MW Park, D Lee, HG Seo, TR Han, JC Lee, HC Kim, BM Oh
    Year: 2021
    Citations: 8

  • Title: Essential elements of physical fitness analysis in male adolescent athletes using machine learning
    Authors: YH Lee, J Chang, JE Lee, YS Jung, D Lee, HS Lee
    Year: 2024
    Citations: 7

  • Title: External testing of a deep learning model to estimate biologic age using chest radiographs
    Authors: JH Lee, D Lee, MT Lu, VK Raghu, JM Goo, Y Choi, SH Choi, H Kim
    Year: 2024
    Citations: 5

  • Title: Effect of an anti-adhesion agent on vision-based assessment of cervical adhesions after thyroid surgery: randomized, placebo-controlled trial
    Authors: HW Yu, D Lee, K Lee, S Kim, YJ Chai, HC Kim, JY Choi, KE Lee
    Year: 2021
    Citations: 5

  • Title: Augmented Reality-Based Visual Cue for Guiding Central Catheter Insertion in Pediatric Oncologic Patients
    Authors: JK Youn, D Lee, D Ko, I Yeom, HJ Joo, HC Kim, HJ Kong, HY Kim
    Year: 2022
    Citations: 4

  • Title: Texture-preserving low dose CT image denoising using Pearson divergence
    Authors: J Oh, D Wu, B Hong, D Lee, M Kang, Q Li, K Kim
    Year: 2024
    Citations: 2

  • Title: Optimal view detection for ultrasound-guided supraclavicular block using deep learning approaches
    Authors: Y Jo, D Lee, D Baek, BK Choi, N Aryal, J Jung, YS Shin, B Hong
    Year: 2023
    Citations: 2

Dharmapuri Siri | Software Engineering | Best Researcher Award

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Dr. Dharmapuri Siri | Software Engineering | Best Researcher Award

Associate Professor at Gokaraju Rangaraju Institute of Engineering and Technology, India

Dr. D. Siri is a committed academician and researcher with over 14 years of teaching and research experience in the field of Computer Science and Engineering. With a keen focus on emerging technologies like machine learning, deep learning, image processing, and smart systems, she has contributed extensively through journal publications, conference presentations, and collaborative research projects. Her academic journey showcases a strong foundation in computer science, culminating in a Ph.D. focused on software quality prediction using ML techniques. Beyond her research, Dr. Siri has demonstrated consistent participation in faculty development programs, technical workshops, and interdisciplinary conferences, reinforcing her commitment to lifelong learning. Her work reflects an integration of academic rigor and applied innovation, seen through her patent on smart vehicle systems and her involvement in smart agriculture, health diagnostics, and cyber-physical security systems. Dr. Siri is recognized for her proactive engagement in knowledge dissemination and contribution to the evolving landscape of intelligent technologies.

Professional Profile 

Education🎓 

Dr. D. Siri holds a Ph.D. in Computer Science and Engineering from JJT University, completed in 2022, where she specialized in software quality enhancement through machine learning. Her doctoral research focused on developing a predictive model for bug detection using advanced ML techniques. Prior to this, she earned her Master of Technology (M.Tech) in Computer Science and Engineering from JNTU Hyderabad, graduating with a strong academic foundation in programming, algorithms, and systems design. She also holds a Bachelor’s degree in Information Technology from Sreenivas Reddy Institute of Technology under JNTU Hyderabad, where she built her core technical skills. Her early education includes intermediate studies in Mathematics, Physics, and Chemistry with a 67.5% score and a 10th-grade certification from the Board of Secondary Education, Andhra Pradesh. Her steady academic progression reflects a strong commitment to developing both theoretical and applied competencies essential for success in the field of computing and data technologies.

Professional Experience📝

Dr. D. Siri brings a rich teaching background with over 14 years of experience in academia. She began her career in 2008 as an Assistant Professor at TRR Engineering College, Patancheru, and continued in the same role at TRR College of Engineering until 2017. Her professional journey then led her to Malla Reddy Engineering College for Women, where she further honed her teaching and mentoring capabilities in computer science. Currently, she serves as an Associate Professor in the Department of Computer Science and Engineering at Gokaraju Rangaraju Institute of Engineering and Technology, Hyderabad. Throughout her career, she has taught a wide range of subjects including Software Engineering, Software Testing Methodologies, Machine Learning, and Data Structures. Her professional engagements are marked by a balance of teaching, research, and institutional development, with active involvement in organizing seminars, guiding student projects, and enhancing technical knowledge delivery through innovative and modern pedagogical techniques.

Research Interest🔎

Dr. D. Siri’s research interests lie at the intersection of machine learning, deep learning, software engineering, medical image processing, smart agriculture, IoT, and blockchain systems. Her doctoral work centered around predictive models for software bug detection, a crucial area in software quality assurance. She has expanded her research scope into cutting-edge domains such as sentiment analysis, diabetic retinopathy classification, underwater fish species recognition, and accelerometer-based activity recognition. Her conference papers showcase broad engagement across themes like AI-driven fraud detection, supply chain optimization using blockchain, and environmental sustainability through data-driven methods. Dr. Siri is particularly passionate about applying machine learning models to real-world problems, including energy harvesting, biofuel production analysis, and healthcare diagnostics. Her interest in smart homes, watermarking in relational databases, and secure communication protocols demonstrates her comprehensive approach to data science and security. Her future research aims to further integrate AI and sustainable technologies for intelligent, real-time, and human-centric solutions.

Award and Honor🏆

Dr. D. Siri’s academic recognition stems from her impactful research contributions and innovative projects across diverse domains of computer science. While specific institutional awards are not listed, her numerous conference participations at esteemed platforms such as IEEE, AIP, and E3S Web of Conferences reflect her recognition as a capable and contributing researcher. Notably, she has published a patent titled “A Vehicle with Smart Biometric Device” in the Indian Patent Office Journal in 2018, which marks a significant milestone in her career and showcases her applied research capabilities. Her consistent participation in high-impact international conferences, including those focused on IoT, AI, sustainable development, and intelligent systems, highlights her evolving professional stature. She has also been part of multiple multi-author collaborations, emphasizing her ability to engage in large-scale academic networks. These achievements underscore her growing influence and suitability for national or international honors such as the Best Researcher Award.

Research Skill🔬

Dr. D. Siri possesses a strong suite of research skills that span both theoretical and practical domains. She is proficient in machine learning and deep learning algorithms, with hands-on experience in model building, classification, clustering, and data analysis across multiple platforms. Her expertise extends to software engineering principles, bug prediction models, and data mining techniques, especially in image processing and real-time sensor data applications. Dr. Siri is skilled in research design, implementation, and performance analysis, using tools like Python, MATLAB, and open-source AI frameworks. Her ability to integrate cross-disciplinary knowledge into practical systems—e.g., smart agriculture, biometric systems, blockchain-enabled secure communications, and medical diagnostics—speaks to her versatility. She has demonstrated competence in publishing high-quality technical articles, collaborating in multi-author projects, and contributing to peer-reviewed journals. With a solid foundation in algorithms, data structures, and AI ethics, she is adept at conducting innovative, scalable, and socially impactful research.

Conclusion💡

Dr. D. Siri demonstrates a strong commitment to academic and applied research, with a focus on cutting-edge technologies such as machine learning, deep learning, blockchain, and image processing. Her recent publication momentum, wide interdisciplinary contributions, and teaching legacy make her a suitable and deserving candidate for the Best Researcher Award.

With improvements in high-impact journal publications, international presence, and research funding, she has the potential to further solidify her stature as a leading researcher in her field.

Publications Top Noted✍

  • Title: Analyzing Public Sentiment on the Amazon Website: A GSK-Based Double Path Transformer Network Approach for Sentiment Analysis
    Authors: LK Kumar, VN Thatha, P Udayaraju, D Siri, GU Kiran, BN Jagadesh, …
    Year: 2024
    Citations: 17

  • Title: Segmentation Using the IC2T Model and Classification of Diabetic Retinopathy Using the Rock Hyrax Swarm-Based Coordination Attention Mechanism
    Authors: BN Jagadesh, MG Karthik, D Siri, SKK Shareef, SV Mantena, R Vatambeti
    Year: 2023
    Citations: 14

  • Title: Breast Cancer Diagnosis from Histopathology Images Using Deep Learning Methods: A Survey
    Authors: V Patel, V Chaurasia, R Mahadeva, A Ghosh, S Dixit, B Suthar, V Gupta, D Siri, …
    Year: 2023
    Citations: 6

  • Title: Detecting Cardiomegaly from CXR Images Using a 2D and 1D Convolutional Neural Network-Based Classifier
    Authors: LR Kumar, K Sravanthi, ES Kiran, D Vinith, D Siri, SK Joshi
    Year: 2023
    Citations: 5

  • Title: Enhanced Deep Learning Models for Automatic Fish Species Identification in Underwater Imagery
    Authors: D Siri, G Vellaturi, SHS Ibrahim, S Molugu, VS Desanamukula, …
    Year: 2024
    Citations: 3

  • Title: Machine Learning Algorithm Application in Software Quality Improvement Using Metrics
    Authors: D Siri
    Year: 2019
    Citations: 3

  • Title: Automated System for Bird Species Identification Using CNN
    Authors: D Siri, S Desu, K Alladi, D Swathi, S Singh, V Srilakshmi
    Year: 2023
    Citations: 2

  • Title: Cloud Verse: Mapping the New Frontiers of Cloud Computing
    Authors: H Bommala, DH Tej, K Ramesh, M Sahil, D Siri, KI Usanova
    Year: 2024
    Citations: 1

