Yao Wan 萬瑤
Mar., 2024 Three papers have been accepted by NAACL 2024. Congratulations to Wenting and Dongping!- Mar., 2024 Our paper titled "Graph Neural Networks for Vulnerability Detection - A Counterfactual Explanation" has been accepted by ISSTA 2024. Congratulations to Zhaoyang!
- Jan., 2024 Our paper titled "Automated Data Visualization from Natural Language via Large Language Models: An Exploratory Study" has been accepted by SIGMOD 2024. Congratulations to Yang!
- Jan., 2024 Our paper titled "IRCoCo: Immediate Rewards-Guided Deep Reinforcement Learning for Code Completion" has been accepted by FSE 2024. Congratulations to Bolun!
- Jan., 2024 Our paper titled "NL2Formula: Generating Spreadsheet Formulas from Natural Language Queries" has been accepted by EACL 2024. Congratulations to Wei!
- June 14, 2022 Our paper titled "You See What I Want You to See: Poisoning Vulnerabilities in Neural Code Search" has been accepted by ESEC/FSE 2022. Congratulations to Shijie!
- Feb 24, 2022 Our two papers on source code summarization and generation have been accepted by ACL 2022 . Congratulations to Juncai and Xin!
- Jan 25, 2022 Our paper titled "NaturalCC: An Open-Source Toolkit for Code Intelligence" has been accepted by ICSE 2022 Demo Track.
- Nov 28, 2020 Our toolkit NaturalCC has been released in GitHub, which can be accessed via the Homepage.
About Me
I am an Associate Professor with the College of Computer Science and Technology at Huazhong University of Science and Technology (HUST), Wuhan, China. Prior to that, I got my Ph.D degree from Zhejiang University in Dec., 2019, under the supervision of Prof. Jian Wu and Prof. Zhou Zhao. I have been visiting Shenzhen Research Institute, Chinese University of Hong Kong, China (working with Prof. Zibin Zheng) in 2014, University of Technology Sydney, Australia (working with Prof. Guandong Xu) in 2016, and University of Illinois at Chicago, USA (working with Prof. Philip S. Yu) in 2018. My research interests are mainly focusing on the synergy between Artificial Intelligence and Software Engineering, especially on Natural Language Processing, Programming Languages, and Large Language Models.
(I am looking for highly-motivated under-graduate students with a strong passion to work with me. If interested, please drop me a message by email.)
Research Highlights
NaturalCC is an advanced sequence modeling toolkit designed to empower researchers and developers in training custom models for a myriad of software engineering tasks, including but are not limited to code summarization, code generation, code search, and type inference. Our vision is to seamlessly connect the realms of programming language and natural language, leveraging cutting-edge machine learning techniques. arXiv Code Homepage
Selected Publications
ACM Computing Survey 2024.
PDF arXiv
ISSTA 2024. The ACM SIGSOFT International Symposium on Software Testing and Analysis
PDF CCF-A
SIGMOD 2024. ACM Special Interest Group on Management of Data
PDF CCF-A
FSE 2024.The ACM International Conference on the Foundations of Software Engineering
PDF arXiv CCF-A
ESEC/FSE 2022. The 30th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering.
PDF CCF-A
ICSE 2022. The 44th ACM/IEEE International Conference on Software Engineering
PDF CCF-A
Confenrence PC/Reviewer