Stephen Thomas

Journals

Chen, T., Thomas, S. W., Hemmati, H., Nagappan, M., and Hassan, A. E. (2017). An Empirical Study on the Effect of Testing on Code Quality Using Topic Models: A Case Study on Software Development Systems. IEEE Transactions on Reliability. 66(3): 806–824.

Chen, T., Shang, W., Nagappan, M., Hassan, A. E., and Thomas, S. W. (2017). Topic-based software defect explanation. Journal of Systems and Software. 129: 79–106.

Chen, T., Thomas, S. W., and Hassan, A. E. (201). A survey on the use of topic models when mining software repositories. Empirical Software Engineering, 21(5): 1843–1919.

Barua, A., Thomas, S. W., and Hassan, A. E. (2014). What are developers talking about? An analysis of topics and trends in Stack Overflow. Empirical Software Engineering 19(3), 619–654.

Thomas, S. W., Adams, B., Hassan, A. E., and Blostein, D. (2014). Studying software evolution using topic models. Science of Computer Programming 80, 457–479.

Thomas, S. W., Hemmati, H., Hassan, A. E., and Blostein, D. (2014). Static test case prioritization using topic models. Empirical Software Engineering 19(1), 182–212.

Thomas, S. W., Snodgrass, R. T., and Zhang, R. (2014). Benchmark frameworks and tBench. Software: Practice and Experience 44(9), 1047–1075.

Thomas, S. W., Nagappan, M., Blostein, D., and Hassan, A.E. (2013). The impact of classifier configuration and classifier combination on bug localization. IEEE Transactions on Software Engineering 39(10), 1427–1443.

Currim, F., Currim, S., Dyreson, C., Snodgrass, R. T., Thomas, S. W., and Zhang, R. (2012). Adding temporal constraints to XML Schema. IEEE Transactions on Knowledge and Data Engineering 24(8), 1361–1377.

Book Chapters

Snodgrass, R. T., Gao, D., Zhang, R., Thomas, S. W., and Dempsey, J. (2018). Temporal PSM. In: Encyclopedia of Database Systems. New York, NY: Springer.

Snodgrass, R. T., Thomas, S. W., and Zhang, R. (2018). tBench. In: Encyclopedia of Database Systems. New York, NY: Springer.

Dempsey, J., Snodgrass, R. T., Thomas, S. W., and Zhang, R. (2018). Temporal Benchmarks. In: Encyclopedia of Database Systems. New York, NY: Springer.

Thomas, S. W., Hassan, A. E., and Blostein, D. (2014). Mining unstructured software repositories. In: Evolving Software Systems, pp.139–162.

Theses

Thomas, S. W. (2012). Mining unstructured software repositories using IR models. D. thesis. School of Computing, Queen’s University.

Thomas, S. W. (2009). The implementation and evaluation of temporal representations in XML. Master’s thesis. Department of Computer Science, University of Arizona.

Reports

Wood, D. M. and Thomas, S. W. (2022). Deeper Learning? Marketing, Personal Data and Privacy after Surveillance Capitalism. Report for the Office of the Privacy Commissioner of Canada.

Thomas, S. W. (2012). Mining software repositories with topic models. Technical report 2012-586. School of Computing, Queen’s University.

Thomas, S. W., Snodgrass, R. T., and Zhang, R. (2010). tBench: Extending XBench with time. Technical report TR-93.

Currim, F., Currim, S., Dyreson, C. E., Joshi, S., Snodgrass, R. T., Thomas, S. W., and Roeder, E. (2009). τXSchema: Support for data- and schema-versioned XML documents. Technical report TR-91. TimeCenter.

Case Studies & Essays

Morantz, A. and Thomas, S. W. (2026). The ABCs of AI Illiteracy. Smith Business Insight.

Gerlsbeck, R. and Thomas, S. W. (2023). Are You Ready for a ChatGPT World? Smith Business Insight.