  • Title: Study of a Fuzzy Logic-Based Approach to Supplier Selection
    Authors: S Singarapu, D Siri, DV Nemova
    Year: 2024
    Citations: 1

  • Title: Segment-Based Unsupervised Deep Learning for Human Activity Recognition Using Accelerometer Data and SBOA-Based Channel Attention Networks
    Authors: M Janardhan, A Neelima, D Siri, RS Kumar, N Balakrishna, N Sreenivasa, …
    Year: Not listed
    Citations: 1

  • Title: Bio-Inspired Feature Selection and Graph Learning for Sepsis Risk Stratification
    Authors: D Siri, R Kocherla, S Tumkunta, P Udayaraju, KC Gogineni, G Mamidisetti, …
    Year: 2025

  • Title: Enhancing Sparse Data Recommendations with Self-Inspected Adaptive SMOTE and Hybrid Neural Networks
    Authors: R Vatambeti, HP Gandikota, D Siri, G Satyanarayana, N Balayesu, …
    Year: 2025

  • Title: Piezoelectric Actuator Characterization Through Piezoresponse Force Microscopy (PFM) Analysis
    Authors: B Singh, RD Nautiyal, K Kumar, AK Pandey, D Siri
    Year: 2025

  • Title: Process Planning and Scheduling Optimization for Low Fossil-Carbon Manufacturing
    Authors: V Sharma, M Nautiyal, P Bhandari, L Govardhan, D Siri
    Year: 2025

  • Title: Analyzing Size’s Impact on Tensile Strength of Polymer Nanocomposites: Mechanical Testing and Material Characterization
    Authors: G Nijhawan, SS Sehgal, S Sharma, D Siri
    Year: 2025

  • Title: A Strong and Adaptable Watermarking Methodology for Relational Databases
    Authors: D Siri, S Sangeetha, P Kalaiselvi, D VC, HMM AlJawahry, R Behl
    Year: 2025

  • Title: Deep Learning Based Smart Home
    Authors: D Siri, KV Laxmi, NK Nivetha, R AlFatlawy, B Rampriya
    Year: 2025

    Title: Enhancing Strategic Marketing with AI-Driven Insights into Dynamic Preferences and Decision Patterns
    Authors: VH Raj, TMK Al-Rubaye, D Siri, N Sirisha, A Dutt
    Year: 2025

  • Title: Optimizing Crop Manufacturing: Combining IoT, Smart Technology, and Information Mining for Sustainable
    Authors: P Karuppasamy, D Siri, AS Shaik, TS Madhuri, MH Fallah
    Year: 2025

  • Title: Implementation and Impact Assessment of Organic Crop Rotation Techniques for Soil Health Improvement in Temperate Agroecosystems
    Authors: AH Shnain, Z Abed, D Siri
    Year: 2025

Daneesha Ranasinghe | Urban Planning | Best Researcher Award

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Ms . Daneesha Ranasinghe | Urban Planning | Best Researcher Award

Research Assistant at University of Moratuwa, Sri Lanka

Daneesha Ranasinghe is an emerging researcher in urban planning, currently pursuing a Master of Science by Research at the University of Moratuwa, Sri Lanka. With a robust academic background in Town and Country Planning, she specializes in integrating technology—particularly mobile augmented reality—into urban design to foster youth engagement and participatory development. Her research projects span disaster education, risk-sensitive planning, and community cohesion, with collaborations both locally and internationally, including with the University of Salford, UK. Daneesha has presented her work at prestigious conferences and has published in high-impact journals, earning accolades such as Best Paper at ICSBE 2024. In addition to her academic pursuits, she is deeply involved in student leadership, organizing technological exhibitions, delivering guest lectures, and engaging in outreach activities. Her interdisciplinary approach, strong communication skills, and technical expertise position her as a promising voice in shaping inclusive and resilient urban futures.

Professional Profile

Education🎓 

Daneesha Ranasinghe is academically grounded in urban and regional planning, beginning with her Bachelor of Science (Hons) in Town and Country Planning from the University of Moratuwa, where she graduated with a GPA of 3.41 (Second Class Upper Division) between 2017 and 2021. She is currently enrolled in a Master of Science by Research at the same institution, focusing on mobile augmented reality and youth engagement in urban planning. Her earlier education includes Advanced Level studies at D. S. Senanayake College in Ampara (2013–2015) and Ordinary Level studies at Pushpadana Girls’ College, Kandy (2007–2013). Complementing her formal education, Daneesha has completed certificate courses in Electronic Media Presentation and Editing (Best Media Network, 2016), and Professional English and Computer Applications (National Youth Services Council, 2013). Her educational trajectory reflects a blend of technical, technological, and communication-oriented learning, equipping her to tackle interdisciplinary challenges in urban research and innovation.

Professional Experience📝

Daneesha Ranasinghe currently serves as a Research Assistant at the University of Moratuwa, actively contributing to multiple cutting-edge research projects that blend technology with urban planning. Her professional experience includes involvement in initiatives such as the TRANSCEND project led by the University of Salford, UK, focusing on risk-sensitive urban development, and Project ENSEMBLE, which explores resilience and social cohesion through community and spatial transformation. She previously completed an internship at the Sri Lanka Tourism Development Authority as a Project Management Trainee. Daneesha has also contributed to university-funded research on involving children in urban planning and has served as a guest lecturer, presenting on applications of geo-informatics such as AR and VR in planning. Her work is not limited to academia; she has been part of event organizing committees, technological exhibitions, and public engagement programs, making her professional journey both dynamic and impactful in the fields of planning, education, and research dissemination.

Research Interest🔎

Daneesha Ranasinghe’s research interests lie at the intersection of urban planning, digital technology, and community engagement. She is particularly focused on how mobile augmented reality (AR) and gamification can be employed to enhance youth involvement in urban design and disaster education. Her academic work explores participatory planning methods, spatial data visualization, and interactive platforms to make urban development more inclusive, resilient, and data-driven. She has engaged in systematic literature reviews and empirical studies addressing flood preparedness, risk-sensitive urban development, and the use of serious games for social learning. Daneesha’s interest in child-friendly cities, crowdsourced data, and placemaking further reflects her passion for community-oriented and technology-driven research. Through collaborative projects and real-world implementations, she seeks to bridge the gap between policymakers, planners, and the public, particularly marginalized groups like youth and children. Her interdisciplinary approach aims to revolutionize how cities are designed, experienced, and sustained in the face of emerging global challenges.

Award and Honor🏆

Daneesha Ranasinghe has received several accolades in recognition of her academic and extracurricular excellence. Most notably, she was awarded Best Paper in the Special Session of Sustainable Construction at the 15th International Conference on Sustainable Built Environment (ICSBE) 2024. She is also a University Color Awardee at the Sri Lanka University Games (SLUG 2019) for her achievements in sports, including her role as a Karate (Kumite) Champion at the Western Province Karate Championship in 2019. In her school years, she received the School Color Award from Pushpadana Girls’ College in 2012 and participated actively in guiding and leadership activities. She has also been a delegate for UNICEF at the International Model United Nations (IMUN) 37.0, reflecting her engagement in global dialogue. Additionally, she has been recognized for her leadership in student associations such as the Young Planner’s Forum and the Mora Hiking Club, further showcasing her diverse and impactful contributions.

Research Skill🔬

Daneesha Ranasinghe demonstrates a diverse and practical skill set essential for contemporary urban research. Her technical proficiencies include GIS & Remote Sensing, AutoCAD, SketchUp Pro, and Unity, all of which support her development of augmented reality applications and spatial analyses. She is skilled in project management, critical thinking, team collaboration, and public communication, ensuring her effectiveness in both research and community engagement settings. Daneesha’s expertise in designing and deploying mobile and web-based platforms, including gamified applications and crowdsourcing tools, underscores her ability to merge technology with participatory planning. Her experience with data visualization and systematic literature reviews further enhances her analytical capacity. Through multi-institutional collaborations, she has refined her skills in stakeholder engagement, risk communication, and disaster education. Her fluency in academic writing and publishing in Q1/Q2 journals reflects a strong command of research communication. Overall, her skill set is both broad and specialized, ideal for interdisciplinary urban innovation.

Conclusion💡

Daneesha Ranasinghe exhibits outstanding potential and is a highly promising candidate for the Best Researcher Award, particularly in the early-career or emerging researcher category. Her innovative work in integrating mobile augmented reality, youth engagement, and participatory urban planning—along with strong publication records and international collaboration—marks her as an exceptionally forward-thinking researcher.

If the award category considers early-career excellence and potential, she is a strong contender. With time and further experience, she is also likely to become a top-tier candidate for major national and international recognitions in the research and urban innovation fields.

