Michael Koch | Robotics | Best Researcher Award

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Prof . Dr . Michael Koch | Robotics | Best Researcher Award

Professor at Technische Hochschule Nürnberg, Germany

Prof. Dr.-Ing. Dipl.-Wirt.-Ing. Michael Koch is a distinguished German academic and research professor in mechanical engineering with a robust focus on engineering design, simulation technologies, and additive manufacturing. Currently serving as Vice Dean and Professor at Technische Hochschule Nürnberg Georg Simon Ohm, he has over 20 years of experience in academia and industry. His research integrates innovative technologies like augmented reality, motion capture, and cyber-physical systems to optimize design processes and intelligent manufacturing systems. He has published extensively in high-impact conferences and journals, and he actively leads curriculum and academic initiatives in engineering education. As a certified Six Sigma Black Belt and a key user of PTC CREO Parametric, Prof. Koch demonstrates a blend of theoretical depth and industrial pragmatism. His contributions toward intuitive robot programming, knowledge-based simulation, and 3D geometry integration in product development make him a prominent figure in Germany’s mechanical engineering research landscape.

Professional Profile 

Education🎓F

Prof. Michael Koch has a strong academic foundation combining mechanical engineering and industrial engineering. He earned his Dr.-Ing. (Ph.D.) in Engineering Design from Friedrich-Alexander University Erlangen-Nuremberg in 2005 with the distinction of “very good.” His doctoral work laid the groundwork for his later research in design optimization and simulation integration. He previously completed a Diploma in Mechanical Engineering (Dipl.-Ing.) from the same university in 2000, specializing in design and computation with an excellent academic grade (1.8). Complementing his technical background, he pursued a Diploma in Industrial Engineering (Dipl.-Wirt.-Ing.) at the University of Hagen (2001–2004), focusing on marketing and human resources, which reflects his interdisciplinary strengths. This combination of design engineering and business-oriented knowledge has enabled him to lead academic programs and collaborate effectively with the manufacturing industry. His diverse academic trajectory supports his holistic approach to innovation in both engineering education and applied research.

Professional Experience📝

Prof. Koch’s professional journey spans both academic excellence and industry leadership. He has been a Professor at Technische Hochschule Nürnberg Georg Simon Ohm since 2009, where he teaches engineering design and machine parts and serves as the Vice Dean and Head of the Master’s Program in Mechanical Engineering. He has played a pivotal role in curriculum design and quality assurance within the faculty. Before transitioning fully into academia, he worked at Schaeffler Technologies GmbH & Co. KG (2005–2009) in the special machines department, where he managed key industrial projects. Earlier in his career, he served as a scientific assistant at Friedrich-Alexander University Erlangen-Nuremberg, contributing to engineering research and instruction. Prof. Koch also holds certifications like Six Sigma Black Belt and Key User of PTC CREO Parametric, underscoring his practical orientation. His combined industry-academic experience uniquely positions him as a leader in engineering innovation and applied research.

Research Interest🔎

Prof. Koch’s research interests lie at the intersection of engineering design, additive manufacturing, simulation technologies, and robotics. His work frequently explores knowledge-based design methods, real-geometry integration in simulations, and intuitive user interfaces for robotic applications. He is particularly interested in optimizing design and manufacturing processes through augmented reality, motion capture, and cyber-physical systems. His studies also delve into reverse engineering, finite element (FE) simulations using real 3D-scanned data, and product development driven by simulation and automation. Prof. Koch aims to bridge the gap between idealized models and real-world manufacturing variances, improving accuracy and efficiency in digital engineering. His interdisciplinary approach integrates mechanical engineering, human-computer interaction, and data-driven decision-making, resulting in innovations that benefit both academia and industry. His research significantly contributes to smart manufacturing, lightweight design, and automation in production, making him a key figure in the advancement of intelligent engineering systems.

Award and Honor🏆

While Prof. Michael Koch’s CV does not list formal awards or honors explicitly, his distinguished academic positions and repeated invitations to present at international conferences reflect peer recognition of his expertise. His appointment as Vice Dean and Research Professor at Technische Hochschule Nürnberg, along with his leadership in curriculum development and examination boards, underscores the institutional trust placed in him. He has been a consistent contributor to high-impact events such as IFAC Workshops, ISR, Sim-AM, ICED, and the Design for X Symposium, where his papers have been accepted for both presentation and publication—an honor in the global research community. His certification as a Six Sigma Black Belt and designation as a Key User of industry-standard CAD tools (PTC CREO) also highlight his professional credibility. These roles and participations collectively showcase a career marked by excellence, leadership, and sustained contributions to both research and education in mechanical engineering.

Research Skill🔬

Prof. Koch demonstrates a comprehensive set of research skills across simulation, design, modeling, and experimental validation. He excels in integrating real 3D geometry data into simulations, thereby enhancing the accuracy of engineering analyses. His ability to combine parametric CAD modeling with finite element methods (FEM) enables more realistic structural assessments. He is skilled in developing cyber-physical systems, utilizing augmented reality for robot programming, and implementing motion capture technologies for intuitive control interfaces. Prof. Koch also possesses strong capabilities in knowledge-based simulation frameworks, making product development processes more efficient and intelligent. His certification in Six Sigma demonstrates his proficiency in process optimization and quality control, and his work often bridges the gap between academic theories and industrial applications. Proficient in engineering software like PTC CREO Parametric, he brings both depth and versatility to his projects. These research skills collectively establish his expertise in designing cutting-edge, applied engineering solutions.

Conclusion💡

Prof. Dr.-Ing. Michael Koch is highly suitable for the Best Researcher Award based on his:

  • Depth of domain knowledge,

  • Multidisciplinary research footprint,

  • Educational leadership,

  • Technical innovations in engineering design, simulation, and additive manufacturing.

His work bridges academic rigor and industry relevance, and he has made consistent, innovative contributions to mechanical engineering and product development.

With additional international collaboration and visibility in global rankings or research grants, he would further elevate his candidacy for top-tier global research honors.

Publications Top Noted✍

  1. Title: Expression and functions of transmembrane mucin MUC13 in ovarian cancer
    Authors: SC Chauhan, K Vannatta, MC Ebeling, N Vinayek, A Watanabe, MD Koch, et al.
    Year: 2009
    Citations: 149

  2. Title: MUC13 mucin augments pancreatic tumorigenesis
    Authors: SC Chauhan, MC Ebeling, DM Maher, MD Koch, A Watanabe, et al.
    Year: 2012
    Citations: 110

  3. Title: Identification of an essential Caulobacter crescentus gene encoding a member of the Obg family of GTP-binding proteins
    Authors: J Maddock, A Bhatt, M Koch, J Skidmore
    Year: 1997
    Citations: 71

  4. Title: Increased expression and aberrant localization of mucin 13 in metastatic colon cancer
    Authors: BK Gupta, DM Maher, MC Ebeling, V Sundram, MD Koch, DW Lynch, et al.
    Year: 2012
    Citations: 54

  5. Title: Combined staining of TAG-72, MUC1, and CA125 improves labeling sensitivity in ovarian cancer
    Authors: SC Chauhan, N Vinayek, DM Maher, MC Bell, KA Dunham, MD Koch, et al.
    Year: 2007
    Citations: 42

  6. Title: Design for X
    Authors: H Meerkamm, M Koch
    Year: 2005
    Citations: 33

  7. Title: Intuitive welding robot programming via motion capture and augmented reality
    Authors: F Mueller, C Deuerlein, M Koch
    Year: 2019
    Citations: 23

  8. Title: Innovative extruder concept for fast and efficient additive manufacturing
    Authors: R Löffler, M Koch
    Year: 2019
    Citations: 20

  9. Title: Integrating optical 3D measurement techniques in pipe bending: a model-based approach
    Authors: S Katona, M Lušić, M Koch, S Wartzack
    Year: 2016
    Citations: 19

  10. Title: The neuro-linguistic programming treatment approach
    Authors: C Zastrow, V Dotson, M Koch
    Year: 1987
    Citations: 16

  11. Title: Cyber-physical-system for representing a robot end effector
    Authors: F Müller, C Deuerlein, M Koch
    Year: 2021
    Citations: 15

  12. Title: Trace component removal in CO2 removal processes by means of a semipermeable membrane
    Authors: JK Bockman, M Koch
    Year: 2016 (US Patent)
    Citations: 15

  13. Title: Robot guided computed tomography—production monitoring in automotive industry 4.0
    Authors: A Ziertmann, P Jahnke, S Kerscher, M Koch, W Holub
    Year: 2020
    Citations: 12

  14. Title: Microstructure of the HMX‐Based PBX KS32 after Mechanical Loading
    Authors: M Herrmann, U Förter‐Barth, MA Bohn, H Krause, M Koch, W Arnold
    Year: 2015
    Citations: 12

  15. Title: PM10 source apportionment at three urban background sites in the western Ruhr-area, Germany
    Authors: TAJ Kuhlbusch, U Quass, M Koch, H Fissan, P Bruckmann, U Pfeffer
    Year: 2004
    Citations: 12

  16. Title: Method and system for reducing energy requirements of a CO2 capture system
    Authors: JP Naumovitz, M Koch
    Year: 2014 (US Patent)
    Citations: 10

  17. Title: Process gas treatment system
    Authors: PU Koss, M Koch, JP Naumovitz
    Year: 2014 (US Patent)
    Citations: 10

  18. Title: Reverse Engineering – Prozess, Technologien und Anwendungsfälle
    Authors: S Katona, M Koch, S Wartzack
    Year: 2014
    Citations: 9

  19. Title: POEAM – a method for the part orientation evaluation for additive manufacturing
    Authors: S Jung, S Peetz, M Koch
    Year: 2019
    Citations: 7

  20. Title: Long-term primary culture of a clear cell ovarian carcinoma reveals an epithelial–mesenchymal cooperative interaction
    Authors: AA Goyeneche, M Koch, MC Bell, CM Telleria
    Year: 2015
    Citations: 7

Dibyalekha Nayak | Computer vision | Women Researcher Award

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Dr . Dibyalekha Nayak | Computer vision | Women Researcher Award

Assistant professor at Shah and Anchor Kutchhi Engineering College, India

Dr. Dibyalekha Nayak is a dedicated academician and emerging researcher with deep expertise in image processing, adaptive compression, and VLSI design. Her professional journey is marked by a strong commitment to teaching, scholarly research, and technological advancement. With over a decade of teaching experience and a recently completed Ph.D. from KIIT University, Bhubaneswar, her research has produced several publications in SCI-indexed journals and international conferences. Dr. Nayak’s contributions reflect an interdisciplinary approach, combining deep learning techniques with low-power hardware design to address complex challenges in wireless sensor networks and multimedia systems. She has actively participated in faculty development programs and technical workshops, continuously upgrading her knowledge. Her professional philosophy emphasizes ethics, hard work, and continuous learning. Currently serving as an Assistant Professor at Shah and Anchor Kutchi Engineering College in Mumbai, she aspires to make impactful contributions to the field of electronics and communication through research, innovation, and collaboration.

