Jong-Hyun Kim | Applied Visual Computing | Best Researcher Award

Published on by Computer Vision Awards

Prof. Jong-Hyun Kim | Applied Visual Computing | Best Researcher Award

Associate Professor at Inha University, South Korea

Prof. Jong-Hyun Kim is an Associate Professor at the College of Software and Convergence, Department of Artificial Intelligence, Design Technology at Inha University, with a joint appointment at the Graduate School of Electrical and Computer Engineering. He is a distinguished researcher with expertise spanning computer graphics, visual effects, physically based simulation, physics engines, artificial intelligence, VR/AR, geometry processing, and GPU optimization. His career bridges academia and industry, having led and participated in numerous national research projects and industry collaborations in areas such as digital twin technology, immersive simulation systems, and AI convergence. With an impressive record of award-winning publications in reputed conferences and journals indexed in IEEE and Scopus, he has contributed significantly to advancing emerging technologies. His leadership in collaborative initiatives and dedication to innovative research continue to strengthen his impact on both scientific communities and practical applications.

Professional Profile 

ORCID Profile

Education

Prof. Jong-Hyun Kim completed his Ph.D. in Computer Science and Engineering from Korea University, following his master’s degree and bachelor’s degree in the same field from Korea University and Sejong University, respectively. His academic journey reflects a strong foundation in both theoretical and applied aspects of computer science, equipping him with advanced skills in simulation, visualization, and artificial intelligence. His studies covered a broad spectrum of technical disciplines, from physics-based modeling and geometry processing to interactive graphics and human-computer interaction. The rigorous academic training at prestigious institutions provided him with the expertise to excel in interdisciplinary research and to address complex computational challenges. This solid educational background has enabled him to integrate advanced computing techniques with creative technological solutions, laying the groundwork for his influential research contributions in academia and his ability to collaborate effectively with industry partners on innovative projects.

Professional Experience

Prof. Jong-Hyun Kim currently serves as an Associate Professor at Inha University, having previously held the same position at Kangnam University. He has also served as a lecturer and teaching fellow at Korea University, contributing to the development of academic programs and mentoring students in advanced computing topics. Before his academic career, he worked extensively in the industry as a senior research engineer and research engineer at multiple companies, gaining hands-on experience in simulation technologies, visual effects, and interactive systems. His professional trajectory reflects a balance between academic scholarship and practical application, with roles that involved designing innovative solutions, leading research teams, and collaborating on both government-funded and industry-driven projects. His combined academic and industrial experience has strengthened his expertise in bridging theoretical research with real-world implementation, enhancing his ability to deliver impactful outcomes in both educational and technological domains.

Research Interest

Prof. Jong-Hyun Kim’s research interests cover a broad and interdisciplinary range of topics, including computer graphics, visual effects, physically based simulation, physics engines, and game physics. He actively explores artificial intelligence techniques for scientific visualization, geometry processing, image processing, and immersive VR/AR experiences. His work often focuses on GPU optimization to achieve real-time performance in complex simulations, enabling practical applications in gaming, virtual reality, and industrial simulations. Additionally, he is interested in human-computer interaction, particularly in developing intuitive interfaces for creative expression and realistic virtual environments. His projects integrate physics-based modeling with AI-driven approaches to address challenges in simulation accuracy, interactivity, and scalability. By combining deep technical expertise with creativity, his research aims to advance the capabilities of simulation and visualization technologies, making them more efficient, accessible, and adaptable for diverse fields ranging from entertainment and education to engineering and healthcare.

Award and Honor

Prof. Jong-Hyun Kim has received numerous awards and honors recognizing his excellence in research, innovation, and academic contributions. His accolades include multiple Best Paper Awards from prestigious conferences such as those organized by the Korea Society of Computer and Information and the Korean Association of Data Science, acknowledging his groundbreaking work in simulations, VR frameworks, AI-driven modeling, and GPU optimization. He has been honored by the Ministry of Science and ICT and the Korean Ministry of Education for his creative and impactful research ideas. His achievements extend beyond academia, with awards recognizing his leadership in industry-academic cooperation and excellence in teaching. These recognitions reflect his sustained contributions to advancing cutting-edge technologies, fostering collaboration between academia and industry, and mentoring future innovators. His consistent recognition at national and professional levels underscores his influence in both research and education, and his ongoing commitment to delivering impactful technological advancements.