Publications Top Noted✍

  • Title: CityBuildAR: Enhancing Community Engagement in Placemaking Through Mobile Augmented Reality
    Authors: Daneesha Ranasinghe, Nayomi Kankanamge, Chathura Kovida De Silva, Nuwani Kangana, Rifat Mahamood, Tan Yigitcanlar
    Year: 2025
    Citation: Ranasinghe, D., Kankanamge, N., De Silva, C. K., Kangana, N., Mahamood, R., & Yigitcanlar, T. (2025). CityBuildAR: Enhancing Community Engagement in Placemaking Through Mobile Augmented Reality. Future Internet, 17(3), 115. https://doi.org/10.3390/fi17030115

  • Title: Bridging Community Engagement and Technological Innovation for Creating Smart and Resilient Cities: A Systematic Literature Review
    Authors: Nuwani Kangana, Nayomi Kankanamge, Chathura Kovida De Silva, Ashantha Goonetilleke, Rifat Mahamood, Daneesha Ranasinghe
    Year: 2024
    Citation: Kangana, N., Kankanamge, N., De Silva, C. K., Goonetilleke, A., Mahamood, R., & Ranasinghe, D. (2024). Bridging Community Engagement and Technological Innovation for Creating Smart and Resilient Cities: A Systematic Literature Review. Smart Cities, 7(6), 3823–3852. https://doi.org/10.3390/smartcities7060147

  • Title: CityBuildAR: Enhancing Community Engagement in PlaceMaking through Mobile Augmented Reality (Working Paper)
    Authors: Daneesha Ranasinghe, Nayomi Kankanamge, Chathura Kovida De Silva, Nuwani Kangana, Rifat Mahamood, Tan Yigitcanlar
    Year: 2024
    Citation: Ranasinghe, D., Kankanamge, N., De Silva, C. K., Kangana, N., Mahamood, R., & Yigitcanlar, T. (2024). CityBuildAR: Enhancing Community Engagement in PlaceMaking through Mobile Augmented Reality. Preprints, https://doi.org/10.20944/preprints202412.1327.v1

Huanyu Li | Underwater Image Captioning | Best Researcher Award

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Mr . Huanyu Li | Underwater Image Captioning | Best Researcher Award

Ph.D. Candidate at China University of Petroleum (East China), China

Huanyu Li is a Ph.D. candidate at the China University of Petroleum (East China), specializing in Marine Resources and Information Engineering. He is an emerging researcher in the field of underwater image processing, focusing on intelligent systems, cross-modal learning, and deep learning model compression. With an impressive array of publications in top-tier journals such as ISPRS Journal of Photogrammetry and Remote Sensing and IEEE Transactions on Geoscience and Remote Sensing, his work bridges advanced computer vision techniques with marine environmental applications. Huanyu Li has actively contributed to international conferences and serves as a reviewer for leading journals, showcasing his academic reliability and engagement. His interdisciplinary research has led to practical implementations, including real-time image captioning and lightweight CNNs for seed sorting systems. With a strong technical foundation and growing influence, he represents a new generation of researchers blending artificial intelligence with real-world marine challenges.

Professional Profile 

Education🎓 

Huanyu Li is currently pursuing a Doctoral degree (Ph.D.) at the China University of Petroleum (East China), majoring in Marine Resources and Information Engineering. His academic journey is rooted in a robust interdisciplinary curriculum that combines the fundamentals of marine sciences with advanced computational techniques. As a Ph.D. candidate, he has undertaken extensive coursework and research in areas such as underwater image processing, computer vision, deep learning, and semantic modeling. His education has been enriched through the development of research articles, participation in international academic conferences, and collaborative work with both faculty and fellow researchers. The rigorous academic environment at the China University of Petroleum has enabled him to explore emerging technologies, apply AI in marine domains, and develop innovative solutions for complex underwater imaging problems. This strong educational background has equipped him with both the theoretical knowledge and technical skillset necessary to lead research at the intersection of AI and oceanography.

Professional Experience📝

Although still in the doctoral phase of his academic career, Huanyu Li has gained significant professional experience through active participation in research projects, publication of scholarly articles, and peer-review activities. He has co-authored multiple research papers in collaboration with established academics and contributed to projects involving underwater image captioning, convolutional neural networks, and AI-based image analysis. His work spans across both journal articles and conference proceedings, where he has served as a presenting author and co-investigator. Additionally, Huanyu has contributed to practical applications such as real-time seed sorting systems, lightweight model deployment, and image enhancement techniques. He has also served as a reviewer for high-impact journals including IEEE Transactions on Geoscience and Remote Sensing, Pattern Recognition, and Neural Computing and Applications, indicating his integration into the broader scientific community. These professional activities have provided him with a rich experience in experimental design, algorithm development, and scholarly communication.

Research Interest🔎

Huanyu Li’s research interests lie at the intersection of artificial intelligence and marine environmental analysis. His primary focus is on underwater image intelligent processing, where he investigates techniques to enhance image quality, recognition, and interpretation in complex underwater environments. He is deeply engaged in image-semantic cross-modal learning, aiming to develop models that bridge visual content with textual understanding, such as underwater image captioning. Another core area of interest is deep learning model compression, where he explores methods to reduce model size and computational requirements without sacrificing performance—enabling real-time processing in resource-constrained scenarios. His research also touches on underwater acoustic communication and attention-based fusion techniques. These interests demonstrate a multidisciplinary approach that combines computer vision, machine learning, signal processing, and marine science. By leveraging AI-driven innovations, he aims to solve real-world challenges in ocean exploration, ecological monitoring, and underwater robotics.

Award and Honor🏆

While specific awards and honors are not detailed in the current profile, Huanyu Li’s accomplishments are evident through the recognition he has received from the academic community. His research has been published in leading international journals such as ISPRS Journal of Photogrammetry and Remote Sensing, Information Fusion, and IEEE Transactions on Geoscience and Remote Sensing—a significant achievement for a doctoral researcher. Furthermore, his invited participation in major conferences and peer-review roles for journals like Pattern Recognition and Neural Networks suggest high regard among his peers. These roles are typically extended to researchers with proven expertise, highlighting his growing reputation. His innovative work on underwater image captioning and real-time image processing systems positions him as a strong candidate for future academic awards, fellowships, and research grants. His academic service, publication record, and practical contributions reflect an honors-worthy trajectory within the field of intelligent vision systems and marine computing.

Research Skill🔬

Huanyu Li possesses a comprehensive and evolving research skill set tailored to modern challenges in computer vision and underwater imaging. His core competencies include deep learning, particularly convolutional neural networks (CNNs), model pruning, and cross-modal learning. He is proficient in developing and optimizing AI algorithms for image captioning, classification, enhancement, and compression. His skills extend to semantic understanding of images, where he connects visual data to textual outputs, enhancing interpretability. Huanyu is also experienced in accelerated computing, using techniques like TensorRT for deploying real-time systems. Additionally, he has practical expertise in entropy-based optimization and 2D information theory for CNN design. His work includes implementing visual attention mechanisms and designing lightweight models for efficient deployment. With a hands-on approach to both algorithmic innovation and applied engineering, Huanyu’s research skills align with the needs of both academic exploration and real-world application in underwater exploration and smart marine systems.

Conclusion💡

Huanyu Li is a highly promising and technically proficient early-career researcher whose contributions in underwater image processing and intelligent systems are both innovative and well-published. His strong academic output, interdisciplinary research, and peer recognition make him a strong candidate for the Best Researcher Award, particularly in the emerging researcher or early-career category.

To further elevate his candidacy for broader or senior-level recognition, increasing leadership visibility, international collaboration, and showcasing real-world impact would be beneficial in the future.

Publications Top Noted✍

  • Title: Underwater Image Captioning via Attention Mechanism Based Fusion of Visual and Textual Information
    Authors: Li Li, Huanyu Li, Peng Ren
    Year: 2025
    Citation: DOI: 10.1016/j.inffus.2025.103269

  • Title: Underwater Image Captioning: Challenges, Models, and Datasets
    Authors: Huanyu Li, Hao Wang, Ying Zhang, Li Li, Peng Ren
    Year: 2025
    Citation: DOI: 10.1016/j.isprsjprs.2024.12.002

  • Title: An Underwater Acoustic Semantic Communication Approach to Underwater Image Transmission
    Authors: Ying Zhang, Huanyu Li, Bingyu Li, Li Li, Weibo Zhang, Hao Wang, Peng Ren
    Year: 2025
    Citation: DOI: 10.1007/s44295-025-00054-7

  • Title: A Real-Time and High-Performance MobileNet Accelerator Based on Adaptive Dataflow Scheduling for Image Classification
    Authors: Xiaoting Sang, Tianyi Ruan, Chunlei Li, Huanyu Li, Rui Yang, Zhen Liu
    Year: 2024
    Citation: DOI: 10.1007/s11554-023-01378-5

  • Title: INSPIRATION: A Reinforcement Learning-Based Human Visual Perception-Driven Image Enhancement Paradigm for Underwater Scenes
    Authors: Hao Wang, Shuhan Sun, Linlin Chang, Huanyu Li, Weibo Zhang, Alejandro C. Frery, Peng Ren
    Year: 2024
    Citation: DOI: 10.1016/j.engappai.2024.108411

  • Title: A Real-Time and High-Performance MobileNet Accelerator Based on Adaptive Dataflow Scheduling for Image Classification (Preprint)
    Authors: Xiaoting Sang, Tianyi Ruan, Chunlei Li, Huanyu Li, Rui Yang, Zhen Liu
    Year: 2023
    Citation: DOI: 10.21203/rs.3.rs-3132056

  • Title: An Accelerating Convolutional Neural Networks via a 2D Entropy Based-Adaptive Filter Search Method for Image Recognition
    Authors: Chunlei Li, Huanyu Li, Guangshuai Gao, Zhen Liu, Peng Liu
    Year: 2023
    Citation: DOI: 10.1016/j.asoc.2023.110326

  • Title: Real-Time Seed Sorting System via 2D Information Entropy-Based CNN Pruning and TensorRT Acceleration
    Authors: Chunlei Li, Huanyu Li, Liang Liao, Zhen Liu, Yizhou Dong
    Year: 2023
    Citation: DOI: 10.1049/ipr2.12747