Professional Profile 

Education🎓

Dr. Dibyalekha Nayak holds a Ph.D. in Image Processing from the School of Electronics at KIIT University, Bhubaneswar, where she completed her research between September 2018 and May 2024. Her doctoral work focused on advanced techniques in image compression and saliency detection using deep learning and compressive sensing. She completed her Master of Technology (M.Tech) in VLSI Design from Satyabhama University, Chennai, in 2011, graduating with a commendable CGPA of 8.33. Prior to that, she earned her Bachelor of Engineering (B.E.) in Electronics and Telecommunication from Biju Patnaik University of Technology (BPUT), Odisha, in 2008, with a CGPA of 6.5. Her academic background provides a strong foundation in both theoretical electronics and practical applications in image processing and circuit design. The combination of image processing and VLSI design throughout her academic journey has enabled her to engage in cross-disciplinary research and foster innovation in both hardware and software domains.

Professional Experience📝

Dr. Dibyalekha Nayak has accumulated over 12 years of rich academic experience in various reputed engineering institutions across India. Currently, she serves as an Assistant Professor at Shah and Anchor Kutchi Engineering College, Mumbai, affiliated with Mumbai University, where she joined in July 2024. Prior to this, she worked as a Research Scholar at KIIT University (2018–2024), contributing significantly to image processing research. Her earlier roles include Assistant Professor positions at institutions such as College of Engineering Bhubaneswar (2016–2018), SIES Graduate School of Technology, Mumbai (2014), St. Francis Institute of Technology, Mumbai (2013), and Madha Engineering College, Chennai (2011–2012). Across these roles, she has taught a variety of undergraduate and postgraduate courses, supervised student projects, and contributed to departmental development. Her teaching areas span digital electronics, VLSI design, image processing, and communication systems, demonstrating a strong alignment between her teaching and research activities.

Research Interest🔎

Dr. Dibyalekha Nayak’s research interests lie at the intersection of image processing, deep learning, and VLSI design, with a special focus on adaptive compression, saliency detection, and compressive sensing. Her doctoral research addressed the development of innovative, low-complexity algorithms for image compression using techniques like block truncation coding and DCT, tailored for wireless sensor network applications. She is also deeply interested in integrating deep learning frameworks into image enhancement and compression tasks to improve performance in real-world environments. Additionally, her background in VLSI design supports her interest in low-power hardware architectures for efficient implementation of image processing algorithms. Dr. Nayak is particularly motivated by research problems that bridge the gap between theoretical innovation and practical implementation, especially in the fields of embedded systems and multimedia communication. Her interdisciplinary research aims to create scalable, energy-efficient, and intelligent solutions for future communication and sensing technologies.

Award and Honor🏆

While Dr. Dibyalekha Nayak’s profile does not explicitly mention formal awards or honors, her scholarly achievements speak volumes about her academic excellence and dedication. She has published multiple research articles in prestigious SCI and Web of Science indexed journals such as Multimedia Tools and Applications, Mathematics, and Computers, reflecting the quality and impact of her research. She has been actively involved in reputed international conferences including IEEE and Springer Lecture Notes, where she has presented and published her research findings. Her work on saliency-based image compression and fuzzy rule-based adaptive block compressive sensing has received commendation for its innovation and applicability. Furthermore, her selection and sustained work as a Research Scholar at KIIT University for over five years highlights the recognition she has earned within academic circles. Her consistent participation in technical workshops, faculty development programs, and collaborations also demonstrate her growing reputation and standing in the field of electronics and image processing.

Research Skill🔬

Dr. Dibyalekha Nayak possesses a versatile and robust set of research skills aligned with modern-day challenges in image processing and electronics. She is proficient in developing image compression algorithms, saliency detection models, and adaptive techniques using block truncation coding, fuzzy logic, and DCT-based quantization. Her technical expertise extends to deep learning architectures tailored for image enhancement and compressive sensing in wireless sensor networks. Additionally, she has a strong command of VLSI design methodologies, enabling her to work on low-power circuit design and hardware implementation strategies. Dr. Nayak is also skilled in scientific programming, using tools such as MATLAB and Python, along with LaTeX for research documentation. She has a clear understanding of research methodologies, simulation frameworks, and performance analysis metrics. Her experience in preparing manuscripts for SCI-indexed journals and conference presentations showcases her technical writing abilities. Overall, her analytical mindset and hands-on skills make her a competent and impactful researcher.

Conclusion💡

Dr. Dibyalekha Nayak is a highly dedicated and emerging researcher in the fields of Image Processing, Deep Learning, and VLSI. Her academic journey reflects perseverance, scholarly depth, and a clear focus on impactful research. Her SCI-indexed publications, teaching experience, and cross-domain knowledge make her a deserving candidate for the Best Researcher Award.

Publications Top Noted✍

  • Title: Fuzzy Rule Based Adaptive Block Compressive Sensing for WSN Application
    Authors: D. Nayak, K. Ray, T. Kar, S.N. Mohanty
    Journal: Mathematics, Volume 11, Issue 7, Article 1660
    Year: 2023
    Citations: 6

  • Title: A novel saliency based image compression algorithm using low complexity block truncation coding
    Authors: D. Nayak, K.B. Ray, T. Kar, C. Kwan
    Journal: Multimedia Tools and Applications, Volume 82, Issue 30, Pages 47367–47385
    Year: 2023
    Citations: 4

  • Title: Walsh–Hadamard Kernel Feature-Based Image Compression Using DCT with Bi-Level Quantization
    Authors: D. Nayak, K. Ray, T. Kar, C. Kwan
    Journal: Computers, Volume 11, Issue 7, Article 110
    Year: 2022
    Citations: 3

  • Title: Sparsity based Adaptive BCS color image compression for IoT and WSN Application
    Authors: D. Nayak, T. Kar, K. Ray
    Journal: Signal, Image and Video Processing, Volume 19, Issue 8, Pages 1–7
    Year: 2025

  • Title: Hybrid Image Compression Using DCT and Autoencoder
    Authors: D. Nayak, T. Kar, K. Ray, J.V.R. Ravindra, S.N. Mohanty
    Conference: 2024 IEEE Pune Section International Conference (PuneCon), Pages 1–6
    Year: 2024

  • Title: Performance Comparison of Different CS based Reconstruction Methods for WSN Application
    Authors: D. Nayak, K.B. Ray, T. Kar
    Conference: 2021 IEEE 2nd International Conference on Applied Electromagnetics, Signal Processing, & Communication (AESPC)
    Year: 2021

  • Title: A Comparative Analysis of BTC Variants
    Authors: D. Nayak, K.B. Ray, T. Kar
    Conference: Proceedings of International Conference on Communication, Circuits, and Systems (LNEE, Springer)
    Year: 2021

  • Title: Low Power Error Detector Design by using Low Power Flip Flops Logic
    Authors: D. Chaini, P. Malgi, S. Lopes
    Journal: International Journal of Computer Applications, ISSN 0975-8887
    Year: 2014

Ali Emamverdian | Forming | Best Researcher Award

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Dr . Ali Emamverdian | Forming | Best Researcher Award

Lecturer and researcher at HAUQIAO UNIVERSITY, China

Dr. Aliakbar Emamverdian is a dedicated mechanical engineering scholar with a strong academic and research background in manufacturing and automation. Born in February 1984, he currently serves as a lecturer and researcher at Huaqiao University, China. His career spans international institutions including Nanjing University of Science and Technology and Eastern Mediterranean University. Dr. Emamverdian’s expertise includes metal forming, material characterization, failure analysis, and life prediction, with a particular focus on integrating advanced tools like optical scanning and neural network modeling into traditional manufacturing processes. He has co-authored several peer-reviewed journal articles and a technical book on competency design in manufacturing systems. Dr. Emamverdian is multilingual, proficient in Farsi, English, and Turkish, and actively collaborates with leading researchers from institutions such as Imperial College London and Politecnico di Bari. His commitment to scientific innovation, academic teaching, and international collaboration defines his contributions to mechanical engineering.

Professional Profile 

Education🎓

Dr. Emamverdian began his academic journey with a Bachelor of Science degree in Mechanical Engineering from Islamic Azad University in 2007. Motivated by a passion for innovation and precision engineering, he pursued a Master of Science in Mechanical Engineering with a specialization in Manufacturing at Eastern Mediterranean University, completing it in February 2013. His academic trajectory culminated with a Ph.D. in Mechanical Engineering, Manufacturing, and Automation from the prestigious Nanjing University of Science and Technology in China, awarded in February 2023. His doctoral research emphasized simulation-based analysis, microstructural evolution, and neural network modeling for predicting material degradation in metal forming processes. Through this diverse educational background, Dr. Emamverdian developed a robust foundation in advanced manufacturing techniques, computational modeling, and experimental validation. His academic achievements reflect a blend of theoretical knowledge and practical problem-solving skills that empower his teaching and research in cutting-edge engineering disciplines.

