Yunshi Lan

Yunshi Lan is an Associate Professor at the School of Data Science and Engineering, East China Normal University (ECNU). He holds a Ph.D. from Singapore Management University (SMU) and a Bachelor's degree from Southwest University (SWU). His research focuses on knowledge bases, question answering systems, deep learning, and large language models. He has led multiple grants, including projects from the National Science Foundation of China and the Shanghai Pujiang Talent Program. Lan has published extensively in top venues like ACL, EMNLP, and AAAI, with notable contributions to visual question answering, grammatical error correction, and educational NLP. He serves on program committees for ACL, EMNLP, and AAAI, and has given invited talks on large language models and knowledge-based systems. His teaching includes undergraduate and graduate courses on deep learning, emphasizing practical applications and LLM integration. Lan mentors a vibrant research group, with students contributing to impactful projects like MWPToolkit and FlaCGEC datasets.

Education: Ph.D., SMU (201X); B.Sc., SWU (201X). Key grants include 'Knowledge Base Question Answering System in Interactive Environments' (NSFC, 2023-2025) and 'Intelligent Low Carbon Oriented Theories for Cross-Border Electric Power Trading' (NSFC, 2024-2028). Awards include the First Prize in the Financial GraphRAG Competition (2024) and the Shanghai Pujiang Talent Program (2022). His research highlights include benchmarking Visual Chinese GEC, developing TreeEval for LLM evaluation, and creating educational NLP tools like 中介语智能批改 for CFL learning.