  • Title: A Block-Based and Highly Parallel CNN Accelerator for Seed Sorting
    Authors: Xiaoting Sang, Zhenghui Hu, Huanyu Li, Chunlei Li, Zhen Liu
    Year: 2022
    Citation: DOI: 10.1155/2022/5608573

  • Title: Rapid and High-Purity Seed Grading Based on Pruned Deep Convolutional Neural Network
    Authors: Huanyu Li, Cuicao Zhang, Chunlei Li, Zhen Liu, Yizhou Dong, Shuhang Tang
    Year: 2022
    Citation: DOI: 10.1007/978-3-031-02444-3_8

  • Title: AMDet: An Efficient Infrared Small Object Detection Model Based on Visual Attention and Multi-Dilation Feature
    Authors: Cuicao Zhang, Yizhou Dong, Huanyu Li, Chunlei Li, Zhen Liu
    Year: 2021
    Citation: DOI: 10.1145/3497623.3497644

  • Title: SeedSortNet: A Rapid and Highly Efficient Lightweight CNN Based on Visual Attention for Seed Sorting
    Authors: Chunlei Li, Huanyu Li, Zhen Liu, Bing Li, Yong Huang
    Year: 2021
    Citation: DOI: 10.7717/peerj-cs.639

Debasish Roy | Emerging Trends and Future Directions | Best Researcher Award

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Dr . Debasish Roy | Emerging Trends and Future Directions | Best Researcher Award

CER Researcher at IIt Kharagpur, India

Dr. Debasish Roy, IPS, is a distinguished officer from the 1990 batch of the Indian Police Service, known for his dynamic leadership and research-driven approach to governance and public safety. With a rich blend of academic excellence and operational expertise, he has significantly contributed to modernization in law enforcement, including pioneering community outreach programs, technological upgrades, and capacity-building initiatives. His intellectual pursuits led to a Ph.D. in 2015, followed by multiple research publications in prestigious journals like IEEE and Elsevier. Dr. Roy has held several key positions across West Bengal, demonstrating exceptional competence in areas such as crime investigation, training, telecommunications, and administrative reform. As a technocrat and scholar, he brings a holistic and future-oriented vision to public service. His career reflects a unique integration of academic rigor with practical law enforcement, earning him commendations and accolades at the state and national levels.

Professional Profile 

Education🎓

Dr. Debasish Roy holds an exceptional academic portfolio encompassing degrees in engineering, computer applications, and management, topped with a doctorate. He began his academic journey with a Bachelor of Engineering (BE), followed by a Master of Computer Applications (MCA) and a Master of Technology (M.Tech), equipping him with advanced knowledge in technical systems and IT. He later pursued a Master of Business Administration (MBA), strengthening his foundation in leadership and administrative strategy. His academic trajectory culminated in a Ph.D. from Techno India University in 2015, where he focused on areas intersecting technology and governance. This multidisciplinary education has empowered Dr. Roy to bridge the gap between policy-making and research. His deep-rooted commitment to lifelong learning is evident not only in his formal degrees but also in the way he applies this academic acumen to practical challenges in law enforcement, human rights, and police training.

Professional Experience📝

With over three decades of experience in the Indian Police Service, Dr. Debasish Roy has served in numerous critical roles across West Bengal, contributing to law enforcement, public administration, and strategic modernization. He has held leadership positions such as Special Commissioner of Police, Kolkata, ADG & IGP in Training, Armed Police, Telecommunication, and Head of Enforcement Branch, among others. As a field officer, he displayed exceptional competence in district policing and crime investigation. In senior roles, he spearheaded institutional reforms, training programs, and community projects like Goalz and Sukanya. He played a pivotal role in implementing e-Governance within the West Bengal Human Rights Commission and conducted large-scale training of police recruits. His leadership in combating highway crime, poppy cultivation, and Maoist activities reflects his operational excellence, while his strategic innovations in telecommunications and digitization showcase his futuristic vision. His career blends grassroots action with policy-level transformation.

Research Interest🔎

Dr. Roy’s research interests lie at the confluence of technology, governance, public safety, and human rights. He is particularly passionate about exploring how digital transformation and intelligent systems can enhance the efficiency, transparency, and accountability of law enforcement agencies. His doctoral work and subsequent publications focus on police modernization, surveillance technologies, communication infrastructure, and community policing models. Dr. Roy also has a strong interest in e-Governance systems, especially their role in judicial and administrative reforms. As the publisher of a peer-reviewed journal on human rights, he promotes interdisciplinary scholarship that merges legal, ethical, and technological frameworks. His work highlights the importance of research-led innovation in public service delivery. Through field application and academic analysis, he continues to contribute to evolving discourses in security informatics, telecommunication frameworks for policing, and data-driven decision-making within public sector institutions.

Award and Honor🏆

Dr. Debasish Roy has been the recipient of numerous awards and honors that recognize his integrity, professionalism, innovation, and academic contribution. He has been conferred with the prestigious Indian Police Medal (IPM) and President’s Police Medal (PPM) for his distinguished service. He has received formal commendations from senior officials, including the Commissioner of Police, Kolkata, and Director General & Inspector General of Police, West Bengal, for exemplary leadership during critical events and public gatherings. His effective handling of law-and-order situations during festivals, elections, and high-risk operations has earned him accolades across different postings. Additionally, his contributions to training, e-Governance, and police modernization have been widely appreciated. His efforts in publishing and peer-reviewing academic content have also drawn recognition within the scholarly community. These honors reflect a rare combination of operational excellence, strategic innovation, and academic dedication in a high-stakes public service environment.

Research Skill🔬

Dr. Debasish Roy demonstrates a high level of competence in applied research methodologies, especially in integrating academic knowledge with field-level applications in policing and governance. He is proficient in technical writing, data analysis, and scholarly communication, having published multiple papers in reputed international journals like IEEE, Springer, Elsevier, and Taylor & Francis. His ability to lead and contribute to interdisciplinary research makes him adept at addressing complex societal problems through a combination of law enforcement insights and academic frameworks. Dr. Roy has practical experience in developing training modules, editing peer-reviewed journals, and leading institutional research initiatives, such as the Journal of Human Rights Commission. His strong analytical skills, combined with deep operational knowledge, allow him to frame relevant research questions, apply empirical methods, and derive actionable conclusions. His work exemplifies the application of research in technology adoption, human rights, and organizational development within public institutions.

Conclusion💡

Dr. Debasish Roy, IPS, demonstrates an outstanding and unique blend of public service leadership and academic excellence. His ability to implement research-driven reforms in law enforcement and governance, publish scholarly work, and lead institutional modernization initiatives makes him a strong candidate for the Best Researcher Award, especially in the domains of applied technology, human rights, e-governance, and public administration research.

Publications Top Noted✍

  • Title: Quantum-secure protocols for privacy preserving location based services
    Authors: Sushmita Sarkar, Tapaswini Mohanty, Vikas Srivastava, Debasish Roy, Sumit Kumar Debnath, Sihem Mesnager, Sourav Mukhopadhyay
    Year: 2025
    Citation: Optical Switching and Networking, October 2025, DOI: 10.1016/j.osn.2025.100811

  • Title: A New Hybrid Algorithm for Multivariate Polynomial System Solving
    Authors: Debasish Roy
    Year: 2024
    Citation: SN Computer Science, March 27, 2024, DOI: 10.1007/s42979-024-02645-3

Lorenzo Pedrolli | Industrial and Manufacturing Applications | Best Researcher Award

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Assist . Prof . Dr . Lorenzo Pedrolli | Industrial and Manufacturing Applications | Best Researcher Award

Assistant Prof. Dr. at University of Deusto, Spain

Dr. Lorenzo Pedrolli is an emerging expert in the field of applied mechanics, with a strong focus on computational fluid dynamics (CFD), discrete element modeling (DEM), and particulate material handling for additive manufacturing. Currently serving as an Assistant Professor at the University of Deusto, he has developed significant research on pneumatic conveying of metal powders and the adhesive properties of particulate materials. His scholarly output includes several peer-reviewed publications and presentations at internationally acclaimed conferences. With a background that bridges academic rigor and industrial application, Dr. Pedrolli has collaborated with institutions such as Fraunhofer IZM and contributed to Horizon 2020 projects. Multilingual and highly versatile, he excels in both teaching and research environments. His deep technical knowledge, combined with hands-on experience in system design, makes him a well-rounded academic contributing to advances in mechatronics, powder technology, and simulation-based engineering approaches.

Professional Profile 

Education🎓

Dr. Lorenzo Pedrolli has pursued a progressive educational path rooted in mechanical and mechatronic engineering. He began with a Technical High School Diploma in Mechanics from Istituto Tecnico Industriale “M. Buonarroti,” where he ranked among the top students nationally in engineering competitions. He earned his Bachelor’s and Master’s degrees in Industrial and Mechatronic Engineering respectively from the University of Trento, where he graduated with commendable scores. His academic journey culminated in a Ph.D. from the University of Deusto under the prestigious 6i Dirs MSC COFUND program, focusing on the CFD-DEM simulation of metallic powder flow in laser metal deposition systems. His educational foundation reflects a strong combination of theoretical understanding, practical application, and cross-disciplinary integration. Throughout his studies, Dr. Pedrolli has demonstrated academic excellence, research innovation, and an unwavering commitment to advancing engineering science, particularly in the areas of fluid-particle interaction and additive manufacturing processes.

