Madhuri Rao | Machine Learning | Best Researcher Award

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Dr. Madhuri Rao | Machine Learning | Best Researcher Award

Senior Assistant Professor | MIT World Peace University | India

Dr. Madhuri Rao is a dedicated researcher and academic in computer science with expertise in wireless sensor networks, Internet of Things, artificial intelligence, blockchain, and cybersecurity, with her current work focusing on deep learning, cloud security, and healthcare applications. She earned her Ph.D. in Computer Science and Engineering from Biju Patnaik University of Technology, where her research emphasized energy-efficient object tracking in wireless sensor networks. Over her career, she has gained extensive professional experience as a faculty member, academic coordinator, research supervisor, and editorial board member, contributing significantly to both teaching and research. She has authored and co-authored numerous publications in reputed journals and conferences, including IEEE, Springer, Elsevier, and Scopus-indexed platforms, along with patents and book chapters that highlight her innovative approach. Her research interests span interdisciplinary applications of advanced technologies to address challenges in security, healthcare, and sustainability, with ongoing involvement in collaborative projects and international initiatives. She has received recognition through awards such as best paper honors and a best research scholar award, underscoring her contributions to the academic community. Her research skills include problem-solving, experimental design, data analysis, and guiding students at undergraduate, postgraduate, and doctoral levels, coupled with active roles as session chair, track chair, and guest lecturer in international conferences. She is also a life member of professional societies and holds certifications that strengthen her academic profile. Her impactful contributions are reflected in 116 citations and an h-index of 7.

Profile: Google Scholar | ORCID | ResearchGate | LinkedIn

Featured Publications

  1. Rao, M., & Kamila, N. K. (2021). Cat swarm optimization based autonomous recovery from network partitioning in heterogeneous underwater wireless sensor network. International Journal of System Assurance Engineering and Management, 1–15.

  2. Rao, M., Kamila, N. K., & Kumar, K. V. (2016). Underwater wireless sensor network for tracking ships approaching harbor. 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), 1098–1102. IEEE.

  3. Rao, M., & Kamila, N. K. (2018). Spider monkey optimisation based energy efficient clustering in heterogeneous underwater wireless sensor networks. International Journal of Ad Hoc and Ubiquitous Computing, 29(1–2), 50–63.

  4. Chaudhury, P., Rao, M., & Kumar, K. V. (2009). Symbol based concatenation approach for text to speech system for Hindi using vowel classification technique. 2009 World Congress on Nature & Biologically Inspired Computing (NaBIC), 1393–1396. IEEE.

  5. Kumar, K. V., Kumari, P., Rao, M., & Mohapatra, D. P. (2022). Metaheuristic feature selection for software fault prediction. Journal of Information and Optimization Sciences, 43(5), 1013–1020.

Ahmet Kayabaşı| Artificial Intelligence | Best Researcher Award

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Prof. Dr. Ahmet Kayabaşı | Artificial Intelligence | Best Researcher Award

Professor | Karamanoglu Mehmetbey University | Turkey

Prof. Dr. Ahmet Kayabaşı is a distinguished academic in electrical-electronics engineering with expertise in artificial intelligence, antennas, biomedical signal processing, image processing, fuzzy logic, and power electronics. He earned his PhD in Electrical-Electronics Engineering from Selcuk University and has since built a strong academic career combining teaching, research, and leadership. His professional experience includes serving as Head of Department, Director of the Institute of Graduate Studies, and Senate Member, along with mentoring numerous MSc and PhD students. His research interests span interdisciplinary fields, applying advanced AI techniques in UAV swarm algorithms, smart agriculture, biomedical diagnostics, and energy-efficient power systems. He has been actively involved in TÜBİTAK and institutional projects, contributing to impactful solutions for both academia and industry. Recognized for his excellence, he has received awards such as Best Presenter Award at ICAT and has played vital roles in academic conferences and scientific communities. His research skills include developing intelligent systems, applying machine learning to engineering challenges, and designing novel antenna and biomedical applications. He has published widely in leading international journals indexed in IEEE, Scopus, and Web of Science, with notable contributions in Applied Thermal Engineering, Swarm and Evolutionary Computation, and Computers and Electronics in Agriculture. His academic excellence is reflected in 609 citations by 522 documents, 47 publications, and an h-index of 13.

