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.

Rania Hamdani | Computer Science and Artificial Intelligence | Best Researcher Award

Ms. Rania Hamdani | Computer Science and Artificial Intelligence | Best Researcher Award

AE3S | University of luxembourg | Luxembourg 

Rania Hamdani is a dynamic early-career research scientist specializing in software engineering, data management, and cloud architecture for Industry 5.0 applications. Currently based at the University of Luxembourg, she is engaged in advanced research on integrating heterogeneous data sources and optimizing decision-making in cloud-based systems. With a strong foundation in software development and operational research, Rania has already co-authored three research papers in Cloud-Edge AI and ontology-driven knowledge management. Her diverse technical skills span Python, Java, Docker, Kubernetes, and Azure DevOps, and she has gained international experience through roles in Luxembourg, Canada, France, and Tunisia. Passionate about both academic and applied innovation, she has contributed to multiple interdisciplinary projects in AI, human-computer interaction, and intelligent systems. Rania is also active in professional communities such as IEEE and youth science associations, reflecting her commitment to collaborative growth and scientific outreach.

Professional Profile 

Education Background

Rania Hamdani has a strong academic foundation rooted in engineering and scientific rigor. She earned her Engineering Degree in Software Engineering from the National Higher School of Engineers of Tunis (ENSIT) between 2021 and 2024, where she specialized in Advanced Design, Service-Oriented Architecture, Object-Oriented Programming, Database Management, and Operational Research. Prior to that, she completed a Preparatory Cycle for Engineering Studies at the Preparatory Institute for Engineering Studies of Tunis (2019–2021), focusing intensively on mathematics, physics, and core technology subjects—a rigorous program designed to prepare students for elite engineering schools. Rania also holds a Baccalaureate in Mathematics from Pioneer High School Bourguiba Tunis, where she graduated with distinction (Very Good) in 2019. This academic journey has laid a solid foundation for her multidisciplinary research and professional growth in software and data sciences.

Professional Experience 

Rania Hamdani has developed a rich and diverse professional portfolio across academia and industry, with hands-on experience in software engineering, research, and cloud-based technologies. She is currently a Research Scientist at the University of Luxembourg (since November 2024), where she focuses on optimizing decision-making processes in cloud environments through advanced data integration techniques. Prior to this, she served as a Research Intern at the same institution (May to October 2024), contributing to projects in Ontology-Driven Knowledge Management and Cloud-Edge AI, resulting in three published papers. Alongside her academic work, Rania worked as a Part-Time Software Engineer at CareerBoosts in Canada (2021–2025), where she honed her skills in DevOps, data analysis, test automation, and backend development using tools like Python, Docker, and Kubernetes. Her earlier internships include roles at Qodexia (France), Sagemcom (Tunisia), and Tunisie Telecom, where she worked on smart recruitment platforms, employee management systems, and server monitoring tools using full-stack technologies such as SpringBoot, Angular, and PostgreSQL. This blend of research and industry experience positions Rania as a versatile and forward-thinking technology professional.

Research Interests of Rania Hamdani

Rania Hamdani’s research interests lie at the intersection of software engineering, operational research, data integration, and cloud-edge intelligence, with a strong orientation toward Industry 5.0 applications. She is particularly passionate about developing intelligent systems that enhance decision-making in cloud-based and distributed environments, leveraging AI, machine learning, and ontology-driven knowledge frameworks. Her work focuses on enabling seamless management of heterogeneous data sources, scalable architectures, and adaptive human-computer interaction (HCI) systems. Rania is also deeply engaged in exploring Cloud-Edge AI ecosystems, recommender systems, and automation pipelines using modern tools like Docker, Kubernetes, TensorFlow, and Neo4j. Her multidisciplinary approach reflects a vision for integrating research-driven insights with real-world industrial challenges, making her contributions both academically valuable and practically impactful.

