Yanlin Wang

Yanlin Wang is an Assistant Professor at the School of Software Engineering, Sun Yat-sen University, where he joined in July 2022 after working as a senior researcher at Microsoft Research Asia in the Data, Knowledge, and Intelligence (DKI) group. His academic journey includes a B.S. from Zhejiang University and a Ph.D. from the University of Hong Kong under the supervision of Prof. Bruno C. d. S. Oliveira.

Dr. Wang's research spans multiple domains within computer science, with particular emphasis on applying large language models to software engineering problems. His work bridges traditional software engineering with cutting-edge AI techniques, focusing on code generation, code search, and intelligent software development tools. He has made significant contributions to understanding how LLMs can be effectively applied to repository-level code completion, security analysis of smart contracts, and improving the efficiency of code generation processes.

An analysis of his recent publications reveals a strong trend toward applying AI to practical software engineering challenges, particularly in the areas of code generation quality, security analysis, and efficient model deployment. His work often combines theoretical insights with practical implementations, as evidenced by multiple tools and frameworks developed by his research group, including MemoryBank for enhancing LLMs with long-term memory and AGIEval for evaluating foundation models.

• ACM SIGSOFT Distinguished Paper Award (ISSTA 2024) - for work on LLM code generation acceleration
• ACM SIGSOFT Distinguished Paper Award (ISSTA 2024) - for work on identifying code security issues
• ACM SIGSOFT Distinguished Paper Award (Internetware 2024)
• Distinguished Reviewer Award (Internetware 2024)
• Best Paper Award (Modularity 2016)

Dr. Wang actively contributes to the academic community through service on program committees for major conferences including ISSTA, FSE, ICSE, and COLING. He serves as a reviewer for prestigious journals and conferences such as TKDE, TNNLS, and AAAI. His teaching portfolio at Sun Yat-sen University includes Principles of Compilers, AI Revolution: Decoding Large Models, and Software Source Codes Analysis, reflecting his expertise across both foundational and cutting-edge topics in computer science.