Bio
I am a postdoctoral researcher at KAIST, currently conducting research at the Embedded Intelligent Systems (EIS) Lab at Yonsei University, where I work with Prof. JeongGil Ko and Prof. Songkuk Kim.
I received my B.S. and Ph.D. degrees from the School of Integrated Technology at Yonsei University under the supervision of Prof. JeongGil Ko.
From August 2024 to February 2025, I was a visiting researcher at Singapore Management University (SMU), working with Prof. Rajesh Krishna Balan, and I continue to collaborate closely with the SMU team.
My research interests broadly lie at the intersection of machine learning and mobile and embedded systems, with a particular focus on mobile and distributed AI, real-world intelligent systems, and AI security.
More specifically, my work explores intelligent healthcare systems, the security and reliability of AI systems, and AI-driven applications for sports science and human performance analysis.
Research Interests
- Efficient and Secure Distributed AI (Federated Learning, On-Device AI)
- Security/Privacy in Intelligent Systems
- On-Device AI for Human Centered Embedded/Mobile Systems and Applications
- Intelligent Systems for Medical and Clinical Systems and Applications
- Evidential and Explainable Artificial Intelligence
- Understanding and Analyzing Neural Networks
I focus on researching diverse areas that grow out of building real-world applications that create new value using AI.
At the core, I'm most interested in designing systems that account for the practical constraints of mobile and embedded devices, and leveraging them to tackle problems in healthcare, mobile health, and sports/performance analytics.
Building on this, I also develop foundational techniques that address the practical challenges that emerge in these settings such as efficiency, robustness, reliability, and privacy-preserving learning and deployment.
This includes developing efficient AI training/inference methodologies that can run under limited computational resources.
At the same time, since mobile AI systems often handle highly sensitive personal data, I also study privacy- and security-oriented defenses as well as emerging attacks.
More broadly, I aim to understand the fundamental principles behind how AI works and, grounded in an understanding of the systems that serve and deploy it, develop effective and efficient solutions to these challenges.
