I am a second year PhD student at UT Austin ECE under the supervision of Prof. Haris Vikalo. My research develops efficient, trustworthy AI for decentralized, resource-constrained systems. I’m interested in designing methods that preserve reliability under tight compute/memory/latency budgets, device heterogeneity, and non-stationary deployments. To view the list of papers I've contributed to, please visit the publication section.

Previously, I completed my master's studies at Advanced Radio Technology Lab, KAIST, where I also earned my Bachelor's degree in Electrical Engineering.

Current research interests

• LLM quantization & speculative decoding for fast, resource-aware inference
• Continual learning in collaborative, privacy-preserving environments
• Task offloading and model onloading for hierarchical edge AI inference

News

09/2025: One paper on continual federated learning is now on ArXiv!

08/2025: One paper on joint model onloading and offloading is now on ArXiv!

07/2025: Our paper GeFL: Model-Agnostic Federated Learning with Generative Models got accepted to IEEE Transactions on Mobile Computing!

02/2025: Our paper NeFL: Nested Model Scaling for Federated Learning with System Heterogeneous Clients was accepted to IEEE Transactions on Mobile Computing!

08/2024: Start my PhD in ECE at UT Austin

10/2023: Paper on conformal prediction was accepted NeurIPS 2023 workshop!

02/2022: Started my MS in EE at KAIST

02/2022: Earned Summa Cum Laude honors from my Bachelor's degree at KAIST