Dr. Kai Gao (高恺)

Pre-Tenure Associate Professor
School of Computer & Communication Engineering
University of Science and Technology Beijing, China
Office: Room 721, Fangxing Building
Email: kai.gao@ustb.edu.cn
Twitter, Google Scholar, GitHub

Dr.Kai Gao is currently a Pre-Tenure Associate Professor in the School of Computer & Communication Engineering, University of Science and Technology Beijing, China (2024-). He received his Ph.D. in Software Engineering from Peking University (PKU) (2019-2024), and was fortunate to be advised by Prof. Minghui Zhou and Prof. Bing Xie. He received his B.S. in Computer Science and Technology (major) and B.A. degree in Economics (minor) from PKU (2015-2019).

His research interests span software engineering, with a focus on open source software supply chain, mining software repositories, and empirical software engineering. He is also actively exploring intelligent software engineering and program analysis.

News

[2024.10] Our paper "LiCoEval: Evaluating LLMs on License Compliance in Code Generation" is accepted by ICSE 2025.

[2024.09] I have joined University of Science and Technology Beijing as an Pre-Tenure Associate Professor.

[2024.05] I have defended my doctoral thesis!

[2024.04] Our paper "PyRadar: Towards Automatically Retrieving and Validating Source Code Repository Information for PyPI Packages" is accepted by FSE 2024.

[2024.03] Our paper "A Comprehensive Analysis of Challenges and Strategies for Software Release Notes on GitHub" is accepted by EMSE.

[2023.12] Our paper "Characterizing Deep Learning Package Supply Chains in PyPI: Domains, Clusters, and Disengagement" is accepted by TOSEM.

[2023.07] Our paper "Understanding and Remediating Open-Source License Incompatibilities in the PyPI Ecosystem" is accepted by ASE 2023.

[2023.05] Our paper "Survey on Open Source Software Supply Chains" is accepted by JOS.

[2022.12] Our paper "Characterize Software Release Notes of GitHub Projects: Structure, Writing Style, and Content" is accepted by SANER 2023.

[2022.03] Our paper "On the Variability of Software Engineering Needs for Deep Learning: Stages, Trends, and Application Types" is accepted by TSE.

[2022.03] Our paper "Demystifying Software Release Note Issues on GitHub" is accepted by ICPC 2022.

[2021.12] Our paper "An Exploratory Study of Deep Learning Supply Chain" is accepted by ICSE 2022.

Last update: 2024/10.