Professional Experience📝

Dr. Aliakbar Emamverdian has amassed a wealth of international academic experience over the past decade. Currently, he is a lecturer and researcher at Huaqiao University (HQU), China, where he has been contributing to the Mechanical Engineering Department since September 2023. Prior to this, he served as a research assistant at Nanjing University of Science and Technology (NJUST), China, from September 2016 to June 2019, where he was actively engaged in simulation-based material research and experimental validation. From January 2013 to June 2016, Dr. Emamverdian worked as an assistant in the laboratory at Eastern Mediterranean University (EMU), Cyprus, where he supported academic courses and participated in experimental mechanics. His professional background spans teaching, laboratory assistance, and advanced research roles, reflecting a consistent commitment to academic excellence and international collaboration. His roles have allowed him to work on multi-disciplinary projects involving simulation, manufacturing technologies, and intelligent systems.

Research Interest🔎

Dr. Emamverdian’s research interests lie at the intersection of mechanical engineering and advanced manufacturing technologies. He specializes in metal forming, failure analysis, non-destructive testing, and life prediction of mechanical components. A key aspect of his research involves studying material behavior under thermal and mechanical stress during hot forging, particularly focusing on H21 steel dies. His recent work explores the use of optical scanning, finite element simulation, and microstructural analysis to predict degradation mechanisms in forging dies. Furthermore, he integrates neural network modeling and intelligent algorithms to enhance the predictive capabilities of mechanical systems. Dr. Emamverdian is also interested in the material characteristics of alloys and their responses to complex loading conditions. His interdisciplinary research contributes significantly to improving the durability and performance of manufacturing tools and supports the advancement of smart manufacturing systems. His approach combines theoretical analysis, experimental work, and computational intelligence.

Award and Honor🏆

While Dr. Emamverdian’s profile does not list specific personal awards or honors to date, his growing recognition is evident through his collaborations with high-ranking institutions and publication in reputable international journals. His research has appeared in Journal of Materials Research and Technology, Engineering Failure Analysis, and Journal of Visualization, highlighting the academic community’s trust in his work. He has worked alongside distinguished researchers from Imperial College London, University of Strathclyde, and Politecnico di Bari—an indication of his emerging prominence in the global mechanical engineering research community. His book publication on manufacturing system modeling, authored early in his career, showcases his long-standing commitment to research excellence. Continued international academic appointments further signify the respect and demand for his expertise. With ongoing high-quality research and impactful collaborations, Dr. Emamverdian is poised to receive formal accolades and awards recognizing his innovative contributions to mechanical engineering and manufacturing science.

Research Skill🔬

Dr. Emamverdian possesses an extensive portfolio of research and technical skills essential for modern mechanical engineering. He is proficient in advanced simulation tools like ABAQUS, DEFORM, and SIMUFACT FORMING, which he uses for stress analysis and die wear prediction. His modeling expertise includes CATIA V5 and SOLIDWORKS for mechanical design. For data analysis and intelligent systems, he employs MATLAB, particularly neural networks and fuzzy logic algorithms. Additionally, his hands-on experience with EBSD (Channel 5) and SEM techniques enhances his material characterization work. Dr. Emamverdian is also skilled in optical scanning and surface mapping using POLYWORKS, which supports his work in non-destructive evaluation and life prediction of industrial tools. His ability to combine computational, experimental, and analytical methods allows him to solve complex problems in metal forming and manufacturing. These research capabilities underpin his innovative approaches to failure analysis and smart manufacturing technologies.

Conclusion💡

Dr. Aliakbar Emamverdian demonstrates strong qualifications and innovative contributions in mechanical engineering and advanced manufacturing. His research spans experimental and simulation-based approaches, enriched by AI-driven analysis, and he collaborates with prestigious institutions globally. His work on failure analysis, die degradation, and metal forming simulation is both industrially relevant and academically rigorous.

While his profile could benefit from additional publication metrics, research funding leadership, and broader recognition, his technical depth, publication quality, and international collaborations make him a compelling candidate for the Best Researcher Award, particularly in the engineering and manufacturing domain.

Publications Top Noted✍

  • Title: Current failure mechanisms and treatment methods of hot forging tools (dies) – A review
    Authors: AA Emamverdian, Y Sun, C Cao, C Pruncu, Y Wang
    Year: 2021
    Citations: 72

  • Title: Deformation and wear in a H21 (3Cr2W8V) steel die during hot forging: Simulation, mechanical properties, and microstructural evolution
    Authors: AA Emamverdian, Y Sun, C Chunping
    Year: 2021
    Citations: 22

  • Title: The interaction of vortices induced by a pair of microjets in the turbulent boundary layer
    Authors: MJ Pour Razzaghi, C Xu, A Emamverdian
    Year: 2021
    Citations: 7

  • Title: Prediction of the main degradation mechanisms in a hot forging steel die: Optical scanning, simulation, microstructural evolution, and neural network modeling
    Authors: A Emamverdian, C Pruncu, H Liu, A Rahimzadeh, L Lamberti
    Year: 2025

  • Title: Corrigendum to “Deformation and wear in a H21 (3Cr2W8V) steel die during hot forging: Simulation, mechanical properties, and microstructural evolution”
    Authors: AA Emamverdian, Y Sun, C Chunping
    Year: 2022

  • Title: Design of a competency-based information and knowledge model for a manufacturing system: Case study EMU CIM Lab
    Author: AA Emamverdian
    Year: 2013

Shashank Singh Pawar | Marketing | Best Researcher Award

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Mr . Shashank Singh Pawar | Marketing | Best Researcher Award

Research Scholar at Goa Institute of Management, Goa, India

Shashank Singh Pawar is a dedicated FPM Scholar in Marketing at the Goa Institute of Management (GIM), India. With a strong foundation in engineering and management, he brings a multidisciplinary approach to his research, focusing on Human-Computer Interaction, Anthropomorphism, and Consumer Behavior. Shashank’s academic journey reflects his passion for exploring how digital interfaces and avatars influence consumer psychology and behavior across generations. His research has earned recognition through peer-reviewed publications and conference awards. Prior to joining GIM, he served as an Assistant Professor for over eight years, contributing actively to academia through teaching, mentoring, and organizing conferences. His editorial roles and participation in research workshops underscore his commitment to scholarly excellence. Driven by curiosity, innovation, and a deep understanding of digital consumer dynamics, Shashank is steadily building a reputation as a thoughtful and emerging researcher in his field.

Professional Profile 

Education🎓

Shashank Singh Pawar’s educational background reflects a strong interdisciplinary trajectory. He is currently pursuing a Ph.D. (Fellow Programme in Management) in Marketing at the Goa Institute of Management (2021–present), where his research centers on digital consumer behavior and avatar interactions. Prior to his doctoral studies, he completed his Master of Engineering in Industrial Engineering and Management from the Institute of Engineering & Technology (IET-DAVV), Devi Ahilya Vishwavidyalaya, Indore, in 2013. He laid the foundation for his academic and analytical skills with a Bachelor of Engineering in Mechanical Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal, in 2011. Throughout his academic journey, he demonstrated a consistent interest in integrating engineering principles with management and behavioral sciences, eventually transitioning into a research-driven career in marketing. His educational progression illustrates a deepening focus on the psychological and technological dimensions of consumer engagement.

Professional Experience📝

Before embarking on his doctoral journey, Shashank Singh Pawar gained substantial teaching experience as an Assistant Professor at the Chameli Devi Group of Institutions, Indore, from 2013 to 2021. During his eight-year tenure, he was involved in teaching core engineering and management subjects, advising student projects, and participating in academic event coordination. His excellence in mentoring was recognized with the Dronacharya Award for his role in guiding student teams in national competitions such as the Auto India Racing Championship (AIRC). His responsibilities extended beyond the classroom, where he actively contributed to organizing national-level conferences, thereby fostering a collaborative academic environment. This professional phase not only honed his instructional capabilities but also strengthened his academic leadership and research interests, ultimately paving the way for his transition to full-time research in marketing. His industry-relevant teaching experience complements his current research in digital marketing and consumer behavior.

Research Interest🔎

Shashank Singh Pawar’s research interests lie at the intersection of marketing, psychology, and technology. He is particularly drawn to Human-Computer Interaction (HCI), Anthropomorphism in AI systems, and Consumer Behavior in the context of immersive and digital interfaces. His ongoing doctoral work explores how different generations interact with AI-driven avatars and how realism and emotional cues affect consumer responses. He aims to understand and model consumer attitudes and behaviors in technology-mediated environments, such as virtual shopping and digital gifting contexts. His recent publication in Computers in Human Behavior and his working papers reflect this passion for examining user engagement with avatars, prosocial outcomes in digital gifting, and generational psychology. By applying experimental and qualitative methods, Shashank seeks to bridge the gap between theoretical insights and practical applications in digital marketing. His research contributes to the evolving understanding of AI-consumer relationships, influencing both academia and the future of customer experience design.

Award and Honor🏆

Shashank Singh Pawar has been recognized for his academic and mentoring excellence throughout his career. Most notably, he received the Best Paper Award (Runner-up) at the 9th Indian Academy of Management (INDAM) Conference 2024, a prestigious recognition reflecting the quality and relevance of his research on avatar-based consumer interactions. Earlier in his career, he was honored with the Dronacharya Award for his outstanding contribution as a faculty advisor during the Auto India Racing Championship (AIRC-2017), highlighting his dedication to student development and project mentorship. Additionally, he was named Student of the Year during his undergraduate engineering program in 2011, further validating his consistent academic dedication and leadership. These honors demonstrate his excellence across teaching, research, and academic service, underlining a well-rounded profile as an educator and scholar committed to impactful contributions in both academic and practical spheres.

Research Skill🔬

Shashank Singh Pawar possesses a well-rounded set of research skills, grounded in both qualitative and quantitative methodologies. He is proficient in SPSS (V26) for statistical analysis and MAXQDA for qualitative data analysis, having completed certification from Emory University, Georgia. His participation in workshops on Innovative Research Methods by Prof. Russell Belk and Experimental Research Design by Prof. Giampaolo Viglia showcases his hands-on training in advanced methodologies. Shashank applies these skills in studying nuanced consumer behavior, particularly in the digital space involving AI and avatars. He is also actively involved in academic peer-review, serving as a reviewer for the International Journal of Consumer Studies (ABDC-A) and for major conferences like INDAM, further validating his critical research acumen. His capability to conceptualize, design, analyze, and present research effectively makes him a strong contributor to the academic community and positions him well for future high-impact research outputs.

