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

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.

Mrs. Deepthi S | Medical Image Analysis | Best Researcher Award

Publications

Gradient Propagation Based DenseNet121 with ResNet50 Feature Extraction for Lymphoma Classification

  • Author: Srinivasan, D.; Kalaiarasan, C.
    Journal: Journal of The Institution of Engineers (India): Series B
    Year: 2024

Non Hodgkin’s Lymphoma Classification using Improved Predator Optimization Based Densenet121 Model

  • Author: Deepthi S; Dr. M. Chandrasekhar
    Journal: Journal of Electrical Systems
    Year: 2024

Harnessing ResNet50 and DenseNet201 for Enhanced Lymphoma Diagnosis via Feature Extraction

  • Author: Deepthi S; Dr. M. Chandrasekhar
    Journal: Frontiers in Health Informatics
    Year: 2024

An efficient face image retrieval system based on attribute sparse codewords

  • Author: Deepthi S
    Journal: International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES)
    Year: 2016

Prof Dr. Guoping Yan | Biomedical Imaging | Best Researcher Award

Structural reconstruction synthesis of highly luminous water-stable CsPbBr3@CsPb2Br5@DSPE core-shell perovskite nanocrystals for bioimaging, pattering, and LEDs

  • Author: Jiejun Ren, Longyun Liu, Fan Liu, Guoping Yan, Yuhua Wang
    Journal: Journal of Materials Science and Technology
    Year: 2025

Synthesis and property of 1,1,3,3-tetramethylisoindolin-2-yloxyl-containing polythiophene

  • Author: Fan Liu, Yanchun Shen, Guoping Yan
    Journal: Journal of Alloys and Compounds
    Year: 2025

Lead-Doped Cesium Manganese Halide Perovskite Nanocrystals for Light-Emitting Diodes: Room-Temperature Synthesis, Energy Transfer, and Phase Modulating

  • Author: Jiejun Ren, Longyun Liu, Huiping Liu, Guoping Yan, Yuhua Wang
    Journal: ACS Materials Letters
    Year: 2025

Carbonic Anhydrase IX Targeted Polyaspartamide Fluorescent Probes for Tumor Imaging

  • Author: Yu Zhang, Fan Liu, Chuntao Shao, Jun Huang, Guoping Yan
    Journal: International Journal of Nanomedicine
    Year: 2025

Synthesis and Characterization of Sulfonamide-Containing Naphthalimides as Fluorescent Probes

  • Author: Zhiwei Liu, Fan Liu, Chuntao Shao, Guoping Yan, Jiangyu Wu
    Journal: Molecules
    Year: 2024

Dr. Yijie Ning | Medical Image Analysis | Best Researcher Award

Dr. Yijie Ning | Medical Image Analysis | Best Researcher Award

Doctorate at the First Hospital of Shanxi Medical University, China

👨‍🎓 Profiles

Scopus

Publications

NIR-II imaging-based detection of early changes in lower limb perfusion in type 2 diabetes patients without peripheral artery disease

  • Author: Yijie Ning, Jie Hu, Yikun Zhu, Ruijing Zhang, Honglin Dong, et al.
    Journal: Diabetes Research and Clinical Practice
    Year: 2025

Prof. Krishan Kumar | Medical Image Analysis | Best Researcher Award

Publications

Enhancing Transparency and Trust in Brain Tumor Diagnosis: An In-Depth Analysis of Deep Learning and Explainable AI Techniques

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Preprint
    Year: 2025

Machine Learning for Brain Tumor Classification: Evaluating Feature Extraction and Algorithm Efficiency

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Discover Artificial Intelligence
    Year: 2024

Explainable AI in Brain Tumor Diagnosis: A Critical Review of ML and DL Techniques

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Preprint
    Year: 2024

Recent Advancements in Grad-CAM and Variants: Enhancing Brain Tumor Detection, Segmentation, and Classification

  • Authors: Krishan Kumar, Kiran Jyoti
    Journal: Preprint
    Year: 2024

A Comparative Analysis of Static and Dynamic Java Bytecode Watermarking Algorithms

  • Authors: Krishan Kumar, Prabhpreet Kaur
    Journal: Advances in Intelligent Systems and Computing
    Year: 2019

Prof. Zhitao Xiao | Medical Image Analysis | Best Researcher Award

Prof. Zhitao Xiao | Medical Image Analysis | Best Researcher Award

School of Life Sciences of Tiangong University, China

👨‍🎓 Profiles

Scopus

Orcid

Publications

MSTNet: Multi-scale spatial-aware transformer with multi-instance learning for diabetic retinopathy classification

  • Author: X. Wei, Xin; Y. Liu, Yanbei; F. Zhang, Fang; X. Cao, Xiangyu; Z. Xiao, Zhitao
    Journal: Medical Image Analysis
    Year: 2025

A Deep Learning-Based Modeling Method for Phase-Free Near-Field Scanning Measurement

  • Author: S. Zhao, Shuli; J. Wu, Jianfei; Y. Song, Yang; L. Chen, Ledong; Z. Xiao, Zhitao
    Journal: IEEE Transactions on Antennas and Propagation
    Year: 2025

Stripe Pooling and Vessel-Constraint Network for Fundus Image Artery /Vein Classification

  • Author: Z. Xiao, Zhitao; X. Peng, Xinwen; Y. Liu, Yanbei; F. Zhang, Fang; W. Wang, Wen
    Journal: Chinese Journal of Biomedical Engineering
    Year: 2024

Diabetic Retinopathy Segmentation Using Dense Dilated Attention Pyramid and Multi-Scale Features

  • Author: Z. Wang, Zhilu; Y. Chi, Yue; Y. Zhou, Yatong; Z. Xiao, Zhitao; S. Wang, Shaoqi
    Journal: Chinese Journal of Medical Physics
    Year: 2024

