About
Hi! I’m an incoming Ph.D. student in Computer Science at Texas A&M University, advised by Prof. Zhengzhong Tu, starting in Fall 2026. Currently, I am working as a Research Intern in the Mathematical and Computer Science (MCS) Division at Argonne National Laboratory, where I work with Dr. Kibaek Kim.
Previously, I earned my master’s degree in Electrical Engineering at the University of Southern California, where I closely worked with Prof. Salman Avestimehr and Prof. Sai Praneeth Karimireddy, and collaborated with Prof. Sunwoo Lee. I received my B.S. in Electronic Engineering from Sogang University, where I worked with Prof. Hongseok Kim.
My research interests broadly span Generative AI, Agentic AI, Multimodal AI, and Trustworthy AI, with the goal of building practical AI systems that can be deployed in real-world settings. Rather than treating these areas as separate directions, I am especially interested in their intersection: how capable generative and agentic systems can reason over multimodal information while remaining reliable, interpretable, and safe.
My research experience includes:
- Trustworthy LLMs: LLM Uncertainty Quantification, Hallucination Detection, Representation Analysis and Control
- Efficient Machine Learning: Federated Learning, Distributed Systems, Parameter-Efficient Fine-Tuning (PEFT), Gradient-based Importance Estimation
Work Experience
Publications
News
- Jun 08, 2026 - I started my summer internship at Argonne National Laboratory, where I am working on asynchronous federated learning.
- May 15, 2026 - I graduated from the University of Southern California with my M.S. in Electrical Engineering and was selected as an MS Honors Fellow.
- May 07, 2026 - Honored to receive the Outstanding Academic Achievement Award from the Ming Hsieh Department of Electrical and Computer Engineering at USC, awarded to one master's student in the department.
- Apr 30, 2026 - Our paper, Uncertainty Quantification for Hallucination Detection in Large Language Models: Foundations, Methodology, and Future Directions, was accepted to IEEE BITS the Information Theory Magazine.
- Jan 25, 2026 - Our paper Uncertainty as Feature Gaps: Epistemic Uncertainty Quantification of LLMs in Contextual Question-Answering got accepted to ICLR 2026.
- Nov 07, 2025 - My first first-author paper GEM: A Scale-Aware and Distribution-Sensitive Sparse Fine-Tuning Framework for Effective Downstream Adaptation was accepted to AAAI 2026.
- Oct 31, 2025 - Honored to receive the Best Poster Award at the USC ECE 15th Annual Research Festival, among 110 participating teams.
- Sep 18, 2025 - Our paper Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning got accepted to NeurIPS 2025.
- Sep 10, 2025 - Our TruthTorchLM paper got accepted to EMNLP 2025 System Demonstrations.
- May 15, 2025 - Our paper Reconsidering LLM Uncertainty Estimation Methods in the Wild was accepted to ACL 2025.
Selected Honors & Awards
Education
Contact
Feel free to contact me at kangsung@usc.edu or connect via LinkedIn. My CV is available here.