Yuchen Lin is a
Postdoc Researcher at Allen Institute for AI (AI2), hosted by Prof. Yejin Choi (University of Washington). Yuchen's primary interest lies in studying the science of large language models (LLMs), developing AI agents for complex interactive tasks, and evaluating the reasoning and alignment ability of LLMs. His research aims to teach machines how to think, plan, and act like humans. Moreover, Yuchen's work focuses on enhancing the robustness, safety, and generalization of LLMs through retrieval augmentation, continual learning, ensemble learning, etc.
Yuchen received Best Paper Award Runner-up at The Web Conference 2020, best paper award at TrustNLP 2021, and got selected as AI Rising Star by Baidu Scholar. He has given several tutorials at ACL and WSDM, and served as an Area Chair for ACL 2023 and EMNLP 2023. He received his PhD from University of Southern California in 2022, advised by Prof. Xiang Ren. Previously, he got his bachelor’s degree from the IEEE Honored Class at Shanghai Jiao Tong University (2014-2018) and won the Best Thesis Award, advised by Prof. Kenny Zhu. He was a research intern at Facebook AI Research (FAIR) (2021 with Scott Yih), Google AI (2020 with William Cohen, 2019 with Sandeep Tata), and Microsoft Research Asia (2017-2018).
🤝 I'm very open to collaboration! Please feel free to email me. :D