Profile: Google Scholar | Scopus | ORCID

Featured Publications

  1. Sabanci, K., Kayabasi, A., & Toktas, A. (2017). Computer vision‐based method for classification of wheat grains using artificial neural network. Journal of the Science of Food and Agriculture, 97(8), 2588–2593.

  2. Yigit, E., Sabanci, K., Toktas, A., & Kayabasi, A. (2019). A study on visual features of leaves in plant identification using artificial intelligence techniques. Computers and Electronics in Agriculture, 156, 369–377.

  3. Kayabasi, A., Toktas, A., Yigit, E., & Sabanci, K. (2018). Triangular quad-port multi-polarized UWB MIMO antenna with enhanced isolation using neutralization ring. AEU-International Journal of Electronics and Communications, 85, 47–53.

  4. Sabanci, K., Toktas, A., & Kayabasi, A. (2017). Grain classifier with computer vision using adaptive neuro‐fuzzy inference system. Journal of the Science of Food and Agriculture, 97(12), 3994–4000.

  5. Yildiz, B., Aslan, M. F., Durdu, A., & Kayabasi, A. (2024). Consensus-based virtual leader tracking swarm algorithm with GDRRT*-PSO for path-planning of multiple-UAVs. Swarm and Evolutionary Computation, 88, 101612.

Fatma Zahra Sayadi | Deep Learning | Best Innovation Award

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Prof. Fatma Zahra Sayadi | Deep Learning | Best Innovation Award

Associate Professor | University of Sousse | Tunisia

Fatma Elzahra Sayadi is a highly accomplished researcher and academic specializing in electronics and microelectronics, with current research focused on video surveillance systems, real-time processing, and signal compression. She earned her PhD in electronics for real-time systems from the University of Bretagne Sud in collaboration with the University of Monastir and has also completed her engineering and master’s studies in electrical and electronic systems. She has extensive professional experience as a maître de conférences and previously as a maître assistante and assistant technologist, teaching courses in microprocessors, multiprocessors, programming, circuit testing, and industrial electronics. Her research interests include signal processing, parallel architectures, microelectronics, real-time systems, and communication networks. She has actively participated in national and international research projects and collaborations with institutions in France, Italy, Germany, and Morocco. Her work has been published in over 37 journal articles, 40 conference papers, and six book chapters, and she has supervised several doctoral and master’s theses. She has been recognized with awards such as the first prize at the Women in Research Forum at the University of Sharjah and contributes to professional communities as a reviewer, evaluator, and organizer of academic events. She is skilled in research methodologies, signal and data analysis, electronic system design, and digital education innovation. Her academic contributions have been cited by 395 documents, with 69 documents contributing to her citations, and she has an h-index of 13.

Profile: Google Scholar | Scopus | ORCID 

Featured Publications

  1. Basly, H., Ouarda, W., Sayadi, F. E., Ouni, B., & Alimi, A. M. (2020). CNN-SVM learning approach based human activity recognition. In International Conference on Image and Signal Processing (pp. 271–281). 77 citations.

  2. Bouaafia, S., Khemiri, R., Sayadi, F. E., & Atri, M. (2020). Fast CU partition-based machine learning approach for reducing HEVC complexity. Journal of Real-Time Image Processing, 17(1), 185–196. 53 citations.

  3. Haggui, O., Tadonki, C., Lacassagne, L., Sayadi, F., & Ouni, B. (2018). Harris corner detection on a NUMA manycore. Future Generation Computer Systems, 88, 442–452. 48 citations.

  4. Basly, H., Ouarda, W., Sayadi, F. E., Ouni, B., & Alimi, A. M. (2022). DTR-HAR: Deep temporal residual representation for human activity recognition. The Visual Computer, 38(3), 993–1013. 40 citations.

  5. Bouaafia, S., Khemiri, R., Messaoud, S., Ben Ahmed, O., & Sayadi, F. E. (2022). Deep learning-based video quality enhancement for the new versatile video coding. Neural Computing and Applications, 34(17), 14135–14149. 35 citations.

Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

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Prof. Igor Belenichev | Machine Learning | Excellence in Innovation

Professor at Zaporizhzhia State Medical University, Ukraine

Profiles

Scopus

Orcid

Google Scholar

📚 Summary

Prof. Igor Fedorovich Belenichev is a distinguished Full Professor and Head of the Department of Pharmacology and Medical Formulation at Zaporizhzhia State Medical University. Renowned for his innovative research in neuroprotection and pharmacology, he is a laureate of the Cabinet of Ministers of Ukraine Prize for the development and implementation of groundbreaking technologies.