Professional Experience📝

Dr. Lorenzo Pedrolli has amassed a diverse range of academic and industrial experiences across Europe. Currently, he serves as an Assistant Professor at the University of Deusto, where he lectures on applied mechanics and material science. Previously, he taught subjects such as pneumatic systems and industrial organization at the University of Trento and Technical High School “M. Buonarroti.” His industry roles include mechanical system design and R&D with leading companies such as PAMA S.p.A. and Ducati Energia S.p.A., where he contributed to flywheel-based energy systems and machining center design. Additionally, he worked as a researcher at Fraunhofer IZM on 3D integration for high-energy physics detectors under a Marie Skłodowska-Curie grant. Dr. Pedrolli also operated as a freelance designer, applying LEAN optimization techniques in mechatronic system development. This comprehensive mix of roles underlines his unique ability to blend teaching, research, and engineering expertise in academic and applied contexts.

Research Interest🔎

Dr. Lorenzo Pedrolli’s research interests lie at the intersection of computational mechanics, particle technology, and additive manufacturing. He specializes in Computational Fluid Dynamics (CFD) and Discrete Element Modeling (DEM), particularly in the simulation of gas-solid interactions in processes such as pneumatic conveying and laser metal deposition. His work contributes to the optimization of powder flow behavior in complex geometries, supporting industrial innovation in the fields of advanced manufacturing and material processing. He is also deeply engaged in studying the surface energy and adhesive properties of powders, developing kinetic adhesion tests and analytical methodologies. Furthermore, his research integrates multi-scale modeling, validation of numerical methods, and experimental techniques to enhance accuracy in material behavior prediction. Through international collaborations and conference presentations, he continues to explore interdisciplinary links across mechanical engineering, materials science, and applied physics, driving forward novel solutions in simulation-driven design and smart manufacturing systems.

Award and Honor🏆

Dr. Lorenzo Pedrolli has received various accolades that reflect his academic excellence and engineering aptitude. During his early academic career, he was recognized as the third-best performer in the National Engineering Competition (2007) in Italy. His Ph.D. journey at the University of Deusto was supported by the 6i Dirs MSC COFUND fellowship, a prestigious EU-funded program promoting interdisciplinary research and mobility. Additionally, he was awarded a Marie Skłodowska-Curie scholarship as part of the Horizon 2020 STREAM project at Fraunhofer IZM, focusing on cutting-edge sensor integration for high-energy physics. These honors underscore his strong research potential and international credibility. His consistent participation in prominent conferences such as CHoPS and OpenFOAM Workshops, where he has presented novel simulation and modeling research, further enhances his professional recognition. These achievements highlight his role as a promising and globally oriented researcher in the field of mechanical and materials engineering.

Research Skill🔬

Dr. Lorenzo Pedrolli possesses a robust and multifaceted research skill set centered on simulation, experimental mechanics, and advanced modeling techniques. He is highly proficient in CFD and DEM modeling, using tools such as OpenFOAM to simulate complex gas-particle flows. His expertise extends to MP-PIC (Multiphase Particle-in-Cell) calibration and validation for additive manufacturing applications. He has developed and utilized kinetic adhesion tests to determine particle surface energy, showcasing both experimental design and analytical capabilities. With a solid grasp of mechatronic system design and mechanical optimization, he excels at translating theoretical models into real-world engineering solutions. His research skills are further complemented by his competence in programming, system integration, and data analysis. Additionally, he has hands-on experience in hardware prototyping and LEAN engineering methodologies. Combined with strong academic writing and scientific communication skills, Dr. Pedrolli’s research abilities position him as a dynamic contributor to innovation in particulate systems and advanced manufacturing.

Conclusion💡

Dr. Lorenzo Pedrolli is a highly promising and accomplished early-career researcher whose strong publication record, international conference presence, applied research background, and academic involvement make him a suitable and competitive candidate for the Best Researcher Award.

Publications Top Noted✍

  • Title: Shape optimization of a metallic flywheel using an evolutive system method: Design of an asymmetrical shape for mechanical interface
    Authors: L. Pedrolli, A. Zanfei, S. Ancellotti, V. Fontanari, M. Benedetti
    Year: 2018
    Citations: 12

  • Title: Comparison of CFD-DEM and MP-PIC in the Simulation of Metal Powder Conveying for Laser Metal Deposition
    Authors: L. Pedrolli, B.A. Menor, I.M. de Arenaza, A. Lopez
    Year: 2024
    Citations: 5

  • Title: Kinetic adhesion test to determine particle surface energy
    Authors: L. Pedrolli, S. Nadimi, S. Maramizonouz, B.A. Menor, A. López
    Year: 2023
    Citations: 5

  • Title: Estimation of mesoscale surface energy in the kinetic adhesion test
    Authors: L. Pedrolli, S. Nadimi, B. Achiaga, A. López
    Year: 2024
    Citations: 2

  • Title: High-speed video recordings of metal powder pneumatic conveying in thin capillary pipes
    Authors: L. Pedrolli, L. Fraccarollo, B. Achiaga, A. Lopez
    Year: 2025
    Citations: 1

  • Title: Caracterización avanzada de polvos
    Authors: B.A. Menor, B. Betto, V. Giraldi, L. Pedrolli, A. López
    Year: 2025

  • Title: Análisis de estructuras autoportantes en la tecnología aditiva fusión láser de lecho de polvo LPBF
    Authors: M.Á. Jankowski, L. Pedrolli, A. López, B. Ach
    Year: 2025

  • Title: Optical Particle Tracking in the Pneumatic Conveying of Metal Powders through a Thin Capillary Pipe
    Authors: L. Pedrolli, L. Fraccarollo, B. Achiaga, A. Lopez
    Year: 2024

  • Title: CFD-DEM Study of metallic powder flow in laser metal deposition
    Author: L. Pedrolli
    Year: 2024

kalaiselvi kaliannan | Wireless sensor networks | Best Researcher Award

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Dr . kalaiselvi kaliannan | Wireless sensor networks | Best Researcher Award

Associate Professor at SRM Institute of Science and Technology, India

Dr. K. Kalaiselvi is a seasoned academician and accomplished researcher with over 20 years of teaching and research experience in the field of Computer Science and Engineering. Currently serving as an Associate Professor at SRM Institute of Science and Technology, Chennai, she has consistently contributed to the advancement of wireless sensor networks and wireless body area networks. Her research portfolio includes more than 52 Scopus-indexed publications, 10 patents, and numerous international and national conference presentations. She is well-known for her leadership roles within academia, having served as a project coordinator, NBA coordinator, and industrial visit organizer, among others. Dr. Kalaiselvi has also demonstrated a strong commitment to mentoring, having guided several innovative student projects in advanced network protocols and security. Her contributions to applied research, academic excellence, and technical mentorship make her a highly respected figure in her field and a valuable asset to any institution or collaborative research initiative.

Professional Profile 

Education🎓

Dr. K. Kalaiselvi holds a Ph.D. in Computer Science and Engineering from Anna University, Chennai, awarded in 2020, with her doctoral work focused on Wireless Body Area Networks (WBANs). Her postgraduate education includes a Master of Engineering (M.E.) in Computer Science and Engineering from Annamalai University, Chidambaram, where she graduated with distinction and an outstanding OGPA of 8.62 in the academic year 2003–2005. She earned her Bachelor of Engineering (B.E.) degree in Computer Science and Engineering, also from Annamalai University, between 1999 and 2003, with a commendable aggregate of 71%. Her educational background lays a solid foundation in both theoretical principles and applied computer science, which she has effectively translated into her teaching, research, and innovation. Throughout her academic journey, Dr. Kalaiselvi has demonstrated a keen interest in advanced computing technologies and has consistently worked on enhancing her domain knowledge through various certifications and technical training programs.

Professional Experience📝

Dr. K. Kalaiselvi brings with her a rich professional experience spanning over two decades in higher education. She is presently an Associate Professor at SRM Institute of Science and Technology, Chennai, where she has been instrumental in academic instruction, curriculum development, and research mentorship. Previously, she served for nine years at Saveetha Engineering College, Chennai, where she contributed significantly to student development and institutional initiatives. She also held academic positions at KSR College of Technology, Tiruchengode, and Kongu Engineering College, Perundurai, gaining diverse exposure across reputed engineering institutions. Over the years, she has taught a wide range of undergraduate and postgraduate courses, including Data Structures, Operating Systems, DBMS, Java, and Wireless Sensor Networks. Apart from teaching, she has actively participated in academic administration and event coordination, earning recognition for her leadership in organizing technical events, coordinating projects, and contributing to accreditation efforts such as NBA. Her experience reflects a balanced blend of academic rigor and organizational excellence.

Research Interest🔎

Dr. K. Kalaiselvi’s research interests lie predominantly in the domains of Wireless Sensor Networks (WSN), Wireless Body Area Networks (WBAN), Computer Networks, and Data Structures. Her doctoral work explored clustering algorithms aimed at enhancing energy efficiency within WBANs—a critical concern in healthcare-related sensor deployments. She is particularly focused on developing intelligent algorithms for energy optimization, secure data transmission, and robust communication in sensor-based environments. In addition, she has contributed to research in healthcare informatics, XML schema design, and spatio-temporal data mining. Her interest in applied research is evident in her paper presentations at IEEE conferences and her proposal to DST under the Women Scientist Scheme on real-time health monitoring systems. Dr. Kalaiselvi also explores interdisciplinary applications of data mining and network algorithms in biomedical engineering. Through continuous learning and active participation in technical workshops and conferences, she stays abreast of emerging trends in embedded systems, IoT, and mobile computing networks.

