About
I am a 5th year Ph.D. candidate in Computer Science at the University of Southern California (USC), advised by Dr. Chao Wang.
My research lies at the intersection of Software Engineering (SE) and Artificial Intelligence (AI). My work spans both SE for AI – developing verification-guided methods for building reliable and responsible AI systems – and AI for SE – leveraging AI and LLMs to improve program analysis and verification. My research is complemented by industry experience in AI agents, reliable AI, and systems infrastructure at Google, Meta, and Amazon. Please refer to my industry CV and academic CV for more information.
Prior to joining USC, I graduated cum laude with a B.S. in Computer Science from New York University Abu Dhabi (NYUAD), where I worked on browser security under Dr. Christina Pöpper. Outside of work, I enjoy reading, clarinet, and tennis!
Recent News
09/2026: Serving as Program Committee for Fairness Workshop 2027 — I am serving as Program Committee for Fairness Workshop 2027, a SANER 2027 workshop on everything related to fairness. Our CFP is open, with the registration deadline in October!
08/2026: Fall Internship at Google — I am working as a Software Engineering Intern with the Data Center Orchestration team at Google for the fall in Pittsburgh, PA! I will be working closely with Dr. Anuj Gautam.
07/2026: Accepted as Shadow PC member for ICSE 2027 — I am serving as a Shadow Program Committee member for ICSE 2027. This is a great opportunity to contribute to the program and get hands-on experience with the review process more extensively and independently.
06/2026: Selected to Give Talk at HARMONY 2026 — I have been selected to give a talk about my work on LLMs for mental health diagnosis at HARMONY 2026, an IEEE/ACM CHASE 2026 workshop around AI and mental health. Happy to be speaking at a venue I helped organize!
05/2026: Summer Internship at Meta — I am working as a Software Engineering Intern with the Distributed Tracing team at Meta for the summer in Menlo Park, CA! I will be working closely with Dr. Kunal Mahajan.
Publications
Analyzing Fairness of Neural Network Prediction via Counterfactual Dataset Generation: Brian Hyeongseok Kim, Jacqueline L. Mitchell, and Chao Wang. Northern Lights Deep Learning Conference (NLDL), 2026.
Understanding Formal Reasoning Failures in LLMs as Abstract Interpreters: Jacqueline L. Mitchell, Brian Hyeongseok Kim, Chenyu Zhou, and Chao Wang. Workshop on Language Models and Programming Languages at SPLASH (LMPL), 2025.
FairQuant: Certifying and Quantifying Fairness of Deep Neural Networks: Brian Hyeongseok Kim, Jingbo Wang, and Chao Wang. IEEE/ACM International Conference on Software Engineering (ICSE), 2025.
Large Language Models for Interpretable Mental Health Diagnosis: Brian Hyeongseok Kim and Chao Wang. Workshop on Large Language Models and Generative AI for Health at AAAI (GenAI4Health), 2025.
Extending Browser Extension Fingerprinting to Mobile Devices: Brian Hyeongseok Kim, Shujaat Mirza, and Christina Pöpper. Workshop on Privacy in the Electronic Society at CCS (WPES), 2023.
Personal
- I am actively running a book review / reflection blog. Let me know if you have any book recommendations.
- I have lived in 6 different countries and have documented my past experiences here and there.
- I am learning Spanish and Tagalog. Help me practice, por favor / pakiusap!
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