Yuangang Li

Yuangang Li

PhD Student at UCI

Biography

Hi ๐Ÿ‘‹! I am Yuangang Li, a PhD student at the Donald Bren School of Information and Computer Sciences, University of California, Irvine, where I am fortunate to be advised by Prof. Cristina (Crista) Lopes. My research focuses on trustworthy LLMs, LLM reasoning, and scalable AI/agent evaluation, with a particular interest in LLM transparency and code generation explainability.

Currently, I am a Machine Learning Research Intern at Kilby Labs, Texas Instruments, on the Generative AI team, working on coding agents and agentic AI systems for complex task automation. I am also a research collaborator with the Stanford team behind Terminal-Bench and Harbor, and a Core Contributor to the open-source agent evaluation ecosystem.

Before my PhD study at UCI, I spent wonderful years at the University of Southern California, completing my Masterโ€™s degree and working with Prof. Yue Zhao. During that time, I also had the pleasure of collaborating with Prof. Xiyang Hu and Prof. Jiechao Gao.

Interests
  • Trustworthy AI & Large Language Models (LLMs)
  • Coding Agent
  • Agent Evaluation & Optimization
  • AI Safety

News

  • [Jun 2026] Co-authored "Agents' Last Exam" โ€” a community-built benchmark of 1,000+ economically valuable, long-horizon agent tasks (one of 300+ contributors).
  • [Jun 2026] Two new preprints with our Stanford collaborators: "Clusters are All You Need" and "The Orchestration Gap".
  • [May 2026] Started as a Machine Learning Research Intern at Kilby Labs, Texas Instruments (Generative AI team), working on coding agents and agentic AI systems for complex task automation.
  • [Apr 2026] Paper "LLM-Guided Semantic Bootstrapping for Interpretable Text Classification with Tsetlin Machines" accepted at ACL 2026 Findings (appeared at ACL in San Diego, July 2โ€“7)!
  • [Apr 2026] New first-author preprint "Beyond Output Correctness: Benchmarking and Evaluating Large Language Model Reasoning in Coding Tasks" (CodeRQ-Bench + VERA), from my research at UCI.
  • [Jan 2026] Two papers presented at AAAI 2026 in Singapore, now published in the Proceedings of AAAI (Vol. 40): "Mitigating Hallucinations via Causal Reasoning" and "S2D-Align".
  • [Dec 2025] Started as a Research Collaborator at Stanford University โ€” now a Core Contributor to the Terminal-Bench 3 / Harbor open-source agent evaluation ecosystem.
  • [Nov 2025] Two papers accepted at AAAI 2026! "Mitigating Hallucinations in Large Language Models via Causal Reasoning" and "S2D-Align: Shallow-to-Deep Auxiliary Learning for Anatomically-Grounded Radiology Report Generation"
  • [Sep 2025] Started my PhD at the UC Irvine Donald Bren School of ICS, focusing on LLM transparency and code generation explainability.
  • [Aug 2025] Paper "NLP-ADBench: NLP Anomaly Detection Benchmark" accepted at EMNLP 2025 Findings.
  • [Aug 2025] Completed Research Assistant position at Stanford University and USC. Special thanks to all my advisors for their mentorship and support!
  • [May 2025] Paper "AD-LLM: Benchmarking Large Language Models for Anomaly Detection" accepted at ACL 2025 Findings.
  • [April 2025] Started as Research Assistant at Stanford University with LLM-guided semantic bootstrapping research.
  • [Dec 2024] Paper "A Large-scale Empirical Study on LLMs for Election Prediction" published on arXiv.
  • [Nov 2024] Paper "FedMetaMed: Federated Meta-Learning for Personalized Medical Treatment" accepted at IEEE BIBM 2024.
  • [Nov 2024] Paper "Fed-LDR: Federated Local Data-infused Graph Creation" accepted at IEEE ICDM SSTDM Workshop 2024.
  • [Sep 2024] Began Research Collaboration at University of Virginia with Dr. Yue Cheng on AutoML and LLM inference.
  • [Aug 2024] Paper "AI-Aided Digital Twin Design: A Systematic Review" published in Preprints.
  • [Jul 2024] Paper "FedBCGD: Communication-efficient Federated Learning" accepted at ACM MM 2024.
  • [Jun 2024] Paper "H-FedSN: Hierarchical Federated Learning with Sparse Networks" published on arXiv
  • [Dec 2023] Joined University of Virginia as Research Assistant with Dr. Jiechao Gao and Prof. Brad Campbell.
  • [Jul 2023] Joined USC FORTIS Lab as Research Assistant, advised by Prof. Yue Zhao on Trustworthy LLM.
  • [May 2023] Completed USC Games position as Game Analyst & Developer on "Hexagon Adventure".
  • [Mar 2023] Published "Ablator" framework on GitHub, open-source distributed ML framework used by 40+ researchers.
  • [Feb 2023] Joined USC as Research Engineer working on distributed AutoML with Dr. Iordanis Fostiropoulos.
  • [Jan 2023] Joined USC Games as Game Analyst & Developer.
  • [Dec 2022] Completed Infrastructure Engineer role at SenseTime.
  • [Jan 2022] Started M.S. in Computer Science at University of Southern California.
  • [Dec 2021] Joined SenseTime Research as Infrastructure Engineer developing "RocketMQ as a Service".
  • [Oct 2021] Completed Research Engineer role at Institute of Software, Chinese Academy of Sciences.
  • [Apr 2021] Joined Institute of Software, Chinese Academy of Sciences as Research Engineer.
  • [Apr 2021] Completed Back End Developer role at NiuTrans.
  • [Jan 2021] Joined NiuTrans as Back End Developer.
  • [Jun 2020] Completed Full-Stack Developer role at Beijing City University.
  • [May 2018] Joined Beijing City University as Full-Stack Developer & Team Leader.