Award and Honor🏆

Dr. K. Kalaiselvi has received several recognitions and honors that underscore her excellence in academic and research endeavors. She has published over 52 research papers indexed in Scopus and has been an active participant in many prestigious IEEE and international conferences, presenting innovative solutions in the field of wireless sensor networks. One of her major recognitions includes funding support from CSIR to organize a seminar on “Research Challenges in Grid Computing,” which reflects her capability to lead academic events of national relevance. She has submitted a proposal under the DST’s Women Young Scientist scheme, emphasizing her proactive approach toward impactful societal research. Dr. Kalaiselvi has also served as a judge and mentor in various inter-collegiate events and has led numerous institutional initiatives such as NBA coordination and curriculum development. Her patented innovations and commitment to both student success and institutional growth further exemplify her standing as a leading researcher and educator in her domain.

Research Skill🔬

Dr. K. Kalaiselvi possesses a comprehensive set of research skills that contribute to her distinction as a forward-thinking academic. She is proficient in algorithm design, data mining, and simulation tools for evaluating wireless network performance. Her expertise spans sensor network protocols, energy-efficient clustering techniques, and healthcare data analysis. She demonstrates strong technical writing skills, evident in her prolific publication record in Scopus-indexed journals and conferences. Dr. Kalaiselvi is skilled in using tools like NS2, MATLAB, and other network simulators, which support her experiments in wireless communication systems. She is also experienced in patent drafting and proposal writing, having authored multiple patents and submitted national-level funding proposals. Beyond technical competencies, she exhibits research leadership by mentoring student projects and facilitating research workshops. Her ability to combine theoretical knowledge with practical implementation equips her to address real-world problems in healthcare monitoring, embedded systems, and smart sensor applications with innovation and precision.

Conclusion💡

Dr. K. Kalaiselvi is a highly suitable candidate for the Best Researcher Award. Her prolific publication record, impactful patents, long-standing academic contributions, and dedication to applied research in wireless technologies make her a strong contender. With minor enhancements in global outreach, citation impact, and research funding, she is poised for even higher recognition in the academic research landscape.

Publications Top Noted✍

  • Title: An automation query expansion strategy for information retrieval by using fuzzy based grasshopper optimization algorithm on medical datasets
    Authors: R. Srivel; K. Kalaiselvi; S. Shanthi; Uma Perumal
    Year: 2023
    Citation: DOI: 10.1002/cpe.7418
    Note: Published in Concurrency and Computation: Practice and Experience

  • Title: RETRACTED ARTICLE: Performance Analysis of Malicious and Link Failure Detection System Using Deep Learning Methodology
    Authors: K. Kalaiselvi; L. Vanitha; K. Deepa Thilak; T. Rajesh Kumar; S. Saranya; K. Kumaresan
    Year: 2022
    Citation: DOI: 10.1007/s11277-021-08790-9
    Note: Published in Wireless Personal Communications

  • Title: Dynamic convolutional neural network based e‐waste management and optimized collection planning
    Authors: C. Jenifa Latha; K. Kalaiselvi; S. Ramanarayan; R. Srivel; S. Vani; T. V. M. Sairam
    Year: 2022
    Citation: DOI: 10.1002/cpe.6941
    Note: Published in Concurrency and Computation: Practice and Experience

  • Title: An adaptive predictor with Kalman filter based energy efficient protocol for WSN
    Authors: P. Tamil Selvan; S. Shaul Hammed; K. Kalaiselvi
    Year: 2019
    Citation: DOI: 10.5373/JARDCS/V11SP12/20193302
    Note: Published in Journal of Advanced Research in Dynamical and Control Systems

  • Title: An efficient approach for the detection of link failures in WBAN system for health care applications
    Authors: K. Kalaiselvi; G.R. Suresh; V. Ravi
    Year: 2019
    Citation: DOI: 10.1002/dac.4112
    Note: Published in International Journal of Communication Systems

  • Title: Detection of faults in flying wireless sensor networks using adaptive reinforcement learning
    Authors: G. Kiruthiga; K. Kalaiselvi; R.S. Shudapreyaa; V. Dineshbabu
    Year: 2019
    Citation: EID: 2-s2.0-85069902688
    Note: Published in International Journal of Recent Technology and Engineering

  • Title: Genetic algorithm based sensor node classifications in wireless body area networks (WBAN)
    Authors: K. Kalaiselvi; G.R. Suresh; V. Ravi
    Year: 2019
    Citation: DOI: 10.1007/s10586-018-1770-6
    Note: Published in Cluster Computing

  • Title: Distance based clustering algorithm for energy efficiency in wireless sensor networks
    Authors: K. Kalaiselvi; G.R. Suresh
    Year: 2014
    Citation: DOI: 10.4028/www.scientific.net/AMM.626.20
    Note: Published in Applied Mechanics and Materials

  • Title: Survey on data aggregation based algorithms for energy efficiency in wireless sensor networks
    Authors: K. Kalaiselvi; G.R. Suresh
    Year: 2014
    Citation: EID: 2-s2.0-84939553673
    Note: Published in International Journal of Applied Engineering Research

  • Title: Improved clustering protocol for energy efficiency algorithms in wireless sensor networks
    Authors: K. Kalaiselvi; G.R. Suresh
    Year: 2013
    Citation: DOI: 10.1109/ICCCNT.2013.6726812
    Note: Presented at 4th International Conference on Computing, Communications and Networking Technologies (ICCCNT)

 

Mikhail Zuev | Industrial and Manufacturing Applications | Best Researcher Award

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Prof . Mikhail Zuev | Industrial and Manufacturing Applications | Best Researcher Award

Chief researcher at Institute of Solid State Chemistry of the Ural Branch of the Russian Academy of Sciences, Russia

The candidate is a distinguished researcher and professor with a doctorate in chemistry, specializing in solid-state and inorganic chemistry. He currently serves as Chief Researcher of the Oxidation Systems Department at the Institute of Solid State Chemistry, Ural Branch of the Russian Academy of Sciences, and as Professor at the Department of Physical and Colloidal Chemistry, Ural Federal University. He has significantly contributed to the synthesis and study of complex oxide systems, including the development of new ternary and quaternary compounds. His innovative research extends to the creation of a new scientific field—solid-state medical chemistry—leading to the development of radiopaque substances for medical use. He has published over 170 scientific papers, authored nine monographs, and holds 33 Russian patents. His pioneering work in nanophosphors and magnetic field effects on photoluminescence demonstrates strong interdisciplinary expertise. Overall, his prolific career showcases a blend of theoretical excellence and applied innovation in material science.

Professional Profile 

Education🎓

The candidate obtained his doctoral degree in Chemistry with a focus on solid-state and physical chemistry. He completed his undergraduate and graduate studies at the Ural Polytechnic Institute named after S.M. Kirov, under the Faculty of Physics and Technology, a highly regarded institution in Russia. His academic training provided him with a deep foundation in the synthesis and characterization of inorganic and oxide materials, equipping him to pursue advanced research in physical and inorganic chemistry. Throughout his education, he developed a strong command of crystallography, spectroscopic techniques, and reaction mechanisms involved in solid-state processes. His formal education was marked by rigorous coursework and research that emphasized the principles of thermodynamics, kinetics, and material structure-property relationships. His transition from student to research scientist was grounded in this academic rigor, paving the way for his influential career as a leading researcher and professor in both scientific and interdisciplinary areas of chemistry.

Professional Experience📝

The candidate has built a robust professional career rooted in academic excellence and high-impact research. He holds the dual role of Chief Researcher at the Oxidation Systems Department of the Institute of Solid State Chemistry (Ural Branch of the Russian Academy of Sciences) and Professor at the Department of Physical and Colloidal Chemistry at Ural Federal University. His professional journey began shortly after completing his doctorate, evolving through years of hands-on experimental work, research leadership, and academic instruction. As a chief researcher, he has led numerous projects related to the synthesis and study of complex oxides, developing novel materials for various scientific and medical applications. As a professor, he has mentored graduate students, supervised theses, and designed advanced courses in solid-state and physical chemistry. His professional experience reflects a well-balanced career between fundamental research, innovation, academic mentorship, and contributions to scientific communities at both national and institutional levels.

Research Interest🔎

The candidate’s research interests lie primarily in the domains of solid-state chemistry, physical and inorganic chemistry, and the synthesis of advanced materials. He has focused extensively on the investigation of multi-component oxide systems involving elements from groups 3 and 5 of the periodic table, successfully modeling phase formation and studying the physicochemical properties of novel compounds. His research also explores the spectral behavior of nanosized phosphors, particularly those produced through pulsed electron beam evaporation—a unique and high-precision method. One of his major contributions includes the development of blue and white nanoamorphous phosphors and identifying how photoluminescence spectra shift in magnetic fields. Furthermore, his interest in applied science led to the creation of a new interdisciplinary field—solid-state medical chemistry—where he developed radiopaque compounds for diagnostic medicine. Overall, his research combines theoretical insights, advanced synthesis methods, and practical applications in material science, nanotechnology, and biomedical chemistry.