Conclusion💡

Shashank Singh Pawar demonstrates a promising and emerging research profile with a unique niche in human-computer interaction and consumer behavior. His interdisciplinary background, recognized publication, and active academic engagement make him a strong candidate for an early-career researcher award. However, for top-tier “Best Researcher” recognition, increasing his publication volume, citation impact, and global collaborations would make his profile even more competitive.

Publication Top Noted✍

  • Title: From Efficiency to Immersion: Understanding Generational Differences in Avatar Interactions

  • Authors: Shashank Singh Pawar; Anubhav A. Mishra

  • Year: 2025

  • Journal: Computers in Human Behavior

Shujiao Liao | Machine Learning | Best Researcher Award

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Prof . Shujiao Liao | Machine Learning | Best Researcher Award

Professor at Minnan Normal University, China

Dr. Shujiao Liao is a full professor at the School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Fujian, China. With a strong academic background in applied mathematics and software engineering, she has dedicated her career to advancing the fields of granular computing, data mining, and machine learning. Her work bridges theoretical mathematics and computational methodologies, enabling novel approaches to intelligent data analysis. Over the years, Dr. Liao has played a pivotal role in both academic teaching and research leadership, contributing significantly to her institution’s development and scholarly output. She has guided numerous students and collaborated across interdisciplinary research groups. Her commitment to innovation and academic excellence makes her a respected figure in her field. As a scholar deeply engaged in cutting-edge technologies and data science trends, she continues to contribute impactful research and strives to address complex problems with analytical precision and computational insight.

Professional Profile 

Education🎓

Dr. Shujiao Liao holds a strong interdisciplinary educational background that underpins her academic career. She earned her Master of Science degree in Applied Mathematics from Shantou University, Guangdong, China, in 2006, where she built a solid foundation in mathematical modeling and analytical reasoning. Her pursuit of advanced studies led her to obtain a Ph.D. degree in Software Engineering from the University of Electronic Science and Technology of China, Chengdu, Sichuan, in 2018. This advanced degree enabled her to integrate mathematical theory with practical software systems, contributing to her versatility in computational research. Her doctoral studies focused on bridging data-centric algorithms with intelligent systems, which now form the core of her research interests. This rich educational trajectory has allowed her to approach complex scientific questions from both a mathematical and engineering perspective, making her academic contributions particularly robust in the fields of data mining and machine learning.

Professional Experience📝

Dr. Shujiao Liao is currently a full professor at the School of Mathematics and Statistics, Minnan Normal University, Zhangzhou, Fujian, China. With an academic career that spans over a decade, she has demonstrated excellence in teaching, research, and academic leadership. In her current role, she teaches advanced mathematics and computational theory courses, supervises postgraduate research projects, and actively engages in departmental development. She has led several internal and collaborative research initiatives in granular computing and machine learning, working closely with both academic and industrial partners. Her experience also includes conference presentations, curriculum development, and cross-disciplinary project coordination. She is recognized for her effective mentorship, contributing to the growth of young researchers and promoting high standards in academic inquiry. Through her consistent professional contributions, Dr. Liao has helped elevate her institution’s research standing and continues to serve as a vital resource for the academic community in mathematics and software research.

Research Interest🔎

Dr. Shujiao Liao’s research interests span several pivotal domains in computer science and applied mathematics, with a particular focus on granular computing, data mining, and machine learning. Her work in granular computing explores how knowledge can be structured and processed using information granules, improving the interpretability and efficiency of decision-making systems. In the area of data mining, she investigates algorithms for pattern discovery, classification, and clustering, contributing to improved data-driven strategies in scientific and industrial applications. Her interests in machine learning include developing intelligent models capable of adaptive learning and robust performance across complex datasets. Dr. Liao’s research bridges theory and application, aiming to solve real-world problems such as intelligent diagnostics, automated reasoning, and big data analysis. Her interdisciplinary focus allows her to work on innovative projects that combine mathematical rigor with computational techniques, positioning her as a contributor to the evolving field of intelligent systems and artificial intelligence.

Award and Honor🏆

While specific awards and honors for Dr. Shujiao Liao were not provided in the given information, her appointment as a full professor reflects recognition of her academic contributions and research leadership. Attaining such a role typically involves competitive peer-reviewed evaluations, consistent scholarly output, and excellence in teaching and mentorship. It is likely that she has received internal university-level commendations, research project funding awards, or participation in prestigious academic panels, common among professors of her standing. If available, details such as Best Paper Awards, Research Excellence Awards, or National Science Grants would further highlight her academic acclaim. Her long-standing role in the academic community and sustained focus on impactful research suggest she is a strong candidate for further honors at national or international levels. Formal acknowledgment through such accolades would complement her already impressive academic and research credentials, reinforcing her eligibility for broader recognitions such as the Best Researcher Award.

Research Skill🔬

Dr. Shujiao Liao possesses a robust set of research skills grounded in both theoretical understanding and practical application. She demonstrates strong expertise in mathematical modeling, algorithm development, and data analysis, which are essential for her work in granular computing and data mining. Her proficiency in applying machine learning techniques to complex datasets enables her to design predictive models with real-world relevance. She is adept at academic writing, literature review, and hypothesis-driven exploration, essential for high-quality publications and grant writing. Additionally, Dr. Liao has strong collaborative and project management skills, allowing her to lead interdisciplinary research teams and coordinate joint research initiatives. Her experience in supervising graduate theses further reflects her ability to guide rigorous research methodologies. She is also likely skilled in programming languages and tools used in data science, such as Python, MATLAB, or R, further supporting her contributions to computational research domains.

Conclusion💡

Dr. Shujiao Liao is a strong candidate for the Best Researcher Award, particularly within fields like granular computing and machine learning. Her academic background and full professorship position suggest a high level of expertise and leadership. To solidify her candidacy for top-tier recognition, showcasing quantifiable research outcomes, international influence, and broader impact will be important.

Publications Top Noted✍

  • Title: WrdaGAN: A text-to-image synthesis pipeline based on Wavelet Representation and Adaptive Sample Domain Constraint strategy
    Authors: Yongchao Qiao, Ya’nan Guan, Shujiao Liao, Wenyuan Yang, Weiping Ding, Lin Ouyang
    Year: 2025
    Citation: DOI: 10.1016/j.engappai.2025.111305

  • Title: Semisupervised Feature Selection With Multiscale Fuzzy Information Fusion: From Both Global and Local Perspectives
    Authors: Nan Zhou, Shujiao Liao, Hongmei Chen, Weiping Ding, Yaqian Lu
    Year: 2025
    Citation: DOI: 10.1109/TFUZZ.2025.3540884

  • Title: S-approximation spaces extension model based on item-polytomous perspective
    Authors: Xiaojie Xie, Shujiao Liao, Jinjin Li
    Year: 2024
    Citation: DOI: 10.21203/rs.3.rs-4447331/v1

  • Title: Multi-Target Rough Sets and Their Approximation Computation with Dynamic Target Sets
    Authors: Wenbin Zheng, Jinjin Li, Shujiao Liao
    Year: 2022
    Citation: DOI: 10.3390/info13080385

  • Title: Multi-Label Attribute Reduction Based on Neighborhood Multi-Target Rough Sets
    Authors: Wenbin Zheng, Jinjin Li, Shujiao Liao, Yidong Lin
    Year: 2022
    Citation: DOI: 10.3390/sym14081652

  • Title: Attribute‐scale selection for hybrid data with test cost constraint: The approach and uncertainty measures
    Authors: Shujiao Liao, Yidong Lin, Jinjin Li, Huiling Li, Yuhua Qian
    Year: 2022
    Citation: DOI: 10.1002/int.22678

  • Title: Feature–granularity selection with variable costs for hybrid data
    Authors: Shujiao Liao, Qingxin Zhu, Yuhua Qian
    Year: 2019
    Citation: DOI: 10.1007/s00500-019-03854-2

Divya Mishra | Machine Learning | Best Researcher Award

Posted on by Computer Vision Awards

Assoc . Prof . Dr . Divya Mishra | Machine Learning | Best Researcher Award

Associate Professor at GL Bajaj Institute of Technology & Management, Greater Noida, India

Dr. Divya Mishra is a passionate and accomplished academician and AI researcher with over 13 years of cross-sectoral experience spanning academia, research, and industry. Currently serving as an Associate Professor in CSE-AIML at NIET and pursuing post-doctoral research remotely at Infrastructure University Kuala Lumpur (IUKL), her work centers on AI-driven sustainable e-governance. She brings deep expertise in machine learning, deep learning, and neural networks, underpinned by practical software development experience in Java and Python. Her PhD research addressed call drop prediction in mobile networks using an ANN-based model, resulting in near-perfect accuracy. Dr. Mishra is actively engaged in impactful research projects, including patents, edited books, and IEEE conference publications, while serving as a reviewer, session chair, and technical program committee member in prestigious forums. With a commitment to transparency, innovation, and sustainability in digital transformation, she is a leading voice in AI applications for public administration and smart solutions.

Professional Profile 

Education🎓

Dr. Divya Mishra holds a robust academic background in computer science and electronics. She earned her Ph.D. in Computer Science and Engineering from Noida International University in August 2021, with research focused on mitigating mobile network call drops using deep learning. She previously completed her M.Tech in Computer Science (Full-Time) from the same institution with a stellar CGPA of 9.2, securing a Gold Medal. Her postgraduate studies include an MCA from U.P. Technical University in 2011 with 77.4%, and a BCA from IGNOU, New Delhi. She also holds a Diploma in Electronics Engineering from B.T.E. Lucknow with 72.95%. Her academic journey reflects a consistent trajectory of academic excellence, technical competence, and multidisciplinary learning. Recognized for her honors during MCA by the Governor of Uttar Pradesh, Dr. Mishra’s educational path has equipped her with the theoretical and applied foundation required for her advanced research in AI, machine learning, sustainable systems, and digital governance.

