Scholar
Shaowei Wang
Google Scholar ID: PIBtljkAAAAJ
Associate professor, Department of Computer Science, University of Manitoba
Citations & Impact
Citations
2,875
H-index
28
i10-index
51
Publications
20
Co-authors
28
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Paper 'VulScribeR: Exploring RAG-based Vulnerability Augmentation with LLMs' accepted by TOSEM.
- Paper 'Order Matters! An Empirical Study on Large Language Models' Input Order Bias in Software Fault Localization' accepted by ICSE 2026.
- Paper 'Model Performance-Guided Evaluation Data Selection for Effective Prompt Optimization' accepted in ACL 2025, findings.
- Received the Distinguish Reviewer Award from FSE.
- Promoted to Associate Professor and tenured.
- Student Shayan successfully defended their thesis.
- Two papers accepted by FSE 2025.
- Paper 'Exploring Demonstration Retrievers in RAG for Coding Tasks: Yeas and Nays!' accepted by SANER 2025.
- Paper 'ZS4C: Zero-Shot Synthesis of Compilable Code for Incomplete Code Snippets using LLMs' accepted by TOSEM.
- Student Azmain successfully defended their thesis and graduated.
- Paper 'SimClone: Detecting Tabular Data Clones using Value Similarity' accepted by TOSEM.
- Paper 'Studying and Recommending Information Highlighting in Stack Overflow Answers' accepted by IST.
- Paper 'Towards Better Graph Neural Network-based Fault Localization Through Enhanced Code Representation' accepted by FSE 2024.
Research Experience
- Leads the Mamba Lab, focusing on software management, maintenance, and reliability research. Previously, he was an assistant professor at Mississippi State University.
Education
- Before joining the University of Manitoba, he was an assistant professor at Mississippi State University. Currently, he is an associate professor in the Department of Computer Science at the University of Manitoba.
Background
- Research interests: software engineering, security, and machine learning. The goal is to improve developers' productivity (e.g., code generation/recommendation, bug fixing) and ensure software quality (e.g., vulnerability detection and bug localization) effectively and efficiently. Research areas include large language models with and for software engineering, software security, code generation and search, data-driven software engineering, AIOps & DevOps.
Miscellany
- Currently only accepting PhD students; applicants need to have completed or be in the process of completing a master's degree.
