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Team BruinWeb

Team BruinWeb

We aim to develop a system that combines a reliable code agent with a user simulator to enable interactive, adaptive problem solving. Our approach emphasizes safe behavior while leveraging simulated user feedback for scalable training and evaluation. By integrating expertise in machine learning, software engineering, and human-computer interaction, we aim to build robust, user-aware code agents that balance performance, safety, and usability.

By University of California, Los Angeles
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Team leaders

Ying Li

Third-year PhD candidate at UCLA working on the intersection of agentic AI and formal reasoning to enhance software security and reliability. Published in top-tier security conferences including IEEE S&P, Usenix Security, NDSS, and CCS.

Peiran Wang

First-year PhD student at UCLA working on system security for agentic AI, coding agents, and LLM safety. Extensive industry experience at ByteDance, Baidu, and Microsoft Research. Awarded the CCS Distinguished Paper Award in 2024.

Di Wu

Fourth-year PhD candidate in Computer Science at UCLA working on retrieval-augmented generation and long-term memory for language models, spanning information retrieval and trustworthy NLP. Published at ICML/ACL/ICLR/EMNLP; interned at Meta, Tencent, and AWS Labs.

Team members

Jinghuai Zhang

Third-year PhD candidate at UCLA focusing on trustworthy machine learning. Work published at top-tier security and AI venues including CCS, CVPR, and EMNLP. Interned at Google and ByteDance.

Kunlin Cai

PhD candidate at UCLA focusing on security and privacy in extended reality (XR) and machine learning. Published at top-tier security venues including USENIX Security and NDSS. Recipient of the Amazon Scholar award.

Yixin (Elaine) Wan

PhD student in Computer Science at UCLA. Research focuses on building trustworthy multimodal generative models. Published at ACL/ICLR/EMNLP; interned at Tencent AI Lab and Amazon AGI. Awardee of the Amazon AI fellowship.

Kaiyuan Zhang

Second-year M.S. student in Electrical and Computer Engineering at UCLA. Research focuses on speech tokenization and privacy in audio generation models, developing more intelligent and trustworthy multimodal language models.

Alex Chang

First-year M.S. student in Electrical and Computer Engineering at UCLA. Research interests in secure model deployment and practical applications of machine learning.

Faculty advisors

Yuan Tian

Associate Professor at UCLA. Research focuses on developing novel technologies for the security, privacy, and safety of modern and emerging systems. Awards include Google Research Scholar Award, Okawa Foundation Award, NSF CAREER Award, Facebook Research Award, and Amazon AI Faculty Fellowship.

Jia-Chen Gu

Postdoctoral Researcher in Computer Science at UCLA. Research focuses on natural language processing, specifically retrieval-augmented language models and model editing. Published in premier venues including ACL, EMNLP, and ICLR. Recipient of ACL Best Paper Honorable Mention and DialDoc Best Paper Award.

About the Author
University of California, Los Angeles

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