Award and Honor🏆

Throughout his career, the candidate has garnered numerous accolades that reflect his excellence in research, innovation, and scientific advancement. He holds 33 Russian patents, a testament to his original contributions to material synthesis and applied chemistry. His work has been widely recognized through the publication of over 170 research articles in reputed scientific journals, along with nine monographs that have contributed significantly to academic literature. While specific named awards or national/international recognitions were not explicitly mentioned, his appointment as Chief Researcher and Professor at prestigious institutions highlights the high regard in which he is held within the academic and research community. His innovative development of radiopaque substances and nanoscale phosphors further suggests his work may have practical and commercial value, potentially recognized through institutional or governmental channels. These accomplishments collectively underscore a career marked by scientific leadership, invention, and dedication to advancing the frontiers of chemistry.

Research Skill🔬

The candidate possesses an extensive array of research skills spanning both experimental and theoretical domains. He has expertise in the synthesis of complex oxide materials, including ternary and quaternary systems, using advanced solid-state and physicochemical methods. His proficiency in spectroscopy, crystallography, and phase modeling enables him to characterize and analyze the structural and optical properties of newly synthesized materials with precision. He is skilled in nanomaterial fabrication, particularly using pulsed electron beam evaporation, and has investigated magnetic field effects on photoluminescence—demonstrating deep technical acumen in nano-optical systems. He also pioneered a new area called solid-state medical chemistry, applying his skills to develop radiopaque materials with medical imaging applications. Furthermore, his ability to translate research into patents and monographs shows excellent documentation and innovation management skills. His multidisciplinary skill set bridges chemistry, materials science, and applied medical research, making him an asset in both academic and industrial research settings.

Conclusion💡

The candidate is highly suitable for the Best Researcher Award due to his exceptional contributions in solid state chemistry, material science innovation, and the creation of a new research discipline. His work bridges fundamental research and applied medical science, demonstrating both intellectual leadership and practical relevance. To further strengthen his candidacy on a global scale, increased international visibility and recent impact metrics could be beneficial. Nonetheless, his academic and inventive excellence makes him a worthy and commendable nominee for the award.

Publications Top Noted✍

  • Title: Influence of annealing on the physicochemical properties of 2L ferrihydrite synthesized by radiation-chemical method from iron (III) nitrate
    Year: 2024
    Citations: 0

  • Title: Threshold phenomena in photoluminescence of upconversion micro- and nanophosphors containing Er³⁺ and Yb³⁺ ions
    Authors: M.G. Zuev, V.G. Il’ves, S.Yu. Sokovnin, A.A. Vasin, E.Yu. Zhuravleva
    Year: 2024
    Citations: 0

  • Title: Effect of permanent magnetic field on photoluminescence of barium and calcium nanofluorides
    Authors: S.Yu. Sokovnin, V.G. Il’ves, M.G. Zuev
    Year: 2024
    Citations: 1

  • Title: Effect of air annealing on structural, textural, thermal, magnetic and photocatalytic properties of Ag-doped mesoporous amorphous crystalline nanopowders Bi₂O₃
    Authors: V.G. Ilves, V.S. Gaviko, A.M. Murzakaev, S.Y. Sokovnin, O.A. Svetlova, M.G. Zuev, M.A. Uimin
    Year: 2024
    Citations: 0

  • Title: Luminescent manifestations of ytterbium ions in the crystal structure of silicate apatite
    Year: 2024
    Citations: 1

  • Title: Synthesis, Structure, and Luminescence Properties of Anion-Substituted Germanates Ca₂La₇.₂Eu₀.₈(GeO₄)₆−ₓ(PO₄)ₓO₂+ₓ⁄₂ with an Apatite-Type Structure
    Year: 2024

  • Title: Radiation-chemical synthesis and characterization of ferrihydrite from iron (III) nitrate
    Authors: [Not fully listed]
    Year: 2024
    Citations: 2

  • Title: Properties of an amorphous crystalline nanopowder Si–SiO₂ produced by pulsed electron beam evaporation
    Authors: V.G. Ilves, M.G. Zuev, A.A. Vasin, P.M. Korusenko, S.Yu. Sokovnin, M.V. Ulitko, A.S. Gerasimov
    Year: 2024
    Citations: 4

Abdul Wasay | Wireless Sensor Networks | Best Researcher Award

Posted on by Computer Vision Awards

Dr . Abdul Wasay | Wireless Sensor Networks | Best Researcher Award

Asst Professor at DCET, India

Mr. H. Abdul Wasay is a committed academician and researcher in the field of Electronics and Communication Engineering, with over 14 years of teaching and mentoring experience. Currently serving at Deccan College of Engineering and Technology, Hyderabad, he has contributed extensively to undergraduate and postgraduate education, academic development, and department-level leadership roles. He is presently pursuing a Ph.D. in Electronics and Communication Engineering with a focus on Wireless Sensor Networks, particularly on bio-inspired optimization algorithms. With a solid foundation in Communication and Signal Processing, he has published multiple research papers in Scopus-indexed and SCI journals and presented his work at IEEE international conferences. His approach to education is complemented by active participation in institutional development activities such as NBA accreditation, examination coordination, and student guidance. Mr. Wasay’s balanced engagement in research, teaching, and academic service highlights his dedication to both knowledge creation and dissemination.

Professional Profile 

Education🎓

Mr. Abdul Wasay has pursued a robust academic journey rooted in Electronics and Communication Engineering. He is currently pursuing a Ph.D. in Electronics and Communication Engineering from Sathyabama University, Chennai, with a research focus on Wireless Sensor Networks using bio-inspired algorithms. He holds a Master of Technology degree in Communication and Signal Processing from Sri Krishnadevaraya University, Anantapur, completed in 2011. His undergraduate studies were completed in 2009, earning a Bachelor of Technology degree in Electronics and Communication Engineering from Jawaharlal Nehru Technological University, Anantapur. His early academic credentials include intermediate education from the Board of Intermediate Education and secondary education (S.S.C.) from the Board of Secondary Education, both from Hyderabad. His academic foundation is strengthened by a combination of theoretical knowledge and hands-on experience, which has shaped his ability to teach complex engineering subjects and guide student research effectively.

Professional Experience📝

Mr. Wasay brings over 14 years of teaching experience at the undergraduate and postgraduate levels in the domain of Electronics and Communication Engineering. Currently serving at Deccan College of Engineering & Technology, Hyderabad, he has handled various core subjects such as Analog and Digital Communication, Electronic Devices and Circuits, Instrumentation Engineering, and Digital Electronics. He has also supervised laboratory sessions in Microwave Engineering, Microprocessors, and Basic Electronics. Beyond teaching, he has taken on key administrative and academic responsibilities, including department in-charge for NBA accreditation, university exam coordinator, group tutor, and member of the timetable committee. He has guided several student projects at both UG and PG levels, fostering research-based learning. His roles reflect not only academic excellence but also leadership, mentorship, and organizational capabilities. His dedication to creating a meaningful learning environment and developing technical competence among students has significantly enriched the institution’s academic reputation.

Research Interest🔎

Mr. Wasay’s research interests lie primarily in the area of Wireless Sensor Networks (WSNs), with a special focus on bio-inspired optimization algorithms. His Ph.D. research explores sensor deployment, coverage estimation, energy efficiency, and reliability using advanced algorithms like the Harris Hawk Optimization (HHO) technique. He is particularly interested in optimizing network performance by improving coverage and minimizing energy consumption, which are critical aspects in the design and operation of modern sensor-based systems. His research extends to addressing security challenges and resource allocation problems in WSNs, contributing towards sustainable and scalable IoT frameworks. Through the development and testing of hybrid optimization models, he aims to enhance the accuracy and efficiency of WSN deployments for real-world applications such as environmental monitoring and smart infrastructure. His work also involves simulation-based evaluations and algorithmic analysis, positioning him at the intersection of wireless communication, artificial intelligence, and embedded systems.

Award and Honor🏆

While Mr. Wasay has not listed formal awards or honors in the traditional sense, his recognition comes from his academic contributions and institutional responsibilities. He has earned professional credibility by publishing research in Scopus and SCI-indexed journals and presenting at IEEE international conferences, which signifies the value and acceptance of his work within the global research community. His selection as the Department NBA Accreditation In-charge is a mark of trust in his leadership and organizational capabilities. In addition, his role as University Examination Coordinator and active participation in student mentoring reflect his standing as a respected faculty member. Being entrusted with these key academic and administrative duties serves as a testament to his dedication, competence, and positive impact on the academic environment. Continued publication in high-quality journals and further conference participation are likely to lead to formal recognitions and research awards in the near future.

Research Skill🔬

Mr. Wasay possesses a well-rounded set of research skills, particularly in the areas of wireless sensor network optimization, algorithm development, simulation modeling, and academic writing. He has demonstrated proficiency in applying bio-inspired algorithms like the Harris Hawk Optimization (HHO) for sensor deployment and energy-efficient data transmission. His research work reflects a strong understanding of mathematical modeling, algorithm analysis, and system simulation for communication systems. He has successfully published in reputable journals and conferences, indicating his ability to conduct independent research, synthesize information, and present findings in a scholarly manner. Additionally, his skills extend to technical documentation, project supervision, and collaborative research, which are essential for academic growth and interdisciplinary engagement. His continued publication efforts and Ph.D. progress show his ability to integrate theory with application, conduct literature reviews, and identify impactful research problems. These capabilities make him a valuable contributor to both academic research and technological innovation.

Conclusion💡

Mr. H. Abdul Wasay is a dedicated academician and emerging researcher with a strong foundation in wireless sensor networks and bio-inspired optimization. His teaching experience, ongoing Ph.D., and multiple indexed publications qualify him as a strong candidate for the Best Researcher Award—especially at the institutional or early-career level.

However, for a top-tier or national-level research recognition, it is advisable to:

  • Publish more in high-impact SCI/SCIE journals.