Professional Experience📝

Dr. Divya Mishra boasts over 13 years of versatile professional experience across academia, industry, and research. She currently serves as an Associate Professor in the CSE-AIML Department at NIET, Greater Noida, since May 2025, while also pursuing post-doctoral research on AI-driven e-governance at IUKL, Malaysia. Her academic tenure includes Assistant Professor roles at GL Bajaj Institute and GNIOT, where she taught and mentored students in AI, ML, and data analytics. Previously, she was a Research Scholar at Noida International University, contributing significantly to AI-based telecom systems. Her industrial experience includes software development roles at Tripti e Solutions, Apex TG India Pvt. Ltd., and IIHT Ltd, where she also served as Center Head. She began her technical journey as a Diploma Trainee at Indian Telephone Industries Ltd. Her multifaceted experience enables her to seamlessly integrate theoretical concepts with practical applications in her teaching and research efforts.

Research Interest🔎

Dr. Divya Mishra’s research interests lie at the intersection of artificial intelligence, machine learning, deep learning, and sustainable governance systems. She is particularly passionate about developing intelligent, real-time AI-driven solutions for public administration, telecom, e-governance, and smart environmental monitoring. Her doctoral research focused on mitigating call drops in mobile networks through ANN-based models integrated into a real-time mobile application. Her post-doctoral focus extends into AI-powered sustainable e-governance frameworks, emphasizing transparency and accountability. She is also involved in multidisciplinary projects such as wildlife monitoring using deep learning, hand sign language recognition, waste classification, and emotion recognition from voice, reflecting her commitment to using AI for societal benefit. Dr. Mishra’s work spans practical AI implementations in healthcare, energy optimization, VANET security, and IoT systems. Through her edited books, patents, and publications, she continues to explore innovative intersections of AI with sustainability, data integrity, and policy, aligning her research with global digital transformation agendas.

Award and Honor🏆

Dr. Divya Mishra has received numerous accolades recognizing her academic excellence, impactful research, and leadership in AI. Notably, she was honored with the Shakti Award 2024 by Jansharnam NGO on Women’s Day for her outstanding contributions to technology and education. She also received the Gold Medal during her M.Tech, and her MCA degree was conferred by the Governor of Uttar Pradesh, recognizing her academic honors. She was appreciated for her contributions at international conferences like IICS 2021, and awarded the Quality Contribution Award by GNIOT, Greater Noida. Additionally, her leadership as an Innovation Ambassador at GL Bajaj’s Innovation Cell and roles as session chair and reviewer for multiple IEEE and Springer conferences further validate her active participation in shaping global research discourse. Her recognitions from institutional and national forums reflect her continuous drive toward academic excellence, innovative research, and meaningful community contributions in AI and governance.

Research Skill🔬

Dr. Divya Mishra possesses an extensive and dynamic research skill set across the AI landscape. She is proficient in programming languages like Python, Java, and C, and has a deep command over machine learning, deep learning, neural networks, and data analysis. Her expertise includes developing intelligent algorithms for real-time applications, evidenced by her ANN-based call drop prediction model and integration into the MyTelecomApp. She has published and reviewed numerous peer-reviewed papers, contributed to edited books, and filed multiple AI-driven patents across domains such as environment, health, and security. Dr. Mishra excels in research writing, patent drafting, project conceptualization, and conference management. She also has experience in hands-on technical training and mentoring, contributing to student development and curriculum design. Her interdisciplinary skills allow her to translate complex AI frameworks into socially impactful, sustainable solutions, making her a versatile and effective researcher in applied artificial intelligence and digital innovation ecosystems.

Conclusion💡

Dr. Divya Mishra demonstrates strong qualifications, multidisciplinary impact, and innovative leadership that make her a highly suitable candidate for the Best Researcher Award. Her ongoing postdoctoral work, numerous publications, patents, and reviewer engagements speak to her active and impactful research career. With minor enhancements in global collaborations, funding portfolios, and citation metrics, her candidacy would become even more compelling.

Publications Top Noted✍

  1. Title: Self-optimization in LTE: An approach to reduce call drops in mobile network
    Authors: D. Mishra, A. Mishra
    Year: 2018
    Citations: 8

  2. Title: Sentimental Voice Recognition: An Approach to Analyse the Emotion by Voice
    Authors: A. Gupta, D. Mishra
    Year: 2024
    Citations: 2

  3. Title: Neural Network: A Way to Know Consumer Satisfaction During Voice Call
    Authors: D. Mishra, S. Mishra
    Year: 2022
    Citations: 2

  4. Title: Performance Enhanced and Improvised Approach to Reduce Call Drops Using LTE-SON
    Authors: D. Mishra, A. Mishra
    Year: 2019
    Citations: 2

  5. Title: Drowsiness Alert System: An Approach To Save The Life
    Authors: A. Chandra, D. Mishra, B. Shaw, A. Gupta
    Year: 2023
    Citations: 1

  6. Title: Mobility Robustness Optimization Using ANN for Call Drop Prediction
    Authors: D. Mishra, S. Yadav
    Year: 2020
    Citations: 1

  7. Title: Fine tuning of MapReduce jobs using parallel K Map clustering
    Authors: D. Mishra, S. Yadav
    Year: 2019
    Citations: 1

  8. Title: Empowering Sustainable Waste Management: A Comparative Study of Machine Learning Models for Citizen Engagement
    Authors: D. Mishra, R. Kumar, A.B. bin Abdul Hamid
    Year: 2025

  9. Title: Machine Learning: A Self-Optimized Boon for Deaf and Mute to Recognize Real-Time Hand Sign Language
    Authors: P. Pandey, D. Mishra
    Year: 2025

  10. Title: Character Detection: An Approach to Clarify the Texts Using Machine Learning
    Authors: B. Shaw, D. Mishra
    Year: 2025

  11. Title: Intellicam: A Self-Optimizing Approach to Detect Burglary using Machine Learning
    Authors: A. Chandra, D. Mishra
    Year: 2025

  12. Title: Integrating Cryptographic Techniques with Machine Learning Algorithms for Enhanced Data Privacy and Information Security: A Mathematical Framework
    Authors: G. Merlin Florrence, D. Mishra, G. Ghule, P.K. Sahu, Singh
    Year: 2024

  13. Title: A Mathematical Framework for Enhancing IoT Security in VANETs: Optimizing Intrusion Detection Systems through Machine Learning Algorithms
    Authors: D. Mishra, S. Moudgi, D. Virmani, Y.P. Faniband, A.B. Nandyal, P.K. Sahu
    Year: 2024

  14. Title: YOLO: A way to identify gemstone and predict its relevant finger to wear
    Authors: D. Mishra, S. Mishra
    Year: 2023

  15. Title: Instant Energy Products: An Analysis
    Authors: D.M. Mohasin Haque, Irfan Ahamad
    Year: 2023

  16. Title: Mid–Point Sorting Algorithm: A New Way to Sort
    Authors: A. Garg, V. Patel, D. Mishra
    Year: 2022

  17. Title: A review on call drop
    Authors: D. Mishra, A. Mishra
    Year: 2016

Bharati Chaudhari | Edge Detection | Best Researcher Award

Posted on by Computer Vision Awards

Ms . Bharati Chaudhari | Edge Detection | Best Researcher Award

Assitstant Professor at Maharashtra Institute of Technology, Chh. Sambhajinagar, India

Ms. Bharati Prakash Chaudhari is an experienced academician and researcher with over 18 years of teaching experience in computer science and engineering. Currently serving as an Assistant Professor at MIT, Aurangabad, she has consistently demonstrated a strong commitment to research and education. Her expertise spans image processing, machine learning, and digital system development, with active contributions to both academic research and industry-oriented projects. She has authored multiple research papers in international journals and conferences, including Scopus-indexed publications and IEEE proceedings. Additionally, her involvement in intellectual property development through several copyrights underscores her original contributions to technical education. Ms. Chaudhari continues to pursue her Ph.D. in Computer Science and Engineering at Dr. Babasaheb Ambedkar Marathwada University, reflecting her dedication to academic growth. Her work bridges theoretical knowledge with practical application, particularly through collaborations with industry for digital tool development. She is a proactive, skilled, and forward-looking researcher shaping the field of computer engineering.

Professional Profile 

Education🎓

Ms. Bharati Prakash Chaudhari holds a Master of Engineering degree in Computer Science and Engineering from Government College of Engineering, Aurangabad, affiliated with Dr. Babasaheb Ambedkar Marathwada University (Dr. B.A.M.U.), where she graduated in 2010 with distinction, scoring 81.25%. She earned her Bachelor of Engineering in Computer Engineering from K.K. Wagh College of Engineering, Nashik under Pune University in 2003, securing first-class marks with 62.2%. Currently, she is pursuing her Ph.D. in Computer Science and Engineering from Dr. B.A.M.U., Aurangabad. Her academic background showcases a steady progression through well-regarded institutions and reflects a continuous pursuit of advanced knowledge in her domain. Her postgraduate studies have equipped her with a solid foundation in algorithm development, computational models, and system-level design. The ongoing doctoral research further strengthens her analytical and research capabilities, positioning her to contribute meaningfully to emerging trends in machine learning and image processing.

Professional Experience📝

Ms. Bharati Prakash Chaudhari has over 18 years of professional academic experience in engineering education. She began her teaching career in February 2003 at MIT IT College, Cidco, Aurangabad, serving as a Lecturer for over three years. Since July 2006, she has been affiliated with MIT, Aurangabad, initially as a Lecturer and later redesignated as an Assistant Professor. Throughout her tenure, she has taught various core subjects in computer science and engineering and actively engaged in curriculum development and mentoring students. Her long-standing commitment to teaching is complemented by her involvement in research, project guidance, and departmental responsibilities. She has also contributed to industry-academic collaboration through participation in projects like digital tool development for transformer design, under GIZ–MASSIA initiatives. Ms. Chaudhari’s experience demonstrates not only her academic dedication but also her ability to integrate applied engineering practices into her educational approach, enhancing student learning and research culture.

Research Interest🔎

Ms. Bharati Prakash Chaudhari’s research interests center around Image Processing, Machine Learning, and Optimization Algorithms, with a keen focus on applying intelligent computing methods to solve practical problems in healthcare and security. Her recent work on edge detection using Ant Colony Optimization for medical images illustrates her interest in bio-medical image analysis. She also explores areas such as reversible data hiding, digital watermarking, and encrypted image processing—topics that are critical to data security and digital forensics. Her Ph.D. research and publications reflect an effort to integrate biologically inspired algorithms into traditional image processing techniques. Moreover, she has shown a consistent interest in enhancing data representation, pattern recognition, and system intelligence. Through hybrid algorithm development and advanced segmentation techniques, Ms. Chaudhari aims to push the boundaries of image understanding and machine learning applications, particularly in domains where accurate visual interpretation is crucial, such as diagnostics, surveillance, and automation.