AGT: Enhancing Many-Body Interactions in Material Property Prediction

  • Author: L. Geng, Lei; Y. Niu, Yaxi; Z. Xiao, Zhitao; H. Yin, Huaqing
    Journal: Computational Materials Science
    Year: 2024

Ms. Yang Yuan | Medical Image Analysis | Best Researcher Award

Ms. Yang Yuan | Medical Image Analysis | Best Researcher Award

Chongqing University of Technology, China

👨‍🎓 Profiles

Scopus

Orcid

Publications

Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation

  • Authors: H. Liu, Y. Yuan, P. Ren, C. Song, F. Luo.
    Journal: Computers, Materials & Continua
    Year: 2025

Prof Dr. Yunyoung Nam | Medical Image Analysis | Best Researcher Award

Publications

A Novel Approach for High-Resolution Coastal Areas and Land Use Recognition from Remote Sensing Images based on Multimodal Network-Level Fusion of SRAN3 and Lightweight Four Encoders ViT

  • Authors: M.K. Bhatti, Muhammad Kashif; M.A. Khan, Muhammad Attique; S. Shaheen, Saima; S.A. Algamdi, Shabbab Ali; Y. Nam, Yunyoung
    Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    Year: 2025

Analysis of Near-Fall Detection Method Utilizing Dynamic Motion Images and Transfer Learning

  • Authors: J. Kim, Jungyeon; N. Mat, Nab; C. Kim, Chomyong; S. Jeon, Seob; Y. Nam, Yunyoung
    Journal: IEEE Access
    Year: 2025

Cooperative PPG/ECG Wearable System for Atrial Fibrillation Diagnosis

  • Authors: Y. Lee, Yonbin; S. Lee, Soyoung; S. Kim, Sang-kyu; Y. Nam, Yunyoung; J. Lee, Jinseok
    Journal: IEEE Sensors Journal
    Year: 2025

Energy-Efficient Discrete Cosine Transform Architecture Using Reversible Logic for IoT-Enabled Consumer Electronics

  • Authors: M. Awais, Muhammad; W. Khan, Wilayat; T. Akram, Tallha; Y. Nam, Yunyoung
    Journal: IEEE Access
    Year: 2025

Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI

  • Authors: I. Jeon, Insoo; M. Kim, Minjoong; D. So, Dayeong; J. Kim, Joungmin; J. Moon, Jihoon
    Journal: Diagnostics
    Year: 2024

Dr. Sajid Ullah Khan | Medical Image Analysis | Best Researcher Award

Dr. Sajid Ullah Khan | Medical Image Analysis | Best Researcher Award

Doctorate at Prince Sattam Bin Abdulaziz University, Saudi Arabia

👨‍🎓 Profiles

Scopus

Orcid

Google Scholar

Publications

Chat-GPT; validating Technology Acceptance Model (TAM) in education sector via ubiquitous learning mechanism

  • Authors: Naveed Saif, Sajid Ullah Khan, Imrab Shaheen, Faiz Abdullah ALotaibi, Mrim M Alnfiai, Mohammad Arif
  • Journal: Computers in Human Behavior
  • Year: 2024

Energy-efficient routing protocols for UWSNs: A comprehensive review of taxonomy, challenges, opportunities, future research directions, and machine learning perspectives

  • Authors: Sajid Ullah Khan, Zahid Ulalh Khan, Mohammed Alkhowaiter, Javed Khan, Shahid Ullah
  • Journal: Journal of King Saud University-Computer and Information Sciences
  • Year: 2024

Multimodal medical image fusion towards future research: A review

  • Authors: Sajid Ullah Khan, Mir Ahmad Khan, Muhammad Azhar, Faheem Khan, Youngmoon Lee, Muhammad Javed
  • Journal: Journal of King Saud University-Computer and Information Sciences
  • Year: 2023

Historical text image enhancement using image scaling and generative adversarial networks

  • Authors: Sajid Ullah Khan, Imdad Ullah, Faheem Khan, Youngmoon Lee, Shahid Ullah
  • Journal: Sensors
  • Year: 2023

A novel CT image de-noising and fusion based deep learning network to screen for disease (COVID-19)

  • Authors: Sajid Ullah Khan, Imdad Ullah, Najeeb Ullah, Sajid Shah, Mohammed El Affendi, Bumshik Lee
  • Journal: Scientific Reports
  • Year: 2023

Mr. Shuhuan Wang | Medical Image Analysis | Best Researcher Award

Mr. Shuhuan Wang | Medical Image Analysis | Best Researcher Award

Shuhuan Wang at Northeastern University, China

👨‍🎓 Profiles

Scopus

Orcid

Google Scholar

Publications

DP-CLAM: A weakly supervised benign-malignant classification study based on dual-angle scanning ultrasound images of thyroid nodules

  • Authors: Wang, S., Zhang, S., Liao, L., Huang, L., Ma, H.
  • Journal: Medical Engineering and Physics
  • Year: 2025

A model fusion method based DAT-DenseNet for classification and diagnosis of aortic dissection

  • Authors: He, L., Wang, S., Liu, R., Ma, H., Wang, X.
  • Journal: Physical and Engineering Sciences in Medicine
  • Year: 2024

SRT: Swin-residual transformer for benign and malignant nodules classification in thyroid ultrasound images

  • Authors: Huang, L., Xu, Y., Wang, S., Sang, L., Ma, H.
  • Journal: Medical Engineering and Physics
  • Year: 2024

DPAM-PSPNet: Ultrasonic image segmentation of thyroid nodule based on dual-path attention mechanism

  • Authors: Wang, S., Li, Z., Liao, L., Huang, L., Ma, H.
  • Journal: Physics in Medicine and Biology
  • Year: 2023