Jeremy Bradbury
PhD
Pronouns: he/him
Professor
Computer ScienceFaculty of Science
Improving software quality through enhanced development practices, tools and education. Supporting software developers test and analyze software with the support of machine learning automation and recommendation. Supporting computer science education and developer retraining through AI-powered personalized learning tools.
- Graduate student research supervision
- Media inquiries
- Partnerships
jeremy.bradbury@ontariotechu.ca
905.721.8668 ext. 3685
Research website
Software Engineering & Education Research Lab
- PhD in Computer Science Queen's University 2007
- MSc in Computing and Information Science Queen's University 2002
- BSc in Computer Science and Mathematics, First Class Honours with Distinction Mount Allison University 2000
- Invited Panelist, "The Role of AI in Software Testing", the 17th IEEE International Conference on Software Testing, Verification and Validation (ICST 2024), May 31, 2024.
- Invited Speaker, “Perspectives on Generative AI and Education”, the 2023 Ontario Universities Council for eLearning Summer Institute, July 24, 2023.
- Invited Panelist, “Top five lessons learned in entertainment games, serious games, and gamification R&D.... is there a ray of sunshine?”, 6th International Workshop on Games and Software Engineering (GAS 2022), May 2022.
- Invited Keynote, “Advancing Test Automation Using Artificial Intelligence (AI)”, 4th IEEE Workshop on NEXt level of Test Automation (NEXTA), April 2021.
- Invited Panelist, “The Impact of AI and Machine Learning on Quality Assurance”, Toronto Association of Systems and Software Quality (TASSQ) President’s Dinner & 25th Anniversary, September 25, 2018.
- Invited Speaker, “Can Commit History Predict Future Code Changes in GitHub Projects”, invited NOVA LINCS Seminar, Universidade Nova de Lisboa, Portugal, June 12, 2018.
- Invited Speaker, “Automating Software Development Using Artificial Intelligence (AI)”, Computer Science Seminar, Mount Allison University, Canada, March 21, 2018.
- Michael A. Miljanovic, Jeremy S. Bradbury. “Engineering Adaptive Serious Games Using Machine Learning.” in Software Engineering for Games in Serious Contexts – Theories, Methods, Tools, and Experiences, 2023, 17 pages.
- Nadia L. Goralski, Jeremy S. Bradbury. “Adapting Between Parsons Problems and Coding Tasks.” Proc. of the 54th ACM Technical Symposium on Computer Science Education (SIGCSE 2023) – Posters, Toronto, Canada, March 2023, pages 1289.
- Stacey A. Koornneef, Jeremy S. Bradbury, Michael A. Miljanovic. “Run, Llama, Run: A Computational Thinking Game for K-5 Students Designed to Support Equitable Access.” Proc. of the 54th ACM Technical Symposium on Computer Science Education (SIGCSE 2023) – Posters, Toronto, Canada, March 2023, pages 1395.
- Jude Arokiam, Jeremy S. Bradbury. “Automatically Predicting Bug Severity Early in the Development Process,” Proc. of the 42nd International Conference on Software Engineering (ICSE 2020), The New Ideas and Emerging Results (NIER) track, Seoul, South Korea, Oct. 2020.
- Michael A. Miljanovic, Jeremy S. Bradbury. “GidgetML: An Adaptive Serious Game for Enhancing First Year Programming Labs,” Proc. of the 42nd International Conference on Software Engineering (ICSE 2020), The Software Engineering Education and Training (SEET) track, Seoul, South Korea, Oct. 2020.
Tim McTiernan Student Mentorship Award
Ontario Tech University2018-2019
Teaching Representative, Ontario Tech University Board of Governors
September 1, 2015Dr. Bradbury was elected as a Teaching Representative on Ontario Tech University's Board of Governors for a three-year term from 2015-18.
Canada Foundation for Innovation Leaders Opportunity Fund - Laboratory for Human-Centred Computer Science Research
January 1, 2012Dr. Bradbury is the principal investigator of this research in Ontario Tech University's Human-Centred Control (HCC) Lab, which was designed for conducting controlled experiments that allow researchers to better understand and evaluate how people interact with leading-edge computer technology. Research in this lab falls under three main themes: information visualization, software engineering and computer security. In all three themes, a novel research approach focuses on the usability perspective of innovative prototypes and tools in new and emerging environments (e.g., mobile devices, large touch displays).
RAISE 2012 Best Paper Award
January 1, 2012Dr. Bradbury received the award for his paper Predicting Mutation Score Using Source Code and Test Suite Metrics, at the Workshop on Realizing Artificial Intelligence Synergies in Software Engineering.
Consortium for Software Enginnering Research (CSER) 2011 Best Poster Award
October 1, 2011Awarded one of three Best Poster Awards at the 2011 CSER Fall Meeting for his work Eclipticon: Eclipse Plugin for Concurrency Testing.
SoftVis’10 Best Poster Award
October 25, 2010Dr. Bradbury received this award for his poster An Interactive Visualization of Thread Interleavings at the 5th ACM Symposium on Software Visualization (SoftVis'10).
School of Computing Award for Excellence in Teaching Assistance
June 1, 2003Dr. Bradbury received this award for his contributions to teaching at Queen's University from 2002-03.
Ian A. Macleod Award
June 1, 2003Given to the graduate student who has made the greatest contribution to the intellectual and social spirit of the School of Computing, Queen's University, 2002-03
eXcellence In Variant Testing (XIVT)
ITEA 3 Call 4 Pan-European Project (2018)[locally funded through a contract with QA Consultants]
Utilizing Artificial Intelligence to Improve the Testing and Debugging of Concurrent Software
NSERC Discovery Grant (2018)Testing and Analysis of Concurrent and Heterogeneous Computing Software ($75,000)
NSERC Discovery Grant April 1, 2013This collaborative five-year research grant expands upon previous research in software testing and analysis in several key areas. This project aims to improve the quality of concurrent and heterogeneous (multicore + manycore) software, and develop better tools to improve the speed and accuracy of assessing this software through automatic testing and analysis techniques. Another key area of this project builds on creating enhanced algorithms for automatic bug detection and repair, as well as automatic debugging in which an algorithm can automatically locate code with the highest probability for a bug to exist.
Laboratory for Human-Centred Computer Science Research ($21,152)
Canada Foundation for Innovation Leaders Opportunity Fund January 1, 2012Dr. Bradbury is the principal investigator of this research in Ontario Tech University's Human-Centred Control (HCC) Lab, which was designed for conducting controlled experiments that allow researchers to better understand and evaluate how people interact with leading-edge computer technology. Research in this lab falls under three main themes: information visualization, software engineering and computer security. In all three themes, a novel research approach focuses on the usability perspective of innovative prototypes and tools in new and emerging environments (e.g., mobile devices, large touch displays).
Empirical Assessment and Improvement of Fault Detection Techniques for Concurrent Software
NSERC Discovery Grant (2008)ACM Special Interest Group on Software Engineering (SIGSOFT)
ACM Special Interest Group on Computer Science Education (SIGCSE)
Association of Computing Machinery (ACM)
Consortium of Software Engineering Research (CSER)
IEEE Computer Society
Institute of Electrical & Electronics Engineers (IEEE)
- Software Quality Assurance (CSCI 3060U)
- Massively Parallel Programming (CSCI 4060U)
- Applications of AI to Software Engineering & Education (CSCI 6100G)
