Kim, B. H., Mirza, S., & Pöpper, C. (2023, November). Extending Browser Extension Fingerprinting to Mobile Devices. In Proceedings of the 22nd Workshop on Privacy in the Electronic Society (pp. 141-146).
Kim, B. H., & Wang, C. Large Language Models for Interpretable Mental Health Diagnosis. In Workshop on Large Language Models and Generative AI for Health at AAAI 2025.
Kim, B. H., Wang, J., & Wang, C. (2025, April). FairQuant: Certifying and Quantifying Fairness of Deep Neural Networks. In Proceedings of the IEEE/ACM 47th International Conference on Software Engineering (pp. 527-539).
Mitchell, J., Kim, B. H., Zhou, C., & Wang, C. (2025, October). Understanding Formal Reasoning Failures in LLMs as Abstract Interpreters. In Proceedings of the 1st ACM SIGPLAN International Workshop on Language Models and Programming Languages (pp. 71-83).
Kim, B. H., Mitchell, J., & Wang, C. (2026, January). Analyzing Fairness of Neural Network Prediction via Counterfactual Dataset Generation. In Northern Lights Deep Learning Conference (pp. 247-262). PMLR.
Talk at UC San Francisco, Department of Testing, San Francisco, California
Tutorial at UC-Berkeley Institute for Testing Science, Berkeley CA, USA
Talk at London School of Testing, London, UK
Conference proceedings talk at Testing Institute of America 2014 Annual Conference, Los Angeles, CA