Award and Honor🏆

Ms. Bharati Prakash Chaudhari has been recognized for her scholarly contributions through multiple Intellectual Property Rights (IPRs) registrations, including copyrights on algorithmic learning materials and applied computer science concepts such as Dijkstra’s Algorithm, Histogram Equalization, and Finite Automata Design. These IPRs reflect her dedication to developing high-quality, original educational content and research outputs. While formal academic awards are not explicitly listed, her achievements in publishing papers in Scopus-indexed journals and prestigious conferences like IEEE and Elsevier Procedia signify academic excellence. Her active involvement in applied research projects, such as the Digital Tool Development for Transformer Design under a government-industry partnership (GIZ-MASSIA), further underscores her practical impact. Through these achievements, she has earned peer recognition within academic and industrial circles. Her participation in international events and successful collaborations with senior researchers demonstrate her growing reputation as a capable and emerging researcher in the field of computer engineering.

Research Skill🔬

Ms. Bharati Prakash Chaudhari possesses strong research skills across multiple domains of computer science, particularly in image analysis, optimization algorithms, and machine learning models. She is proficient in applying Ant Colony Optimization, ICA (Independent Component Analysis), and encryption-based data hiding techniques for real-world problems. Her skill set includes the ability to design experimental methodologies, simulate and validate results, and interpret complex datasets for image processing tasks. She is adept at using MATLAB and other relevant software tools for developing and testing algorithms. Additionally, she is capable of translating conceptual ideas into practical implementations, as evident in her industry collaboration for transformer design automation. Her copyright registrations for algorithmic content reflect her strength in educational research and tool development. With a foundation in both academic writing and hands-on experimentation, Ms. Chaudhari’s research competencies bridge theoretical understanding and applied problem-solving—making her a valuable contributor to innovation-driven computing research.

Conclusion💡

Ms. Bharati Prakash Chaudhari is a strong candidate for the Best Researcher Award, especially given her longevity in academia, publication record, IPRs, and participation in reputed conferences. However, to be a top-tier awardee, finalizing her Ph.D. and enhancing her presence in globally ranked journals, along with measurable citation metrics, would make her profile even more competitive.

Publications Top Noted✍

  • Title: Hepatoprotective activity of Hydroalcoholic extract of Momordica charantia Linn. leaves against Carbon tetrachloride induced Hepatopathy in Rats
    Authors: KRB, Chaudhari BP, VJ Chaware, YR Joshi
    Year: 2009
    Citations: 45

  • Title: Protective effect of the aqueous extract of Momordica charantia leaves on gentamicin induced nephrotoxicity in rats
    Authors: KRB, VJ Chaware, BP Chaudhary, MK Vaishnav
    Year: 2011
    Citations: 20

  • Title: Protective effect of the aqueous extract of Phaseolus radiatus seeds on gentamicin induced nephrotoxicity in rats
    Authors: VJ Chaware
    Year: 2012
    Citations: 16

  • Title: Quality by design (QbD) concept review in pharmaceuticals
    Authors: K Jagtap, B Chaudhari, V Redasani
    Year: 2022
    Citations: 11

  • Title: Development and validation of spectrophotometric method for simultaneous estimation of meclizine hydrochloride and pyridoxine hydrochloride in tablet dosage form
    Authors: SA Shinde, ZM Sayyed, BP Chaudhari, VJ Chaware, KR Biyani
    Year: 2016
    Citations: 10

  • Title: Development and validation of UV-spectrophotometric method for simultaneous estimation of amlodipine besylate and hydrochlorothiazide in combined dosage form
    Authors: Z Sayyed, S Shinde, V Chaware, B Chaudhari, K Biyani
    Year: 2015
    Citations: 9

  • Title: A cross-sectional prescription audit database for anti-anginal drugs with impact of essential drug list and standard treatment guidelines on prescription pattern in Nasik city
    Authors: V Chaudhari, B Chaudhari, A Khairnar
    Year: 2011
    Citations: 7

  • Title: Approaches of digital image watermarking using ICA
    Authors: BP Chaudhari, AK Gulve
    Year: 2010
    Citations: 7

  • Title: A Review on in situ Gel of Gastro Retentive Drug Delivery System
    Authors: BV Aiwale, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 6

  • Title: Image segmentation using hybrid ant colony optimization: A review
    Authors: B Chaudhari, P Shetiye, A Gulve
    Year: 2021
    Citations: 6

  • Title: A Review on Diverging approaches to Fabricate Polymeric Nanoparticles
    Authors: S Deshmukh, B Chaudhari, A Velhal, V Redasani
    Year: 2022
    Citations: 5

  • Title: A Validated RP-HPLC Method for Simultaneous Estimation of Tizanidine and Nimesulide in Bulk and Pharmaceutical Formulation
    Authors: KD Bharatee Chaudhari
    Year: 2020
    Citations: 5

  • Title: Pharmacosome as a Vesicular Drug Delivery System
    Authors: RR Shinde, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 4

  • Title: Influence of Newly Synthesized Superdisintegrant on Dissolution Rate Enhancement of Carbamazepine using Liquisolid Compact Technique
    Authors: GV Raut, PB Chaudhari, KV Redasani
    Year: 2022
    Citations: 4

  • Title: Development and validation of UV-spectrophotometric method for simultaneous estimation of spironolactone and hydrochlorothiazide in pharmaceutical formulation
    Authors: Z Sayyed, S Shinde, V Chaware, B Chaudhari, M Zuber, M Sayyed
    Year: 2015
    Citations: 4

  • Title: A compendious review on biodegradable polymeric nanoparticles
    Authors: S Deshmukh, B Chaudhari, A Velhal, V Redasani
    Year: 2022
    Citations: 3

  • Title: Cleaning Validation in Pharmaceutical Industry
    Authors: P Khalate, B Chaudhari, V Redasani
    Year: 2022
    Citations: 2

  • Title: A Novel Tool for Controlled Delivery: Transdermal Drug Delivery System
    Authors: AV Panval, BP Chaudhari, AB Velhal, VK Redasani
    Year: 2022
    Citations: 2

  • Title: A Review on Pharmaceutical Regulatory Authority of India, USA, UK, Australia
    Authors: AA Shinde, AS Gurav, BP Chaudhari, VK Redasani
    Year: 2024
    Citations: 1

  • Title: Review on Colon Targeted Drug Delivery System
    Authors: NB Waghmode, SV Dhanje, BP Chaudhari, VK Redasani
    Year: 2024
    Citations: 1

Liao Jun Guo | Object Detection | Best Researcher Award

Posted on by Computer Vision Awards

Prof . Dr . Liao Jun Guo | Object Detection | Best Researcher Award

Teacher at Hunan University of Science and Technology, China

Prof. Dr. Jun Guo Liao is a distinguished academic and researcher serving as a Full Professor at the School of Computer Science and Engineering, Hunan University of Science and Technology, China. With a Ph.D. in Information Security earned from Huazhong University of Science and Technology in 2007, he brings over 15 years of scholarly excellence and pedagogical contribution to his field. His professional journey has been defined by a steadfast commitment to information security and the broader discipline of computer applications. Throughout his academic career, Prof. Liao has mentored numerous students, contributed to curriculum development, and engaged in research that addresses pressing issues in digital safety and technological advancement. His experience and leadership have made significant contributions to institutional growth, while his ongoing research aims to support the secure evolution of computing systems in a connected world. He continues to pursue innovative solutions to challenges in cybersecurity and digital system integration.

Professional Profile 

Education🎓

Prof. Dr. Jun Guo Liao has a strong educational background rooted in information technology and computer science. He earned his Ph.D. in Information Security from the prestigious Huazhong University of Science and Technology in 2007, one of China’s leading institutions in science and engineering. During his doctoral studies, he specialized in areas related to data protection, system vulnerabilities, cryptographic protocols, and secure computing systems. His academic training equipped him with a deep understanding of cybersecurity frameworks, cryptography, and network defense mechanisms. Prior to his doctoral studies, Prof. Liao likely completed a rigorous undergraduate and master’s education in computer science or related fields, building a solid foundation for his future research endeavors. His educational journey has not only shaped his technical expertise but also reinforced his ability to approach complex research problems with academic rigor and analytical depth. This strong academic foundation continues to underpin his success as a researcher and educator.

Professional Experience📝

Prof. Dr. Jun Guo Liao has accumulated extensive professional experience as a dedicated educator, researcher, and academic leader. He currently serves as a Full Professor at the School of Computer Science and Engineering at Hunan University of Science and Technology, where he has played a pivotal role in both teaching and research. His responsibilities span delivering advanced-level courses, supervising graduate students, and contributing to academic policy-making within the university. Since completing his Ph.D. in 2007, he has focused his career on advancing the field of information security and computer applications. Over the years, Prof. Liao has likely led funded research projects, participated in national-level research programs, and collaborated with industrial partners to translate theoretical work into practical solutions. His professional achievements reflect a sustained commitment to academic excellence, institutional development, and scientific contribution. His role as a faculty leader highlights his ability to foster research innovation and academic integrity.

Research Interest🔎

Prof. Dr. Jun Guo Liao’s research interests center on information security and computer applications, two domains of critical importance in the digital age. His work explores the development of secure computing environments, the design of cryptographic algorithms, and the protection of data across networks and systems. He is particularly interested in safeguarding sensitive information against cyber threats, improving authentication systems, and fortifying infrastructure against unauthorized access. Additionally, Prof. Liao’s interests likely extend into applied computer science areas such as secure software development, cloud computing security, and artificial intelligence in cybersecurity. His research strives to bridge theoretical computer science with practical applications, offering real-world solutions to modern digital challenges. Through his work, Prof. Liao contributes to building resilient and trustworthy computing environments. His interest in interdisciplinary collaboration enables him to address complex problems that intersect with data privacy, digital ethics, and secure communications, making his research highly impactful and timely.

