Scholar
Jingzhi Gong
Google Scholar ID: m63bkGEAAAAJ
University of Leeds
Citations & Impact
Citations
113
H-index
7
i10-index
5
Publications
18
Co-authors
9
list available
Publications
Resume (English only)
Academic Achievements
- Recipient of the SPEC Kaivalya Dixit Distinguished Dissertation Award 2024; Published a paper titled 'Tuning LLM-based Code Optimization via Meta-Prompting: An Industrial Perspective' at ASE 2025; Another paper 'GA4GC: Greener Agent for Greener Code via Multi-Objective Configuration Optimization' was accepted by SSBSE 2025; Selected as Shadow Program Committee Member for ICSE 2026, Program Committee Member for WWW 2026, and Junior Program Committee member for MSR 2026.
Research Experience
- A member of the Intelligent Systems Software Lab (ISSL) and the Distributed Systems and Services (DSS) research group at the University of Leeds, supervised by Prof Jie Xu and Prof Zheng Wang; Also a member of the Data Science team at TurinTech AI, led by Dr Fan Wu and Dr Paul Brookes.
Education
- Completed PhD in December 2024 at the Department of Computer Science, Loughborough University, supervised by Dr Tao Chen in the IDEAS Laboratory (Intelligent Dependability Engineering for Adaptive Software Laboratory).
Background
- An AI4SE researcher building trustworthy, efficient, and sustainable software using AI. Currently working as a postdoctoral KTP Associate with both the University of Leeds and TurinTech AI, focusing on compiler- and LLM-based code optimization.
Miscellany
- Ongoing interests include AI-driven performance engineering, AI4SE, SE4AI, such as LLM performance modeling (hybrid models + online adaptive tuning), performance-aware GenAI systems (dynamic prompt engineering + configuration tuning), and industry standards/tooling.