  • Enhance research diversity and impact.

  • Seek grants, collaborations, and increase academic visibility through talks, workshops, and editorial contributions.

Publications Top Noted✍

  1. Title: Estimation of Coverage and Energy in Bio Inspired Wireless Sensors Using Harris Hawk Algorithm

    • Authors: H. Abdul Wasay, Kavi Priya

    • Year: 2023

    • Journal: Indonesian Journal of Electrical Engineering and Computer Science

    • DOI: 10.11591/ijeecs.v30.i3.pp1813-1820

    • ISSN: 2502-4752 / 2502-4760

    • Type: Journal Article

  1. Title: Effective Coverage Optimization Techniques in WSN Using the Harris Hawk Algorithm

    • Authors: H. Abdul Wasay, P. Kavi Priya

    • Year: 2022

    • Conference: 2022 International Conference on Recent Trends in Microelectronics, Automation, Computing and Communications Systems (ICMACC)

    • DOI: 10.1109/icmacc54824.2022.10093669

    • Type: Conference Paper

  1. Title: Optimization for Bio Inspired Wireless Sensors Using Hybridization

    • Authors: H. Abdul Wasay, Dr. P. Kavi Priya

    • Year: 2022

    • Journal: Computer Integrated Manufacturing Systems

    • DOI: 10.24297/j.cims.2022.12.32

    • Type: Journal Article

  1. Title: A Study of Energy Efficient Security Algorithm for Heterogeneous Clusters

    • Author: H. Abdul Wasay

    • Year: 2020

    • Journal: Test Engineering and Management

    • Publication Date: April 22, 2020

    • Type: Journal Issue or Edition

Lorenzo Longo | Interaction fluid-structure | Young Scientist Award

Posted on by Computer Vision Awards

Dr . Lorenzo Longo | Interaction fluid-structure | Young Scientist Award

Ingénieur chercheur at CEA, France

Dr. Lorenzo Longo is a research engineer with expertise in thermo-hydraulics and nuclear safety systems for advanced reactor designs. With a multidisciplinary academic background and hands-on experience in experimental and numerical modeling, he has significantly contributed to the understanding of fluid-structure interaction in nuclear fuel assemblies. Currently based at CEA Cadarache in France, he is actively involved in innovative nuclear system research, particularly focusing on small modular reactors and safety-critical thermo-fluid processes. Dr. Longo is recognized for his analytical acumen, adaptability across research domains, and proficiency in modern simulation and diagnostic techniques. His international exposure, including a research stint at George Washington University, highlights his global outlook and collaborative spirit. A fluent communicator in English, French, and Italian, he brings cultural and scientific versatility to any team. Dr. Longo’s profile exemplifies the qualities of a next-generation nuclear engineer committed to safety, sustainability, and technological innovation in energy systems.

Professional Profile 

Education🎓

Dr. Lorenzo Longo holds a PhD in Mechanical Engineering from Centrale Méditerranée in Marseille, France, where he specialized in experimental and numerical studies of fluid-structure interaction in reduced-scale Pressurized Water Reactor (PWR) fuel assemblies. Prior to that, he earned his MSc in Nuclear Engineering from Politecnico di Milano, Italy, with a thesis focused on the seismic behavior of half-scale PWR fuel assemblies, showcasing early expertise in reactor safety. His academic foundation began with a Bachelor’s degree in Engineering Physics, also from Politecnico di Milano, where he developed advanced skills in optics and laser spectroscopy. Throughout his academic journey, Dr. Longo consistently demonstrated a commitment to interdisciplinary learning and critical thinking, merging engineering principles with complex physical modeling. His educational path is distinguished by a steady progression toward highly specialized knowledge in nuclear energy systems, safety analysis, and dynamic fluid mechanics, laying a strong foundation for his research and professional accomplishments.

Professional Experience📝

Dr. Longo’s professional experience is rooted in his role as a research engineer at CEA Cadarache, one of Europe’s premier nuclear research facilities. Since July 2023, he has been engaged in developing thermo-hydraulic systems and safety mechanisms for next-generation reactors, contributing directly to innovation in nuclear energy. His past internships and research collaborations at CEA include seismic response studies of nuclear fuel assemblies and experimental fluid dynamics in reactor systems. Notably, he completed a visiting research stint at George Washington University, USA, where he deployed Time-Resolved Particle Image Velocimetry (PIV) in complex flow configurations. These roles illustrate his strengths in handling both experimental instrumentation and advanced computational techniques. Dr. Longo’s work bridges theoretical engineering principles with practical reactor safety applications, emphasizing real-world impact. His dynamic contributions to international research projects underline his commitment to scientific progress, nuclear safety, and energy sustainability in the context of emerging technological demands.

Research Interest🔎

Dr. Longo’s research interests lie at the intersection of nuclear safety, fluid-structure interaction, and advanced experimental diagnostics for thermo-hydraulic systems. He focuses on the behavior of Pressurized Water Reactor (PWR) fuel assemblies under seismic and dynamic loads, combining computational modeling with full-scale experimental validation. His current research explores safety-critical fluid mechanics and thermal behavior in Small Modular Reactors (SMRs), aiming to improve the reliability and resilience of future nuclear systems. He is particularly interested in non-intrusive measurement techniques like Laser Doppler Velocimetry (LDV) and Particle Image Velocimetry (PIV), which enhance the understanding of complex flow behavior in reactor geometries. Additionally, Dr. Longo investigates fluid-structure coupling phenomena to mitigate instabilities and ensure structural integrity under extreme operating conditions. His interdisciplinary approach integrates nuclear engineering, mechanical systems modeling, and advanced instrumentation, reflecting a strong commitment to optimizing safety and efficiency in clean, next-generation nuclear technologies.

Award and Honor🏆

While formal awards are not explicitly listed, Dr. Lorenzo Longo’s recognition is reflected through his prestigious academic and research appointments. Being selected as a Visiting Researcher at George Washington University is a notable honor, enabling him to collaborate on advanced fluid diagnostics using Time-Resolved PIV in nuclear configurations—an opportunity often extended to highly promising researchers. His continuous involvement with CEA Cadarache, a leading European nuclear research institute, across multiple roles including internships, doctoral research, and a full-time engineering position, speaks to his sustained excellence and trust in high-stakes projects. Furthermore, his inclusion in peer-reviewed publications on reactor safety and fluid instability, such as studies on Keulegan–Carpenter instability and drag estimation, highlights his growing academic reputation. Although he may not yet hold mainstream research awards, his professional trajectory and affiliations with elite research institutions serve as a testament to his merit, dedication, and scientific promise in the nuclear engineering field.

Research Skill🔬

Dr. Lorenzo Longo possesses a rich repertoire of research skills that span experimental design, computational modeling, and data analytics. He is proficient in Python, C++, LabVIEW, and LaTeX, which he employs for simulation, control systems, and documentation. His experience with Laser Doppler Velocimetry (LDV) and Particle Image Velocimetry (PIV) enables high-precision measurement of complex flow fields, particularly in nuclear reactor environments. Dr. Longo is adept at managing and calibrating experimental setups, interpreting sensor data, and executing non-intrusive diagnostics in controlled environments. His work with fluid-structure interaction models demonstrates competence in multiphysics simulations, essential for reactor safety evaluations. He also excels in communicating complex data visually and technically across interdisciplinary teams. With strong analytical thinking and hands-on lab expertise, Dr. Longo consistently bridges theoretical concepts with experimental verification. His research skill set is ideal for addressing multifaceted challenges in thermo-fluid systems and nuclear safety, making him an asset to high-impact engineering research.

Conclusion💡

Dr. Lorenzo Longo demonstrates outstanding technical depth, interdisciplinary fluency, and an international research trajectory in the domain of nuclear engineering and thermo-hydraulic safety systems. His focus on experimental and numerical modeling, combined with strong analytical capabilities, aligns well with the values of a Best Researcher Award.

Publications Top Noted✍

  • Title: Deployment of Time-Resolved Particle Image Velocimetry Between Two PWR Surrogate Bundles
    Authors: R. Capanna, L. Longo, F. Bazin, G. Ricciardi, P.M. Bardet
    Year: 2021
    Cited by: 3

  • Title: Drag Coefficient Estimation in FSI for PWR Fuel Assembly Bowing
    Authors: L. Longo, K. Cruz, N. Cadot, E. Sarrouy, G. Ricciardi, C. Eloy
    Year: 2022
    Cited by: 2

  • Title: Threshold of Keulegan–Carpenter Instability Within a 6×6 Rod Bundle
    Authors: L. Longo, R. Capanna, G. Ricciardi, P.M. Bardet
    Year: 2024

  • Title: Experimental Characterization of PWR Fuel Assemblies Mechanical Behavior Under Hydrodynamic and Seismic-Like Loads
    Author: L. Longo
    Year: 2023

  • Title: Deployment of Time-Resolved Particle Image Velocimetry Between Two PWR Surrogate Bundles
    Authors: P. Bardet, F. Bazin, R. Capanna, L. Longo, G. Ricciardi
    Year: 2019

  • Title: Experimental Study on the Behaviour of 4 Half-Scale PWR Fuel Assemblies Under Seismic Excitation
    Author: L. Longo
    Year: 2018

  • Title: Drag Coefficient Estimation in FSI for PWR Fuel Assembly Bowing
    Authors: L. Longo, K. Cruz, E. Sarrouy, G. Ricciardi, C. Eloy
    Cited by: Overlap with 2022 version (likely the same or extended work)