Education

  • Zaporizhzhia State Medical Institute (1988): Graduated with a degree in medicine.
  • Postgraduate studies (1988), professor assistant (1991), senior teacher (1999), associate professor (2004), and full professor (2006).

💼 Professional Experience

  • Zaporizhzhia State Medical University: Head of the Department of Pharmacology and Medical Formulation since 2005.
  • Main Scientific Researcher at «Pharmatrone» (since 1993).
  • Head of the regional branch of the Association of Pharmacologists of Ukraine.
  • Co-worker of the regional group of the National Expert Centre of the Ministry of Health of Ukraine.

🔬 Research Interests

Prof. Belenichev’s research focuses on the molecular and biochemical mechanisms of ischemic brain damage and the development of effective neuroprotectors. His work explores the roles of reactive oxygen and nitrogen species, thiol-disulfide systems, pro-/anti-apoptotic proteins, estrogen receptors, and endogenous neuroprotection factors. He also investigates drugs for CNS pathologies and effective neuro- or cardioprotectors from derivatives of 1,2,4-triazole, chinazoline, and xanthine.

🏆 Achievements

  • Scientific Works: Authored and co-authored 715 scientific publications.
  • Patents: Holder of 182 patents in Ukraine and the Russian Federation.
  • Theses: Supervised 3 Dr. Habs and 7 Ph.D. theses.
  • Drug Development: Contributed to the creation of drugs like Thiotriazoline, Thiocetam, and Thiodarone.
  • Awards: Token of the Bibliographical Society of America (2003), Regional Program “Zoryaniy Shlyakh” Prize (2000), and Cabinet of Ministers of Ukraine Prize (2017).

 

Publications

5+1-Heterocyclization as preparative approach for carboxy-containing triazolo[1,5-c]quinazolines with anti-inflammatory activity

  • Authors: Krasovska, Natalya; Berest, Galina; Belenichev, Igor; Severina, Hanna; Nosulenko, Inna; Voskoboinik, Oleksii; Okovytyy, Sergiy; Kovalenko, Serhii
  • Journal: European Journal of Medicinal Chemistry
  • Year: 2024

Beta-Blockers of Different Generations: Features of Influence on the Disturbances of Myocardial Energy Metabolism in Doxorubicin-Induced Chronic Heart Failure in Rats

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Biomedicines
  • Year: 2024

Characteristics of HIF-1α and HSP70 mRNA Expression, Level, and Interleukins in Experimental Chronic Generalized Periodontitis

  • Authors: Parkhomenko Daria; Igor Belenichev; Kuchkovskyi Oleh; Ryzhenko Victor
  • Journal: MicroRNA
  • Year: 2024

Comparative Analysis of the Effect of Beta Blockers of Different Generations on the Parameters of Myocardial Energy Metabolism in Experimental Doxorubicin-Induced Chronic Heart Failure

  • Authors: Igor Belenichev; Olexiy Goncharov; Nina Bukhtiyarova; Oleh Kuchkovskyi; Victor Ryzhenko; Lyudmyla Makyeyeva; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Preprint
  • Year: 2024

Development and Optimization of Nasal Composition of a Neuroprotective Agent for Use in Neonatology after Prenatal Hypoxia

  • Authors: Igor Belenichev; Olena Aliyeva; Bogdan Burlaka; Kristina Burlaka; Oleh Kuchkovskyi; Dmytro Savchenko; Valentyn Oksenych; Oleksandr Kamyshnyi
  • Journal: Pharmaceuticals
  • Year: 2024

Dr. Na Yi | Deep Metric Learning | Best Researcher Award

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Dr. Na Yi | Deep Metric Learning | Best Researcher Award

Doctorate at Heilongjiang University of Science and Technology, China

Profiles

Scopus

Orcid

Academic Background

Dr. Na Yi, born in June 1997 in Acheng, Harbin, is an Associate Professor and a committed member of the Communist Party of China. With a strong academic foundation in Electrical Engineering and Automation, she has quickly risen as a prominent figure in the field of Petroleum and Natural Gas Engineering.

Education

Dr. Na Yi graduated with a degree in Electrical Engineering and Automation from Northeast Petroleum University in 2019. She was subsequently recommended for a doctoral program in Petroleum and Natural Gas Engineering, during which she also studied at Southeast University, earning her doctorate in 2024.

