International Conference on 2026 PyGeek

• CEO, Marketian (Current)
• Adjunct Professor, Graduate School of Medicine, CHA University (Current)
• Former Chief Executive of Management Division, Kwangdong Hospital
• Former Vice President, K-DOC
• Former GL&S Korea Manager, Pfizer Korea
• Former Senior Consultant, Gallup Korea Consulting
• Former Team Leader, Healthcare Information Systems Development Team, Hallym University Medical Center

• M.Ph.D. in Medicine, CHA University
• M.M.S. in Marketing, University of Colorado Denver
• M.B.A. in Accounting, Dongguk University

This keynote examines the fundamental challenges and opportunities facing computer science education and software professionals amid the rapid paradigm shift from the analog era through digital transformation to the emerging Intelligence Economy. Drawing parallels with the rise and decline of past industries and academic disciplines, the talk explores how the widespread adoption of Generative AI has significantly reduced the scarcity value of programming syntax itself. As the world transitions from the 20th-century paradigm of oil refining to the 21st-century era of “intelligence refining” powered by computing resources, developers must evolve beyond the role of coders to become architects of systems and definers of problems. The lecture highlights how value creation is increasingly driven not by writing code, but by identifying meaningful problems, designing intelligent systems, and orchestrating AI capabilities. Through practical industry cases and real-world examples, the speaker will present five actionable principles that professors of artificial intelligence, computer science students, and industry professionals can immediately adopt to secure competitive advantages in the age of AI-driven transformation.

• Motorola Korea Ltd. Korea, Computer Integrated Manufacturing Engineer in Advanced Technology Research and Development
• HQ of Motorola Inc., Schaumburg Illinois, Senior Software Engineer in Networks and Enterprises.
• Chairman of the Dept. of Software and Communications Engineering, Vice President of Graduate School, and Director of Planning & Management Office at Hongik University, Korea, where he is currently a professor since 2007.
• Adjunct professor of TDTU, Vietnam from 2023.
• IEEE Senior Member and is serving as Associate Editors of IEEE Access, Telecommunication Networks, IEIE SPC, and Journal of the Institute of Electrics and Information Engineers.
• Guest Editors of special issues of IEEE IoT, IEEE OJCS, IEEE Access, International Journal of Distributed Sensor Networks, Sensors, Applied Science, and Electronics. He served as an organizing chair for ICGHIT 2024 & 2025.

• B.S. degree in Electrical Engineering, In-Ha University
• M.S. and Ph.D. in Electrical and Computer Engineering, University of Florida

The explosive growth of 6G networks and the Internet of Things (IoT) has ushered in the era of 'Edge Intelligence,' shifting data processing from centralized clouds to the network edge. However, conventional edge AI systems still rely on static models and lack the autonomy required to dynamically adapt to rapidly changing wireless environments. This keynote presentation introduces a revolutionary paradigm to overcome these limitations: 'Agentic AI' and its implementation process, Agentification. Agentification represents a profound shift that transforms passive edge devices and network nodes into autonomous agents capable of perceiving multi-modal environments (Perception), understanding complex contexts (Reasoning), and executing self-directed workflows to achieve specific goals. In this talk, we delve into the four core pillars for building practical and scalable Agentic AI systems within resource-constrained 6G edge environments: Compactness, Efficiency, Knowledge & Reasoning, and Migration. Furthermore, we showcase how agentified edge intelligence maximizes network efficiency and operational autonomy through some real-world case studies. Ultimately, this keynote envisions a future where edge computing transcends merely running pre-trained AI models to becoming a unified, self-evolving system-Edge General Intelligence-offering deep insights into the key enabling technologies, structural designs, and future research directions for next-generation autonomous networks.