Awards and Honors of Rania Hamdani

While still in the early stages of her research career, Rania Hamdani has demonstrated exceptional academic and technical promise. She graduated with a “Very Good” distinction in her Baccalaureate in Mathematics from the prestigious Pioneer High School Bourguiba in Tunis, reflecting her consistent academic excellence. Rania has also earned multiple professional certifications from Microsoft, including Azure Fundamentals, Azure Data Fundamentals, Azure AI Fundamentals, and Azure Security, Compliance, and Identity Fundamentals, showcasing her dedication to staying at the forefront of cloud and AI technologies. Though formal research awards or honors are not yet listed, her early publications, research contributions, and international internships highlight a trajectory poised for future recognition in both academic and industry spheres.

Publications Top Noted

Title: Adaptive human‑computer interaction for Industry 5.0: A novel concept, with comprehensive review and empirical validation
Year: 2025

Conclusion

Rania Hamdani is highly suitable for the Best Emerging Researcher or Young Researcher Award category. She has excellent technical skills, promising early-stage research output, international exposure, and a forward-looking vision in areas like Industry 5.0, cloud-edge intelligence, and AI-based decision systems. While still building her publication track record and academic leadership, her current trajectory shows strong promise for future impactful contributions to scientific and industrial domains.

Luis Pastor Sanchez-Fernandez | Computer Science and Artificial Intelligence | Cross-disciplinary Excellence Award

Prof. Dr. Luis Pastor Sanchez-Fernandez | Computer Science and Artificial Intelligence | Cross-disciplinary Excellence Award

Senior Researcher at Center for Computing Research Instituto Politecncico Nacional, Mexico

Luis Pastor Sánchez-Fernández is a Full Professor at the Computer Research Center of the National Polytechnic Institute (IPN) in Mexico City, with a PhD in Technical Sciences from the José Antonio Echeverría Polytechnic Institute (CUJAE), Havana (1998). A distinguished researcher and educator, he has been a member of Mexico’s National System of Researchers since 2007 (currently Level II). His work spans multiple disciplines, including biomechanics, bioinformatics, environmental acoustics, signal processing, expert systems, and intelligent automation. He has supervised over 13 doctoral and 46 master’s students, many of whom received honors or were inducted into national research systems. Dr. Sánchez-Fernández has led several research groups and CONACYT-funded projects, notably designing the Environmental Noise Monitoring System for the Historic Center of Mexico City. A recipient of the 2014 IPN Applied Research Award, he is also an accomplished keynote speaker, reviewer for high-impact journals, and advocate for interdisciplinary and socially impactful research.

Professional Profile 

🎓 Education of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández holds a PhD in Technical Sciences from the prestigious José Antonio Echeverría Polytechnic Institute (CUJAE) in Havana, Cuba, awarded in 1998. His doctoral education laid a strong interdisciplinary foundation, combining elements of engineering, computer science, and applied research. This academic background has been instrumental in shaping his cross-disciplinary research career, allowing him to contribute significantly to fields such as biomechanics, signal processing, and intelligent systems.

💼 Professional Experience of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández has served as a Full Professor at the Computer Research Center of the National Polytechnic Institute (IPN), Mexico City, since 2000, where he has been a key figure in advancing interdisciplinary scientific research and technological development. With over two decades of academic and research leadership, he has directed multiple research groups in bioinformatics and intelligent measurement systems, supervised numerous postgraduate theses, and mentored future leaders in science. His expertise spans diverse fields including biomechanics, environmental acoustics, expert systems, and automation. He has also played critical roles as a project leader for national research initiatives funded by CONACYT, and as an advisor and evaluator of scientific proposals. His contributions extend beyond academia into societal impact projects, such as the Environmental Noise Monitoring System for Mexico City, solidifying his reputation as a cross-disciplinary innovator and research leader.