Professional Experience

Throughout her career, Dr. Na Yi has published over 20 research papers in esteemed journals, with 10 SCI-indexed and 5 EI-indexed papers, including highly cited and hot papers. She holds 6 national patents and has participated in 5 significant scientific research projects. Her achievements have earned her more than 10 national and provincial awards.

Research Interests

Dr. Na Yi’s research interests lie in Petroleum Engineering, with a focus on sustainable energy, power systems, and technological innovation. She is an active reviewer for multiple international and Chinese academic journals and has been invited to present her research at several international and domestic conferences.

 Publications

A multi-stage low-cost false data injection attack method for power CPS

  • Authors: Yi, N., Xu, J., Chen, Y., Pan, F.
  • Journal: Zhejiang Electric Power
  • Year: 2023
A New Distributed Power Supply for Distribution Network Considering SOP Access
  • Authors: Peng, C., Xu, J., Zhao, S., Yi, N.
  • Year: 2023
Multi-stage coordinated cyber-physical topology attack method based on deep reinforcement learning
  • Authors: Yi, N., Xu, J., Chen, Y., Sun, D.
  • Journal: Electric Power Engineering Technology
  • Year: 2023
A multi-stage game model for the false data injection attack from attacker’s perspective
  • Authors: Yi, N., Wang, Q., Yan, L., Tang, Y., Xu, J.
  • Journal: Sustainable Energy, Grids and Networks
  • Year: 2021
Insulator Self-Explosion Defect Detection Based on Hierarchical Multi-Task Deep Learning
  • Authors: Xu, J., Huang, L., Yan, L., Yi, N.
  • Journal: Diangong Jishu Xuebao/Transactions of China Electrotechnical Society
  • Year: 2021

Ms. Linjing Wei | Deep Learning | Best Researcher Award

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Ms. Linjing Wei | Deep Learning | Best Researcher Award

Linjing Wei at Gansu Agricultural University, China

Profile

Scopus

Academic Background:

Ms. Linjing Wei is a distinguished female professor at Gansu Agricultural University, specializing in Grassland Science with a research focus on Grassland Informatics. Born in July 1977, she has made significant contributions to her field through her extensive research, academic guidance, and numerous publications.

Education:

Ms. Wei earned her PhD in Grassland Science from Gansu Agricultural University in June 2015. Her educational background has provided a strong foundation for her academic and research pursuits.

Professional Experience:

Ms. Wei teaches several courses for master’s students, including Introduction to Cloud Computing, Case Analysis of Software Engineering, Information Systems and Information Resource Management, and Distributed Systems and Cloud Computing Technology. As the first supervisor, she has guided numerous master’s students in various majors, particularly in Agricultural Engineering and Information Technology.

Research Interests:

Ms.Wei's research interests lie in Grassland Informatics. Over the past five years, she has led several key research projects with significant funding, focusing on areas such as data resource integration, intelligent cloud platforms for agricultural logistics, ecosystem restoration and monitoring, sustainable development planning, and trustworthy traceability systems for agricultural products. Her published works include papers in prestigious journals like Sensors and the Canadian Journal of Remote Sensing, as well as contributions to national-level textbooks and academic monographs.

📝 Academic Achievements:

Ms. Wei has an impressive list of published papers, including "Fine Segmentation of Chinese Character Strokes Based on Co-ordinate Awareness and Enhanced BiFPN" in Sensors (2024), "Enhanced Wheat Head Detection in Images Using Fourier Domain Adaptation and Random Guided Filter" in Canadian Journal of Remote Sensing (2024), and "Feature Selection in High Dimensional Biomedical Data Based on BF-SFLA" in Neurogenetics (2022).

 Publications:

Fine Segmentation of Chinese Character Strokes Based on Coordinate Awareness and Enhanced BiFPN
  • Authors:Mo, H., Wei, L.
  • Journal: Sensors
  • Year: 2024
A Smart Chicken Farming Platform for Chicken Behavior Identification and Feed Residual Estimation
  • Authors: Yang, J., Gao, J., Li, Y., Lu, Q., Zheng, H.
  • Journal: Proceedings - 2023 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2023
  • Year: 2023
Feature Selection in High Dimensional Biomedical Data Based on BF-SFLA
  • Authors: Dai, Y., Niu, L., Wei, L., Tang, J.
  • Journal: Frontiers in Neuroscience
  • Year: 2022
Jointly Learning Topics in Sentence Embedding for Document Summarization
  • Authors: Gao, Y., Xu, Y., Huang, H., Wei, L., Liu, L.
  • Journal: IEEE Transactions on Knowledge and Data Engineering
  • Year: 2020
Study on the Matching Algorithm of Turf Grass Introduction Features Based on Big Data Analysis
  • Authors: Wei, L., Dong, W., Gan, S., Wang, Y.
  • Year: 2019