Research Skill

Prof. Jong-Hyun Kim possesses advanced research skills in multiple technical domains, including physically based simulation, visual effects, GPU optimization, and complex animation systems. He is proficient in designing real-time interactive environments, implementing physics engines, and integrating artificial intelligence into simulation and visualization frameworks. His expertise includes scientific visualization, geometry processing, VR/AR development, and image processing, enabling him to create innovative solutions that merge creativity with computational precision. He has extensive experience managing large-scale research projects funded by national agencies and industry partners, demonstrating strong project management, team leadership, and cross-disciplinary collaboration skills. His technical abilities are complemented by his capacity to translate theoretical models into practical applications across entertainment, engineering, and scientific research. By combining analytical thinking, problem-solving, and creative design, he continues to push the boundaries of simulation and visualization technologies, contributing significantly to both academic advancements and industry innovation.

Publications Top Notes

Title: A Geometric Approach to Efficient Modeling and Rendering of Opaque Ice With Directional Air Bubbles
Authors: Jong-Hyun Kim
Year: 2025

Title: Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing
Authors: Jong-Hyun Kim; Jung Lee
Year: 2025

Title: Improved Air Mesh Refinement for Accurate Strand-Solid and Self-Collision Handling
Authors: Jong-Hyun Kim
Year: 2025

Title: Neural Network-Based Projective Grid Model for Learning Representation of Surface and Wave Foams
Authors: Jong-Hyun Kim
Year: 2025

Title: Porous Models for Enhanced Representation of Saturated Curly Hairs: Simulation and Learning
Authors: Jong-Hyun Kim; Jung Lee
Year: 2025

Title: A 3D Visual Tool for Analyzing Changes in Hair Volume and Length Caused by Medications
Authors: Jong‐Hyun Kim; Jung Lee; Seungbin Kwon; Minji Jo; Yunjin Hwang; In‐Sook An
Year: 2025

Title: Numerical Dispersed Flow Simulation of Fire-Flake Particle Dynamics and Its Learning Representation
Authors: Jong-Hyun Kim; Jung Lee
Year: 2025

Title: Unified GPU Framework for Simulating Wave Turbulence, Diffusion, and Wrinkling in Fluid-Cloth Interaction
Authors: Eun Su Park; Juyong Lee; In Kyu Park; Jong-Hyun Kim
Year: 2025

Title: Scalable and Rapid Nearest Neighbor Particle Search Using Adaptive Disk Sector
Authors: Jong-Hyun Kim; Shaofeng Xu; Jung Lee
Year: 2025

Title: Depth-of-Field Region Detection and Recognition From a Single Image Using Adaptively Sampled Learning Representation
Authors: Jong-Hyun Kim; Youngbin Kim
Year: 2024

Title: Motion Generation and Analyzing the User’s Arm Muscles via Leap Motion and Its Data-Driven Representations
Authors: Jong-Hyun Kim; Jung Lee; Youngbin Kim
Year: 2024

Title: Visualization of Vector Fields from Density Data Using Moving Least Squares Based on Monte Carlo Method
Authors: Jong-Hyun Kim
Year: 2024

Title: Isoline Tracking in Particle-Based Fluids Using Level-Set Learning Representation
Authors: Jun Yeong Kim; Chang Geun Song; Jung Lee; Jong-Hyun Kim; Jong Wan Lee; Sun-Jeong Kim
Year: 2024

Title: Efficient and Stable Generation of High-Resolution Hair and Fur With ConvNet Using Adaptive Strand Geometry Images
Authors: Jong-Hyun Kim; Jung Lee
Year: 2023

Conclusion

Prof. Jong-Hyun Kim is highly deserving of the Best Researcher Award for his outstanding contributions to cutting-edge research in computer graphics, AI-driven simulation, and immersive technologies, as well as his significant role in bridging academia and industry through impactful collaborative projects. His innovative work has advanced both scientific understanding and practical applications, benefiting diverse sectors and inspiring the next generation of researchers. With a proven track record of excellence, leadership, and innovation, he holds strong potential to make even greater contributions to research and society in the future.

Dibyalekha Nayak | Computer vision | Women Researcher Award

Published on by Computer Vision Awards

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