Dr. Zhenpeng Chen (้™ˆ้œ‡้น)

                    Research Fellow
                    Department of Computer Science
                    University College London (UCL)
                    Gower Street, London WC1E 6BT, UK
                    Email: zp.chen AT ucl DOT ac DOT uk

                         



I am a Research Fellow at University College London (UCL), working with Prof. Mark Harman and Prof. Federica Sarro. I received my Ph.D. from Peking University (PKU), and was fortunate to be advised by Prof. Hong Mei and Prof. Xuanzhe Liu. My Ph.D dissertation won the Outstanding Doctoral Dissertation Award of China Computer Federation. I received my B.S. in Computer Science and B.A. in Economics from Peking University (PKU).

My research interests mainly focus on Trustworthy AI, Software Engineering for AI, and AI for Software Engineering.


Recent Services: ASE 2023 (Research Track, NIER Track, and Tool Demo Track), WWW 2023, KDD 2023, ISSRE 2023, ICWS 2023, ESEC/FSE 2023 Industry Track, SANER 2023 Tool Track, TOSEM Board of Distinguished Reviewers, TWEB Board of Distinguished Reviewers. Looking forward to your high-quality submissions!

News

  • Our paper "Adonis: Practical and Efficient Control Flow Recovery through OS-Level Traces" has been accepted by TOSEM.
  • Our MSR'23 paper has been selected as an ACM SIGSOFT Distinguished Paper. Thanks for the recognition!
  • Our paper "AutoML from Software Engineering Perspective: Landscapes and Challenges" has been accepted by MSR 2023.
  • Our paper "FaaSLight: General Application-Level Cold-Start Latency Optimization for Function-as-a-Service in Serverless Computing" has been accepted by TOSEM.
  • Our paper "Who Judges the Judge: An Empirical Study on Online Judge Tests" has been accepted by ISSTA 2023.
  • Our comprehensive study of fairness improvement methods for machine learning software has been accepted by TOSEM.
  • Our systematic review of serverless computing has been accepted by TOSEM.
  • Privacy-friendly federated learning on heterogeneous smartphones! Check out our paper "FLASH: Heterogeneity-aware Federated Learning at Scale" accepted by TMC.
  • Interested in software fairness? We will present our paper "MAAT: A Novel Ensemble Approach to Fixing Fairness and Performance Bugs for Machine Learning Software" at ESEC/FSE 2022.
  • Can emojis predict dropouts of remote developers? Find out in our paper "Emojis predict dropouts of remote workers: An empirical study of emoji usage on GitHub" accepted by PLOS ONE.
  • I am excited to join University College London as a Research Fellow.
  • June 11, 2021. I successfully defend my PhD thesis.