Mr. Siphumelele Zondi | Artificial Intelligence | Best Researcher Award

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Mr. Siphumelele Zondi, Artificial Intelligence, Best Researcher Award

Siphumelele Zondi at Durban University of Technology, South Africa

Professional Profile

🌟 Summary:

Mr. Bhekani Siphumelele Zondi is a charismatic media practitioner, journalist, academic, content lead, and media researcher. With extensive experience in technology, social media, television, online, and radio programming, Zondi has significantly impacted South Africa’s media landscape.

🎓 Education:

  • Master of Arts in Media and Cultural Studies
    • University of Sussex, England (2012 – 2013)
    • Research: Social Media as the New Public Sphere
  • Bachelor of Technology in Journalism
    • Tshwane University of Technology, South Africa (Received Dec 2005)
    • Major: Broadcast Journalism

💼 Professional Experience:

  • Durban University of Technology (DUT)
    • Journalism Lecturer (2019 – Present)
    • Creator & Content Lead, Credible Source by DUT Journalism (2023 – Present)
  • South African Broadcasting Corporation (SABC)
    • Creator, Senior Producer & Presenter: Network (2013 – March 2024)
    • Presenter: Africa Digest (April 2013 – February 2019)
  • CNBC Africa
    • Senior Producer & Presenter (April 2013 – July 2013)
  • Tshwane University of Technology (TUT)
    • Journalism Lecturer (August 2009 – September 2011)
  • e-TV
    • Television News Reporter (April 2005 – September 2006)

🔬 Research Interests:

  • Social Media Engagement
  • Interactions between Politicians, Journalists, and Audiences
  • Use of Artificial Intelligence in Journalism

🏆 Awards & Recognitions:

  • 2017: Mail & Guardian Top 200 Young South Africans
  • 2011: Chevening Scholarship from the British Council
  • 2010: Blog of the Year Award Nomination – Journ’Tau
  • 2008: SABC News Awards Nomination – Best Current Affairs Presenter

🌐 Fellowships:

  • 2010/11: Finland EVA Junior Fellow
  • 2007: Member of Finland Foreign Correspondents’ Programme

📖 Publications Top Noted:

Paper Title: The Role of Artificial Intelligence in Contemporary Journalism Practice in Two African Countries
  • Authors: Siphumelele Zondi, Theodora Adjin-Tettey, Tigere Muringa, Samuel Danso
  • Journal: Media and Journalism
  • Year: 2024

Mr. Xiaoyu Li | Deep Learning | Best Researcher Award

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Mr. Xiaoyu Li, Deep Learning, Best Researcher Award

Xiaoyu Li at Beijing Forestry University, China

Professional Profile

🌟 Summary:

Xiaoyu Li is a university student at Beijing Forestry University’s School of Soil and Water Conservation. His research focuses on Remote Sensing & GIS, Image Processing, Land Use, Transportation, UAV utilization, and Ecology. He has contributed to national-level scientific projects, including the Qinghai-Tibet Plateau expedition, and has authored publications in prestigious journals. His work includes assessing human living environments, controlling soil erosion, and studying sediment connectivity and erosion dynamics. Xiaoyu Li has pioneered large-scale land use classification in northwestern China using UAV remote sensing and has contributed to understanding vegetation changes in the Qinghai-Tibet Plateau.

🎓 Education:

Currently pursuing studies at Beijing Forestry University, College of Soil and Water Conservation.

💼 Professional Experience:

Engaged in multiple national-level research projects focusing on environmental assessment, soil erosion control, and watershed dynamics.

🔬 Research Interests:

  • Remote Sensing & GIS
  • Image Processing and Analysis
  • Land Use and Transportation
  • UAV (drone) utilization and Ecology

📖 Publications Top Noted:

Paper Title: Land-Use Composition, Distribution Patterns, and Influencing Factors of Villages in the Hehuang Valley, Qinghai, China, Based on UAV Photogrammetry
  • Authors: Xiaoyu Li, Zhongbao Xin
  • Journal: Remote Sensing
  • Year: 2024