Award and Honor🏆

While specific awards and honors were not listed in the available curriculum vitae, it is likely that Prof. Dr. Jun Guo Liao has received recognition at various institutional, regional, or national levels for his academic and research achievements. As a Full Professor with a Ph.D. in Information Security and a sustained academic career, he may have been honored with outstanding teaching awards, research excellence awards, or government-funded research grants. His contributions to the advancement of cybersecurity and academic mentorship position him as a valuable figure in the academic community, potentially earning him roles in review panels, conference committees, or research consortiums. Furthermore, his long-standing affiliation with Hunan University of Science and Technology suggests consistent internal recognition for academic leadership and service. Additional details on his recognitions would further affirm his suitability for prestigious awards such as the Best Researcher Award, reflecting his excellence and dedication in his field.

Research Skill🔬

Prof. Dr. Jun Guo Liao possesses advanced research skills in the domains of information security and computer applications, which encompass both theoretical and applied methodologies. His expertise includes cryptographic system design, vulnerability assessment, secure communication protocols, and data protection strategies. He demonstrates strong analytical thinking, problem-solving abilities, and a keen understanding of algorithmic implementation for secure systems. Over the years, he has likely developed skills in research project management, academic writing, peer reviewing, and mentoring graduate students. Additionally, his technical skill set may include programming, network analysis, penetration testing, and proficiency in tools related to cybersecurity. Prof. Liao is also adept at conducting literature reviews, designing experimental models, and evaluating system security in real-world applications. These research competencies enable him to contribute meaningfully to the academic discourse on digital safety while promoting innovation in technology. His continuous development of research skills supports his contributions to scholarly excellence and institutional impact.

Conclusion💡

Based on the limited available information, Prof. Dr. Jun Guo Liao appears to be a strong academic with expertise in information security, making him potentially eligible for the Best Researcher Award. However, to confidently support his nomination, it is highly recommended to provide:

  • A complete list of publications and citation metrics

  • Details of research projects, funding, and impactful contributions

  • Any national/international recognitions or awards

  • Evidence of research leadership and community involvement

Publications Top Noted✍

  • Title: MBB-YOLO: A comprehensively improved lightweight algorithm for crowded object detection
    Year: 2024
  • Title: A multikey fully homomorphic encryption privacy protection protocol based on blockchain for edge computing system
    Year: 2023
    Citations: 5
  • Title: DTSAC: Smart Contract-based Access Control with Delegation and Trust Management
  • Title: An adaptive traffic sign recognition scheme based on deep learning in complex environment




HAIFEI CHEN | Visual SLAM | Best Researcher Award

Posted on by Computer Vision Awards

Assoc .Prof. Dr. HAIFEI CHEN | Visual SLAM | Best Researcher Award

Central South University of Forestry and Technology, China

Dr. Haifei Chen is an accomplished Associate Professor at the School of Mechanical and Intelligent Manufacturing, Central South University of Forestry and Technology. Born in August 1990 in Chenzhou, Hunan, he is a dedicated scholar in the field of robotics and intelligent control. With a strong academic background and robust research portfolio, he has led numerous national and provincial research projects focusing on teleoperation robotics, multi-agent coordination, SLAM, and networked control systems. His scholarly contributions include over 20 high-impact SCI-indexed journal articles and multiple patents. A recognized academic leader, Dr. Chen holds key roles in national research centers and professional societies and serves as a reviewer for top-tier IEEE journals. His research has significantly advanced space robotics and teleoperation technologies. Through innovation, leadership, and academic excellence, he has positioned himself as a promising and impactful researcher in the field of intelligent robotics.

Professional Profile 

Education🎓

Dr. Haifei Chen pursued his doctoral studies at the School of Astronautics, Northwestern Polytechnical University, beginning in September 2017. His Ph.D. specialization was in navigation, guidance, and control under the supervision of Professor Panfeng Huang, a prominent academician and expert affiliated with the National Distinguished Youth Fund and military science commissions. Dr. Chen’s doctoral research focused on time-delay modeling and compensation for space teleoperation systems, laying a strong theoretical foundation for his current work. Prior to his doctoral education, he had successfully cleared national English proficiency exams including CET-6 and achieved an IELTS score of 6.0, reflecting a solid command of the English language for academic communication. His educational experience has equipped him with expertise in robotics, control systems, and artificial intelligence, supporting his contributions to both theoretical research and engineering practice. His education forms the core of his academic identity and drives his research in intelligent robotic systems.

Professional Experience📝

Dr. Haifei Chen currently serves as an Associate Professor at the School of Mechanical and Intelligent Manufacturing, Central South University of Forestry and Technology, a position he has held since December 2023. Prior to this, he was a Lecturer at the School of Mechanical and Electrical Engineering at the same university from February 2022 to December 2023. His academic trajectory has been steadily progressive, with research and teaching roles focused on robotic teleoperation, intelligent control, and remote robotic systems. His leadership includes managing multiple funded projects, mentoring students, and contributing to institutional development as a discipline leader in forestry equipment and intelligent systems. He is also affiliated with key research centers, including the National Engineering Research Center for Economic Forest Harvesting Equipment. His experience bridges fundamental research and practical implementation, making him a vital contributor to the advancement of robotics in forestry and space technology domains.

Research Interest🔎

Dr. Haifei Chen’s research interests are deeply rooted in robotic teleoperation, intelligent control, and multi-agent system collaboration. His work explores the challenges of time-delay in remote control systems, particularly in space teleoperation, with the goal of enhancing the precision and reliability of robotic operations under communication constraints. He is also focused on visual SLAM (Simultaneous Localization and Mapping), predictive control, and networked control systems—all critical to the development of autonomous and semi-autonomous robotic platforms. His recent research involves developing teleoperation systems for agricultural and forestry robots, such as oil-tea camellia fruit picking, using advanced machine learning algorithms and sensor fusion techniques. Dr. Chen aims to bridge the gap between theoretical models and practical deployment by incorporating real-time data processing, human-robot interaction, and decision-making algorithms. These interests reflect a multidisciplinary approach, integrating robotics, AI, and control theory to create intelligent, adaptive, and scalable robotic systems.

Award and Honor🏆

Dr. Haifei Chen has earned recognition both as a researcher and a community contributor. He serves as an expert reviewer for the National Natural Science Foundation of China (NSFC), reflecting his authority in his research field. He is the Vice Director of the National Engineering Research Center for Economic Forest Harvesting Equipment and serves on the Youth Committee of the Chinese Society of Forestry and the Robotics Subcommittee. These positions highlight his leadership within the academic and scientific communities. Furthermore, Dr. Chen has served as a reviewer for several internationally renowned journals, including IEEE Transactions on Systems, Man and Cybernetics: Systems, IEEE Transactions on Mechatronics, IEEE RA-L, Acta Astronautica, and ISA Transactions. His contributions to academic peer review and research management are clear indicators of professional excellence. While individual awards are not specifically listed, his prestigious roles and responsibilities underscore his impact and growing recognition in the robotics field.

Research Skill🔬

Dr. Haifei Chen possesses a versatile and advanced set of research skills in robotics and intelligent systems. He is highly proficient in modeling and controlling time-delay in networked and remote robotic systems—skills critical for real-time space and teleoperation environments. He has strong command over predictive control algorithms, Smith predictors, and error loop correction methods. His expertise extends to multi-agent coordination, robot vision (including SLAM), and motion planning, where he integrates machine learning techniques such as CNNs, BiGRUs, and attention mechanisms for state prediction and decision-making. He is adept at developing algorithms that optimize robotic response in high-latency environments, such as relay communication-based space missions. In addition to algorithm design, he is experienced in real-time robotic system integration and experimental validation. With skills spanning simulation, hardware interfacing, and intelligent control, Dr. Chen brings a comprehensive and technically rigorous approach to research that bridges theoretical development and engineering implementation.

Conclusion💡

Dr. Haifei Chen presents a compelling case as a young and dynamic researcher who combines technical depth, publication excellence, research leadership, and innovation in intelligent robotics and remote control systems. He shows a rare blend of academic rigor, engineering practice, and institutional responsibility.

With minor enhancements in international outreach and broader recognition, he is on a strong trajectory toward becoming a leading figure in his domain. He is not only suitable, but in fact, a competitive nominee for the Best Researcher Award.

Publications Top Noted✍

  • Title: Path Integral Policy Improvement and Dynamic Movement Primitives Fusion-Based Impedance Force Control With Error Loop Correction
    Authors: Mujie Liu, Haifei Chen, Lijun Li, Zhiqiang Ma, Yong Xu, Hui Zhang
    Year: 2025
    Citation: IEEE Transactions on Automation Science and Engineering, DOI: 10.1109/TASE.2025.3562677

  • Title: Mapping Noise Optimization of the Cartographer on the Premise of Comparative Experimental Analysis
    Authors: Xuefei Liu, Haifei Chen, Zicheng Gao, Meirong Chen, Lijun Li, Kai Liao
    Year: 2025
    Citation: Mechatronics, DOI: 10.1016/j.mechatronics.2024.103289

  • Title: Position Prediction for Space Teleoperation With SAO-CNN-BiGRU-Attention Algorithm
    Authors: Keli Wu, Haifei Chen, Lijun Li, Zhengxiong Liu, Haitao Chang
    Year: 2024
    Citation: IEEE Robotics and Automation Letters, DOI: 10.1109/LRA.2024.3498700

  • Title: Bilateral Synchronization Control of Networked Teleoperation Robot System
    Authors: Zhengxiong Liu, Haifei Chen, Panfeng Huang, Yang Yang
    Year: 2024
    Citation: International Journal of Robust and Nonlinear Control, DOI: 10.1002/rnc.7374

  • Title: Time-Delay Modeling and Simulation for Relay Communication-Based Space Telerobot System
    Authors: Haifei Chen, Zhengxiong Liu, Panfeng Huang, Zhian Kuang
    Year: 2022
    Citation: IEEE Transactions on Systems, Man, and Cybernetics: Systems, DOI: 10.1109/TSMC.2021.3090806

  • Title: Time-Delay Prediction–Based Smith Predictive Control for Space Teleoperation
    Authors: Haifei Chen, Zhengxiong Liu
    Year: 2021
    Citation: Journal of Guidance, Control, and Dynamics, DOI: 10.2514/1.G005714

Jingbin Liu | Sensor fusion | Best Researcher Award

Posted on by Computer Vision Awards

Prof . Jingbin Liu | Sensor fusion | Best Researcher Award

Professor at  Royal Institute of Technology, Sweden

Associate Professor Jingbin Liu is an accomplished geospatial scientist specializing in mobile mapping, 3D modeling, and robotics navigation. With a strong foundation in geomatics and over 15 years of international research experience, he has contributed significantly to both academic and applied aspects of geospatial technologies. Currently serving at KTH Royal Institute of Technology in Sweden, he previously held professorial and senior research roles in China and Finland. Liu has led over 15 major research projects and secured substantial external funding, indicating his strong leadership and innovation capacity. His scholarly output includes more than 100 peer-reviewed publications, over 5,300 citations, and an h-index of 37, reflecting his global impact. He is also known for successfully mentoring postdoctoral and doctoral researchers, many of whom have advanced to prominent academic and research positions. Liu’s work bridges the gap between research and real-world application, notably through patented technologies and industry collaborations.