Morantz, A. and Thomas, S. W. (2021). AI Tools for Savvy Startups. Smith Business Insight.

Thomas, S. W. (2019). Using Text Analytics to Predict Loan Defaults: Kiva. Smith Living Case.

Thomas, S. W. (2019). Assembling the AI Dream Team. Smith Business Insight.

Thomas, S. W. (2019). In AI, There are No Magical Unicorns. Smith Business Insight.

Montgomerie, A. and Thomas, S. W. (2019). Hack the Language of Loan Defaults. Smith Business Insight.

Montgomerie, A. and Thomas, S. W. (2019). Ping! Click! How One Mega-Mall Finds Its Big Data Edge. Smith Business Insight.

Thomas, S. W. (2017). Advanced Analytics at SCENE. Smith Living Case.

Webinars & Podcasts

July 28, 2026. Getting Real Value from AI: Why Most Organizations Fall Short. Queen’s Executive Education.

November 20, 2023. AI Reality Check: Welcome to the Age of AI. Smith Insight.

April 15, 2021. AI Jumpstart. HOOPP Lunch and Learn Webinar.

January 21, 2021. 7 Things Every Business Leader Needs to Know about AI. Smith Insight.

November 21, 2019. AI in Small Business. Smith Insight.

March 13, 2019. Chatbots: Technology and Trends. Smith Insight.

September 11, 2018. AI and Management Come Together in the Classroom at Queen’s University. Big Data Beard Episode 42. (YouTube)

July 3, 2018. Recommender Systems: Overview and Case Studies. Smith Insight.

May 17, 2018. Building AI Bench Strength. Smith Insight.

August 29, 2017. Data Analytics: An Overview. United Nations World Food Program ICT Workshop. Panama (Webinar).

June 29, 2017. Data Analytics: An Overview. United Nations World Food Program ICT Workshop. Johannesburg, South Africa (Webinar).

Media Coverage

External

White, Linda. “Generative AI to Change your Business.” Toronto Sun. August 30, 2023.

“Stephen Thomas on the Balance between AI Advancement and Data Security.” Canadian SME. August 12, 2023.

Lindzon, Jared. “AI plagiarism hits the workplace, creating new hazards for employers.” The Globe and Mail. July 29, 2023.

Lindzon, Jared. “Canada’s largest sectors and its workers will be most disrupted by AI, report shows.” The Globe and Mail. May 29, 2023.

Lawson, Loraine. “Banks invest in AI with an eye towards ethics.” Bank Automation News. June 8, 2021.

Lawson, Loraine. “Ethical AI: Experts say AI can be tapped for alternative credit scoring.” Bank Automation News. June 3, 2021.

Israelson, David. “How data analytics transformed M&M Food Market.” Globe and Mail. February 11, 2020.

Murray, Seb. “5 Ways Artificial Intelligence is Impacting MBA Students.” BusinessBecause. December 3, 2019.

Eppel, Mike. “Affordable intelligence - AI for small business.” 680 News. October 26, 2019.

Murray, Seb. “Should I do a Specialized Business Master’s Program?” MiM Guide. June 14, 2019.

Titleman, Naomi. “How to address the rise of AI technology in the world of work.” Globe and Mail. May 13, 2019.

Titleman, Naomi. “Robot to human: Help me help you.” Globe and Mail. May 13, 2019.

Toneguzzi, Mario. “Technology sector increasingly attractive for Calgary workers.” Calgary Business. March 12, 2019.

Flexhaug, Dallas. “Energy workers turn to tech jobs.” Global News Morning. Global News. February 25, 2019.

Saba, Rosa. “Energy workers are willing to switch to tech, survey finds – and experts say it’s time for Calgary to ‘take the lead.’” The Star Calgary. Feb 21, 2019.

Whelan, Audrey. “How Calgarians can pivot their careers towards technology.”660 News Calgary. February 13, 2019.