🔬 Research Interests of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández’s research interests lie at the intersection of engineering, computer science, health sciences, and environmental studies, reflecting his strong cross-disciplinary approach. He focuses on the biomechanical analysis of patients with Parkinson’s disease, exploring computational and signal-based methods to improve medical diagnostics and rehabilitation. He is also deeply engaged in environmental acoustics, developing noise indicators and acoustic indices to assess and mitigate the harmful effects of urban noise pollution. His work extends into signal pattern recognition, expert systems, virtual instrumentation, and the design of intelligent systems for automation. Additionally, he has a sustained interest in bioinformatics, leading research groups that develop advanced computational tools for biological data analysis. His research consistently integrates theory and practical application, addressing real-world problems through innovative, multidisciplinary solutions.

🏅 Awards and Honors of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández has received several prestigious awards and honors in recognition of his outstanding contributions to interdisciplinary research and academic mentorship. He was honored with the Applied Research Award by the National Polytechnic Institute (IPN) in 2014, acknowledging his impactful work that bridges scientific innovation and real-world application. As a dedicated mentor, he has received two thesis advisor awards from IPN, celebrating the excellence of his supervised postgraduate research. Many of his doctoral and master’s students have earned honorable mentions and Cum Laude distinctions, with several joining Mexico’s National System of Researchers—a testament to his role in cultivating high-caliber scholars. Since 2007, he has held Level II membership in the National System of Researchers of Mexico (SNI), further solidifying his reputation as a leader in cross-disciplinary scientific advancement.

🧾 Conclusion

The candidate demonstrates exceptional cross-disciplinary impact, strong leadership, and a deep commitment to advancing science at the intersection of multiple fields. His contributions in biomechanics, environmental monitoring, signal processing, and intelligent systems showcase not only depth but also the integration of diverse disciplines to address complex societal challenges. He is an ideal nominee for the Cross-disciplinary Excellence Award. Minor enhancements in visibility, global partnerships, and documentation of publications would make his case even more compelling.

📚 Publications by Luis Pastor Sánchez-Fernández

1.Title: Dataset for Gait Assessment in Parkinson’s Disease Patients

  • Authors: (Not provided)
  • Year: (Not explicitly listed)
  • Type: Data Paper – Open Access
  • Citations: 0

2.Title: Innovations and Technological Advances in Healthcare Remote Monitoring Systems for the Elderly and Vulnerable People: A Scoping Review

  • Authors: (Not fully listed)
  • Year: (Not explicitly listed)
  • Type: Review – Open Access
  • Citations: 0

3.Title: Computer Model for Gait Assessments in Parkinson’s Patients Using a Fuzzy Inference Model and Inertial Sensors

  • Authors: (Not fully listed)
  • Journal: Artificial Intelligence in Medicine
  • Year: 2025
  • Citations: 2

4.Title: Motion Smoothness Analysis of the Gait Cycle, Segmented by Stride and Associated with the Inertial Sensors’ Locations

  • Authors: (Not fully listed)
  • Journal: Sensors
  • Year: 2025
  • Type: Article – Open Access
  • Citations: 1

5.Title: Network Long-Term Evolution Quality of Service Assessment Using a Weighted Fuzzy Inference System

  • Authors: (Not fully listed)
  • Journal: Mathematics
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 0

6.Title: Biomechanics of Parkinson’s Disease with Systems Based on Expert Knowledge and Machine Learning: A Scoping Review

  • Authors: (Not listed)
  • Year: (Not explicitly listed)
  • Type: Review – Open Access
  • Citations: 0

7.Title: An Integrated Approach to the Regional Estimation of Soil Moisture

  • Authors: (Not fully listed)
  • Journal: Hydrology
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 0

8.Title: A Fuzzy Inference Model for Evaluating Data Transfer in LTE Mobile Networks via Crowdsourced Data

  • Authors: (Not fully listed)
  • Journal: Computación y Sistemas
  • Year: 2024
  • Type: Article
  • Citations: 1

9.Title: Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation

  • Authors: (Not fully listed)
  • Journal: Mathematics
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 4