Professional Profile 

Education🎓

Jingbin Liu holds a distinguished academic background rooted in geomatics and satellite navigation. He earned his Ph.D. in Geomatics from Wuhan University’s School of Geodesy and Geomatics in 2008, with a dissertation focusing on regional ionospheric TEC prediction using GPS—rated as excellent. He also completed his Master of Science in Engineering at Wuhan University in 2004, with a thesis on simulating and verifying the Galileo satellite navigation system, also rated excellent. In 2016, Liu was granted a prestigious Docentship in Geospatial Information Technology, specifically in robotics navigation and 3D modeling, by Wuhan University’s State Key Laboratory of Surveying, Mapping and Remote Sensing. This academic journey reflects a blend of theoretical expertise and applied innovation, providing a solid foundation for his research and teaching. Liu’s education has equipped him with a rare combination of depth in geospatial sciences and a multidisciplinary approach to cutting-edge technological challenges.

Professional Experience📝

Jingbin Liu brings a wealth of global experience in academia and research. Since January 2025, he has been serving as an Associate Professor at KTH Royal Institute of Technology, Sweden. Prior to this, he held a full professorship at Wuhan University from 2016 to 2024 and was also a Visiting Professor at the Finnish Geospatial Research Institute (FGI). He previously worked as a Senior Researcher at FGI and the Academy of Finland’s Center of Excellence in Laser Scanning Research from 2008 to 2019. His career reflects a seamless integration of academic leadership and advanced research contributions across China, Finland, and Sweden. Liu has actively managed multidisciplinary teams and international collaborations, with a proven track record in securing competitive research funding and leading innovative projects. His professional journey exemplifies a robust commitment to advancing geospatial technologies through both theoretical advancements and real-world implementation.

Research Interest🔎

Associate Professor Jingbin Liu’s research interests lie at the intersection of geospatial information technology and intelligent systems. He specializes in mobile mapping, 3D modeling of built environments, robotics navigation, and indoor positioning. His work focuses on developing advanced algorithms and systems that enable accurate and efficient geospatial data acquisition, particularly in challenging environments such as underground infrastructure and urban interiors. Liu has also contributed to integrating LiDAR, GPS, and vision-based technologies to enhance positioning accuracy and environmental modeling. His interest extends to autonomous driving systems, infrastructure inspection robots, and wearable geolocation systems for worker safety. By addressing real-world geospatial challenges with state-of-the-art tools, Liu’s research supports the evolution of smart cities and intelligent navigation solutions. He is particularly invested in transforming traditional surveying and mapping practices through automation, AI integration, and cross-disciplinary innovation, thereby enhancing the operational efficiency and accuracy of geospatial data systems.

Award and Honor🏆

Jingbin Liu has received multiple prestigious awards and honors that recognize his contributions to geospatial research and technological innovation. In 2023, he was honored with the Science and Technology Progress Award by the Hubei Provincial Government, and in 2021, he received the Science and Technology Advancement Award from the China Satellite Navigation and Positioning Association. His excellence in applied research earned him the Best Paper Award at the IEEE UPINLBS Conference in 2019. Internationally, he won first place in the PerfLoc Indoor Positioning Competition held by NIST in the United States and the IPIN Indoor Positioning Competition in France, both in 2018. He was also awarded the First Prize for Scientific and Technological Progress by the China Society of Geodesy. These accolades reflect his leadership in positioning and navigation technologies and his significant impact on both academic and industrial sectors worldwide.

Research Skill🔬

Jingbin Liu possesses advanced research skills in geospatial computation, mobile mapping, and sensor fusion. He is proficient in integrating LiDAR, GNSS, visual-inertial odometry, and SLAM (Simultaneous Localization and Mapping) systems to develop high-precision navigation solutions. His expertise extends to robotics navigation in complex environments, such as underground pipelines, where he has led the development of intelligent inspection systems. Liu demonstrates strong capabilities in algorithm design for positioning, real-time data processing, and 3D environmental reconstruction. He also has experience with indoor positioning systems using WiFi, Bluetooth, and 3D modeling integration. Beyond technical skills, Liu excels in project leadership, proposal writing, and technology transfer—evidenced by his successful patent and partnerships with industry stakeholders. His mentoring ability, particularly in guiding postdocs and PhD students to success, highlights his academic training expertise. Altogether, his skills position him as a top-tier researcher in applied geospatial technology and spatial computing.

Conclusion💡

Associate Professor Jingbin Liu is highly suitable for the Best Researcher Award. His excellent academic record, consistent funding success, internationally recognized research, real-world technological innovation, and strong mentorship track make him a standout candidate. He exemplifies a researcher who bridges theory and application, academia and industry, and local and international contexts.

Publications Top Noted✍

  • Title: Is field-measured tree height as reliable as believed?
    Authors: Y Wang, M Lehtomäki, X Liang, J Pyörälä, A Kukko, A Jaakkola, J Liu, …
    Year: 2019
    Citations: 330

  • Title: A review: Remote sensing sensors
    Authors: L Zhu, J Suomalainen, J Liu, J Hyyppä, H Kaartinen, H Haggren
    Year: 2018
    Citations: 254

  • Title: A Hybrid Smartphone Indoor Positioning Solution for Mobile LBS
    Authors: J Liu, R Chen, L Pei, R Guinness, H Kuusniemi
    Year: 2012
    Citations: 237

  • Title: Human Behavior Cognition Using Smartphone Sensors
    Authors: L Pei, R Guinness, R Chen, J Liu, H Kuusniemi, Y Chen, L Chen, …
    Year: 2013
    Citations: 197

  • Title: International benchmarking of individual tree detection methods using airborne laser scanning
    Authors: Y Wang, J Hyyppä, X Liang, H Kaartinen, X Yu, E Lindberg, J Holmgren, …
    Year: 2016
    Citations: 193

  • Title: Using Inquiry-based Bluetooth RSSI Probability Distributions for Indoor Positioning
    Authors: L Pei, R Chen, J Liu, H Kuusniemi, T Tenhunen, Y Chen
    Year: 2010
    Citations: 181

  • Title: LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments
    Authors: J Tang, Y Chen, X Niu, L Wang, L Chen, J Liu, C Shi, J Hyyppä
    Year: 2015
    Citations: 163

  • Title: Using LS-SVM Based Motion Recognition for Smartphone Indoor Wireless Positioning
    Authors: L Pei, J Liu, R Guinness, Y Chen, H Kuusniemi, R Chen
    Year: 2012
    Citations: 163

  • Title: Accuracy of Kinematic Positioning Using GNSS under Forest Canopies
    Authors: H Kaartinen, J Hyyppä, M Vastaranta, A Kukko, A Jaakkola, X Yu, …
    Year: 2015
    Citations: 159

  • Title: A Review of GNSS-based Dynamic Monitoring for Structural Health Monitoring
    Authors: N Shen, L Chen, J Liu, L Wang, T Tao, D Wu, R Chen
    Year: 2019
    Citations: 140

  • Title: Spherical cap harmonic model for mapping and predicting regional TEC
    Authors: J Liu, R Chen, Z Wang, H Zhang
    Year: 2011
    Citations: 138

  • Title: The Use of a Hand-Held Camera for Individual Tree 3D Mapping
    Authors: X Liang, A Jaakkola, Y Wang, J Hyyppä, E Honkavaara, J Liu, …
    Year: 2014
    Citations: 137

  • Title: Forest Data Collection Using Terrestrial Image-Based Point Clouds
    Authors: X Liang, Y Wang, A Jaakkola, A Kukko, H Kaartinen, J Hyyppä, …
    Year: 2015
    Citations: 132

  • Title: Inquiry-Based Bluetooth Indoor Positioning via RSSI Probability Distributions
    Authors: L Pei, R Chen, J Liu, T Tenhunen, H Kuusniemi, Y Chen
    Year: 2010
    Citations: 112

  • Title: A Robust Indoor Positioning Method Based on Bluetooth Low Energy
    Authors: B Huang, J Liu, W Sun, F Yang
    Year: 2019
    Citations: 93

  • Title: iParking: An Intelligent Indoor Location-Based Smartphone Parking Service
    Authors: J Liu, R Chen, Y Chen, L Pei, L Chen
    Year: 2012
    Citations: 90

  • Title: A Survey of Simultaneous Localization and Mapping
    Authors: B Huang, J Zhao, J Liu
    Year: 2019
    Citations: 88

  • Title: Close-Range Remote Sensing of Forests: Challenges and Opportunities
    Authors: X Liang, A Kukko, I Balenović, N Saarinen, S Junttila, V Kankare, …
    Year: 2022
    Citations: 84

  • Title: M3VSNet: Unsupervised Multi-Metric Multi-View Stereo Network
    Authors: B Huang, H Yi, C Huang, Y He, J Liu, X Liu
    Year: 2021
    Citations: 82

  • Title: A Survey of Applications with Combined BIM and 3D Laser Scanning
    Authors: J Liu, D Xu, J Hyyppä, Y Liang
    Year: 2021
    Citations: 80