Lawrence, Daina. “Business and artificial intelligence come together in new program.” The Globe and Mail. December 20, 2018.

“How Calgary can become an innovation hub.” Global News Radio. Newstalk 770 Calgary. November 2, 2018.

Nilsson, Patrica. “Business schools bridge the artificial intelligence skills gap.” Financial Times. September 12, 2018.

“… with Artificial Intelligence in Business?” What on Earth is Going on? June 29, 2018.

Mark, Corey. “Why Do A Master Of Management In Artificial Intelligence?” BusinessBecause. June 7, 2018.

“Is Artificial Intelligence really more dangerous than a nuke?” The Morning Show. Global News. March 12, 2018.

Ethier, Marc. “Queen’s Launches 1st-Of-Its-Kind AI Degree.” Poets & Quants. March 12, 2018.

“The First Master’s Program in Artificial Intelligence.” Gormley. 650 CKOM Saskatchewan. March 9, 2018.

Greiner, Lynn. “IBM and Queen’s University Smith School of Business unveil five-year partnership with the Cube.” Financial Post. March 24, 2017.

Internal

Klassen, Victoria. “Queen’s Collaborates on Creating Accessible Wellness App.” Queen’s Gazette. November 24, 2021.

“Developing Leaders of Technology.” Smith Year in Review. August 31, 2021.

“Smith welcomes inaugural MMAI class.” Smith News. September 28, 2018.

Gerlsbeck, Rob. “The AI Manager.” Smith Magazine. Summer 2018.

Pabla, Jasnit. “Artificial Intelligence comes to the Smith School of Business.” The Queen’s Journal. March 23, 2018.

“Students look to solve global food security at Queen’s challenge.” Smith News. December 12, 2017.

Guest Lectures & Workshops

May 8, 2024. AI in Business. Smith Master in Management Innovation & Entrepreneurship. Kingston, ON, Canada.

March 3, 2020. AI in Business. Smith Executive MBA Alumni Event. Kingston, ON, Canada.

September 12, 2019. Introduction to NLP. Queen’s Law School. Kingston, ON, Canada.

June 17, 2019. Artificial Intelligence and Machine Learning—What is it all about? Surveillance Studies Summer Seminar. Kingston, ON, Canada.

May 15, 2019. AI in Business. Smith Executive MBA Alumni Event. Kingston, ON, Canada.

April 2, 2019. AI in Business. Smith Centre for Social Impact. Kingston, ON, Canada.

November 27, 2018. Overview of AI and NLP. Queen’s Law School. Kingston, ON, Canada.

Student Supervision

• Co-supervisor. Yihao Fang. 2023–2024.
• Tesfamariam Abuhay. 2022–2023.

• Committee member, Amir Emami Gohari. Interpretable by Design: Explainable Frameworks for Machine Learning and Recommendations in Complex Settings. 2026.
• Supervisor, Cecilia Ying. Three Studies on the Practical Use of Machine Learning Techniques in Analytics. 2020– 2025.
• Committee member, Lavy Khoushinsky. Narratives for Sale: Conceptualizing and Measuring the Marketplace for Consumer Chatter in a Digital World. 2024–2025.

• External examiner, David Eliot. Ambient Economics.
• Supervisor, Cecilia Ying. Improving the Classification Parity of Machine Learning Models through Subgroup Threshold Optimization. 2019–2020.
• External examiner, Julianne Jakobek. You Are Never Alone with a Robot: A Qualitative Content Analysis on the Use of Anthropomorphic Technologies.
• External examiner, Kristopher Jones. Toward a Political Sociology of Blockchain.
• Co-supervisor, Amir Emami Gohari. Interpretation of Black-box Models. 2017.

