Jaehyun Chung| Computer Science and Artificial Intelligence | Best Researcher Award

Mr. Jaehyun Chung| Computer Science and Artificial Intelligence | Best Researcher Award

Computer Science and Artificial Intelligence | Korea University | South Korea

Jaehyun Chung is a highly promising M.S. student at Korea University’s Artificial Intelligence and Mobility Laboratory, specializing in Generative AI, Reinforcement Learning, and Quantum AI applications. His research focuses on autonomous systems, AI-based mobility, defense technologies, and intelligent control, reflected in his involvement in over ten major R&D projects funded by prestigious Korean institutions. He has co-authored several high-impact journal articles and conference papers, including works published or under review in IEEE Transactions and ACM venues, and has earned multiple student paper awards, such as the IEEE Seoul Section Bronze Paper Award. Jaehyun demonstrates strong interdisciplinary capability, applying advanced AI techniques to fields as diverse as torpedo evasion, space rocket stabilization, and stock market prediction. Although early in his academic career, his rapid research output, national recognition, and contributions to innovative, real-world AI applications position him as an outstanding young researcher with exceptional potential for future impact.

Professional Profile 

Educational 

Jaehyun Chung pursued both his undergraduate and graduate studies at Korea University, one of South Korea’s leading institutions. He earned his Bachelor of Science (B.S.) in Electrical and Computer Engineering from the College of Engineering, completing the program between March 2017 and August 2023. Following his undergraduate success, he continued at Korea University to pursue a Master of Science (M.S.) in Electrical and Computer Engineering, starting in September 2023, where he is currently engaged in advanced research in Artificial Intelligence and Mobility. His academic path reflects a strong and consistent focus on engineering and cutting-edge AI technologies.

Professional Experience 

Jaehyun Chung is currently serving as a Research Assistant at the Artificial Intelligence and Mobility Laboratory at Korea University since September 2023, under the guidance of Professor Joongheon Kim. In this role, he actively contributes to a wide range of advanced R&D projects focused on AI-based autonomous systems, reinforcement learning, and quantum AI technologies. His professional experience includes hands-on involvement in nationally funded initiatives such as the Quantum Hyper-Driving Project, AI Bots Collaborative Platform, and Learning-Based Swarm Mission Planning Algorithms, among others. Jaehyun’s work spans across various sectors including defense, mobility, construction, and education, highlighting his ability to apply AI innovations to real-world challenges through practical, cross-disciplinary research collaborations.

Research Interests 

Jaehyun Chung’s research interests lie at the intersection of Artificial Intelligence, Autonomous Systems, and Quantum Computing. He is particularly focused on Generative AI technologies, including Transformer-based architectures, and their application in dynamic environments. A key area of his work involves AI-based Autonomous Control, where he utilizes advanced Reinforcement Learning techniques to optimize decision-making in systems such as autonomous vehicles, robotic platforms, and defense mechanisms. Additionally, his growing involvement in Quantum Reinforcement Learning and Federated Learning reflects a forward-looking approach to building scalable and intelligent systems. His research is deeply interdisciplinary, targeting real-world problems in mobility, finance, aerospace, and military applications through the lens of cutting-edge AI innovation.

Awards and Honors 

Jaehyun Chung has received several prestigious awards recognizing his innovation and excellence in research at an early stage in his academic career. In December 2024, he was honored with the IEEE Seoul Section Best Student Bronze Paper Award for his impactful work on stock prediction using correlation graph-based proximal policy optimization. In November 2024, he received the Outstanding Paper Award from the Korean Institute of Communications and Information Sciences (KICS) for his research on reinforcement learning-based countermeasure tactics against torpedo threats. Additionally, he earned another Bronze Paper Award at the IEEE Seoul Section Student Paper Contest in December 2023 for developing reinforcement learning strategies for aircraft taxi routing. These accolades reflect Jaehyun’s strong analytical skills, innovative thinking, and significant contributions to the fields of AI and autonomous control.

 Publications 

Title: Joint Quantum Reinforcement Learning and Stabilized Control for Spatio-Temporal Coordination in Metaverse
Authors: S. Park, J. Chung, C. Park, S. Jung, M. Choi, S. Cho, J. Kim
Year: 2024
Cited by: 19

Title: Realizing Stabilized Landing for Computation-Limited Reusable Rockets: A Quantum Reinforcement Learning Approach
Year: 2024
Cited by: 17

Title: Quantum Multi-Agent Reinforcement Learning for Cooperative Mobile Access in Space-Air-Ground Integrated Networks
Authors: G. S. Kim, Y. Cho, J. Chung, S. Park, S. Jung, Z. Han, J. Kim
Year: 2024
Cited by: 4

Title: DDPG-based Deep Reinforcement Learning Tactics for Defending Torpedo Attacks
Authors: J. Chung, C. Im, J. Choi, Y. Yoon, S. Park
Year: 2024
Cited by: 1

Title: Correlation-Assisted Spatio-Temporal Reinforcement Learning for Stock Revenue Maximization
Year: 2025

Title: Multi-Modal LLM-Based Fully-Automated Training Dataset Generation Software Platform for Mathematics Education
Year: 2025

Title: Trends in Reinforcement Learning Methods for Stock Prediction
Year: 2024

Conclusion 

Jaehyun Chung is an exceptionally strong early-career researcher who demonstrates intellectual depth, research versatility, and practical relevance across AI domains. He possesses all the qualities sought in a Best Researcher Award.

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Shuai Cao | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profile 

Orcid

Education

Dr. Shuai Cao’s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014–2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017–2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization scheduling—work closely aligned with his master’s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projects—including “Research and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturing” (Project Code: 2130218003022) and the “Foshan Science and Technology Innovation Team Project” (Project Code: FS0AA-KJ919-4402-0060)—he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Cao’s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes