Kostadin Damevski, Ph.D.
Professor and Graduate Program Director, Department of Computer Science; Co-Director, Software Engineering Center
- Richmond VA UNITED STATES
Builds machine learning and AI systems that study and support how software developers communicate, reason about code, and handle security.
Social
Biography
Damevski was named a VCU Nationally and Internationally Recognized Scholar (NIRA) in 2025. His research has been supported by NSF, DARPA, DOE, DHS, and industry partners including Google and ABB. He serves as an Associate Editor of IEEE Software, and is Co-General Chair of SANER 2027, which his group is hosting in Richmond.
Industry Expertise
Areas of Expertise
Education
University of Utah
Ph.D.
Computer Science
2007
Affiliations
- Co-Director, Software Engineering Center, VCU College of Engineering
- Associate Editor, IEEE Software
Media Appearances
Software Engineering Center at VCU will train engineers to build robust applications
VCU News online
2026-05-01
With more than $3.5 million in NSF support, the center is developing software and AI solutions for critical industries, like healthcare.

National Science Foundation award funds development of experiential learning program to address shortage of AI professionals in healthcare
VCU News online
2025-04-15
The National Science Foundation (NSF) recently awarded a $750,000 grant to support the development of “living labs” for undergraduates at the Virginia Commonwealth University (VCU) College of Engineering. Living labs (LL) are a form of experiential learning that integrates multidisciplinary science, technology, engineering and math (STEM) education with hands-on educational opportunities.
Selected Articles
Improving Data Curation of Software Vulnerability Patches through Uncertainty Quantification
IEEE Transactions on Software Engineering (2025)Hui Chen, Yunhua Zhao, Kostadin Damevski
We propose an approach employing Uncertainty Quantification (UQ) to curate datasets of publicly-available software vulnerability patches.
Toxicity Ahead: Forecasting Conversational Derailment on GitHub
International Conference on Software Engineering (ICSE 2026)Mia Mohammad Imran, Robert Zita, Rahat Rizvi Rahman, Preetha Chatterjee, Kostadin Damevski
We present a novel Large Language Model (LLM)-based framework for predicting conversational derailment on GitHub.
Fast changeset-based bug localization with BERT
44th International Conference on Software Engineering (ICSE 2020)Agnieszka Ciborowska, Kostadin Damevski
2022-05-01
Helping developers to localize bugs (using bug reports) to the changeset that induced them. Changesets (or diffs) can be more useful for fixing bugs than static source code (e.g., methods or classes) as they encode the change that created the bug and include a (usually) meaningful message.