• Supervisor, Muhammad Hassan Anwar, Queen’s Supercluster Project. 2023.
• Supervisor, William Aitken, Queen’s Supercluster Project. 2022.
• Supervisor, Natalie Nova, Queen’s Supercluster Project. 2022.
• Supervisor, Jason Li, Queen’s Supercluster Project. 2022.
• Supervisor, Erin Atacan, Queen’s Supercluster Project. 2022.
• Supervisor, Kelly McConvey, OPC Project. 2021–2022
• Supervisor, Amir Hossini, Queen’s Supercluster Project. 2021.
• Co-supervisor, Arnoosh Golestanian, Conflict Analytics Lab. 2019.
• Co-supervisor, Karandeep Singh. Scotiabank Centre for Customer Analytics. 2019.
• Co-supervisor, Neal Gilmore. Conflict Analytics Lab. 2019.
• Co-supervisor, Ross Couldrey. Scotiabank Centre for Customer Analytics. 2018–2019.
• Supervisor, Imad Ghani. Conflict Analytics Lab. 2018–2019.
• Supervisor, Sargon Morad. Analytics and AI at Oxford Properties. 2018–2019.
• Supervisor, Sarah Scott. Analytics at SCENE. 2018.
• Co-supervisor, Arnoosh Golestanian, Analytics and AI at BGIS. 2018.
• Supervisor, Yue Zhou. Analytics at SCENE. 2017–2018.
• Supervisor, Ninad Parab. Analytics at SCENE. 2017.

Courses Taught

Smith School of Business | Queen's University

Commerce

• COMM 161: Introduction to Mathematical Analysis for Management
• COMM 162: Managerial Statistics
• COMM 163: Business Decision Models
• COMM 492: Managing Data for Business Intelligence

Master of Management Analytics

• MMA 865: Big Data
• MMA 869: Machine Learning and AI
• Workshop: Text Analytics and Sentiment Analysis Workshop: Advanced Topics in Machine Learning

Master of Management in Artificial Intelligence

• MMAI 869: Machine Learning and AI
• MMAI 891: Natural Language Processing

Global Master of Management Analytics

• GMMA 869: Machine Learning and AI
• GMMA 865: Big Data Analytics

Executive MBA Americas

• NBAB5950-MBQC960: Big Data Analytics

Executive MBA

• MBUS 865: Big Data and AI

Summer Enrichment Program

• MBQC 960: Big Data Analytics

Master of Business Administration

• MBAS 862: Topics in Analytics
• MBAS 862: Text Analytics

Queen’s Executive Education

• AI Essentials
• Introduction to AI
• Building an AI-Powered Organization
• AI for Leaders
• AI Jumpstart for Managers
• Digital Transformation
• Big Data and Text Analytics
• Text Analytics and Sentiment Analysis

Invited Presentations

June 6, 2025. AI in Business. NUCLEUS Symposium. Kingston, ON, Canada.

November 1, 2024. What is a Neural Network? Seniors Association Kingston Learning Series. Kingston, ON.

September 29, 2022. Four ways to use AI in Contact Centers. Cam-X 2022 Conference. Kingston, ON.

June 17, 2022. How Much Supervision Does AI Need? Wysdom AI Summit. Toronto, ON and Virtual.

September 29, 2020. AI Fairness. Big Data and AI Conference. Toronto, ON.

November 6, 2019. The AI Gap: Building the Next Generation of Talent. Panel member. SAS Analytics Roadshow. Toronto, ON, Canada.

June 19, 2019. Building the AI Dream Team. Vector’s AI for Executives. Toronto, ON, Canada.

June 13, 2019. The New Manager: The Growing Need for Analytics & AI Managers. What AI Can Do to Drive Your Business Forward. HEC Montreal. Montreal, QB, Canada.

June 12, 2019. The New Manager: The Growing Need for Analytics & AI Managers. Big Data and AI conference. Toronto, ON, Canada.

May 3, 2019. AI and Big Data. Canadian University Board Association Conference. Kingston, ON, Canada.

March 9, 2019. AI Transforming Industry. Panel moderator. Canadian Undergraduate Conference on Artificial Intelligence. Kingston, ON, Canada.

March 6, 2019. Machine Learning in the Financial Industry. Panel member. CPA Ontario. Toronto, ON, Canada.

December 10, 2018. Building Analytics and AI Bench Strength. SLF Analytics Conference. Toronto, ON, Canada.

November 7, 2018. AI and the Future of Extraction Industries. Becoming Future Proof. Calgary, AB, Canada.

August 28, 2018. AI and Analytics for Business. Disney Data & Analytics Conference 2018. Orlando, FL, USA.

June 6, 2018. Recommender Systems: Overview and Three Case Studies. Smith/Vector Presents: AI for Execs. Toronto, ON, Canada.

May 17, 2018. AI and Analytics in Business. Machine Learning & Artificial Intelligence Ottawa. Ottawa, ON, Canada.

May 11, 2018. Building the Next Generation of Analytics Talent. Analytics by Design. Toronto, ON, Canada.

May 2, 2018. Advanced Analytics at SCENE. Queen’s Data Day. Kingston, ON, Canada.

April 18, 2018. Analytics and AI in Business. Council for Chief Privacy Officers: Emerging Technologies and Privacy. Toronto, ON, Canada.

October 23, 2017. Machine Learning and Analytics. Smith in Calgary (Alumni Event). Calgary, AB, Canada.

September 6, 2017. Artificial Intelligence. Smith Graduate Student Consortium. Roundtable Discussion. Kingston, ON, Canada. 

July 24, 2017. Harnessing the Power of Data Analytics within Your Organization. Chief Learning Officer Exchange. Toronto, ON, Canada.

June 1, 2017. Sentiment Analysis: Opportunities, Challenges, and the Future. Queen’s Analytics Institute Workshop. Kingston, ON, Canada.

April 19, 2017. The Analytics Mindset. Scotiabank’s Finance Learning Day. Toronto, ON, Canada.

March 13-14, 2017. A Strategic Analytics Framework. United Nations Data Innovations Lab Workshop. Nairobi, Kenya. 

November 7, 2012. Effective bug localization. IBM CASCON 2012. Markham, ON, Canada.

October 15, 2012. Mining unstructured data. Panelist member. Mining Unstructured Data 2012. Kingston, ON, Canada.

Other

October 18, 2019. AI in Business. Queen’s Homecoming Event. Kingston, ON, Canada.

June 11, 2019. AI in Business. Proof Lunch and Learn. Toronto, ON, Canada.

May 7, 2019. AI and Smith. Presentation to the Smith Global Council. New York, NY, USA.

February 4, 2019. AI and Smith. Presentation to the Smith Global Council. London, UK.

Selected Refereed Conference Proceedings

Ghassel, A., Zhu, X., and Thomas, S. W. (2024). Are Large Language Models General-Purpose Solvers for Dialogue Breakdown Detection? An Empirical Investigation. In: Proceedings of the IEEE Canadian Conference on Electrical and Computer Engineering (CCECE).

Fang, Y., Li, X., Thomas, S. W., and Zhu, X. (2024). HGOT: Hierarchical Graph of Thoughts for Retrieval-Augmented In-Context Learning in Factuality Evaluation. In: Proceedings of the 4^th Workshop on Trustworthy Natural Language Processing (TrustNLP). Winner: Best long paper award.

Fang, Y., Li, X., Thomas, S. W., and Zhu, X. (2023). ChatGPT as Data Augmentation for Compositional Generalization: A Case Study in Open Intent Detection. In: Proceedings of the 5^th Workshop on Financial Technology and Natural Language Processing (FinNLP).

Li, X., Aitken, W., Zhu, X., and Thomas, S. W. (2022). Learning Better Intent Representations for Financial Open Intent Classification. In: Proceedings of the 4^th EMNLP Workshop on Financial Technology and Natural Language Processing (FinNLP).

Ying, C. and Thomas, S. W. (2022). Label Errors in BANKING77. In: Proceedings of the 2022 ACL Insights Workshop.

Ying, C. and Thomas, S. W. (2021). Improving Fairness in Credit Lending Models with Machine Learning. In: Proceedings of the 2021 NeurIPS Workshops on Strategic Machine Learning.

Bettenburg, N., Thomas, S. W., and Hassan, A. E. (2012). Using fuzzy code search to link code fragments in discussions to source code. In: Proceedings of the 16^th European Conference on Software Maintenance and Reengineering.

Snodgrass, R. T., Gao, D., Zhang, R., and Thomas, S. W. (2012). Temporal support for Persistent Stored Modules. In: Proceedings of the 28^th International Conference on Data Engineering.

Thomas, S. W. (2011). Mining software repositories with topic models. In: Proceedings of the 33^rd International Conference on Software Engineering, pp. 1138–1139.

Thomas, S. W., Adams, B., Hassan, A. E., and Blostein, D. (2011). Modeling the evolution of topics in source code histories. In: Proceedings of the 8^th Working Conference on Mining Software Repositories, pp. 173–182.

Thomas, S. W., Adams, B., Hassan, A. E., and Blostein, D. (2010). Validating the use of topic models for software evolution. In: Proceedings of the 10^th International Working Conference on Source Code Analysis and Manipulation, pp. 55–64. Winner: Most influential paper award, SCAM 2020.

Teaching Honors

• 2024–2027. Distinguished Teaching Fellow of Management Analytics. Smith School of Business
• 2026. Professor of the Year Award, Smith Master of Management Analytics
• 2024. Professor of the Year Award, Smith Master of Management Analytics
• 2024. Professor of the Year Award, Smith Master of Financial Innovation & Technology
• 2024. Professor of the Year Award, Smith Global Master of Management Analytics
• 2024. Faculty of the Year Award, Smith Master of Management in Artificial Intelligence
• 2023. Professor of the Year Award, Smith Master of Management Analytics
• 2023. Professor of the Year Award, Smith Master of Financial Innovation & Technology
• 2023. Professor of the Year Award, Smith Global Master of Management Analytics
• 2023. Faculty of the Year Award, Smith Master of Management in Artificial Intelligence
• 2021–2023. Distinguished Teaching Professorship. Smith School of Business
• 2022. Professor of the Year Award, Smith Master of Management Analytics
• 2022. Professor of the Year Award, Smith Global Master of Management Analytics
• 2022. Faculty of the Year Award, Smith Master of Management in Artificial Intelligence
• 2021. Professor of the Year Award, Smith Master of Management Analytics
• 2021. Professor of the Year Award, Smith Global Master of Management Analytics
• 2021. Faculty of the Year Award, Smith Master of Management in Artificial Intelligence
• 2020. Faculty of the Year Award, Smith Master of Management in Artificial Intelligence
• 2019. Professor of the Year Award, Smith Master of Management Analytics
• 2019. Faculty of the Year Award, Smith Master of Management in Artificial Intelligence
• 2018. Professor of the Year Award, Smith Master of Management Analytics
• 2017. Professor of the Year Award, Smith Master of Management Analytics

Research & Academic Honors

• TrustNLP Best Long Paper Award
• SCAM 2020 Most Influential Paper Award
• INFORMS George D. Smith Prize. Co-winner
• 2016–present. Scotiabank Scholar, Smith School of Business, Queen’s University

Selected Grants

• 2022–2024. Wellness AI project. Canada’s Digital Technology Supercluster. With partners Lululemon and Wysdom.ai. CAD 350,000.
• 2021. Deeper Learning: Marketing, Personal Data and Privacy after Surveillance Capitalism. Office of the Privacy Commissioner of Canada. With David Murakami Wood, David Eliot, and Kelly McConvey. CAD 49,407.78.
• 2020. Machine Learning for Default Prediction of Private Pension Administration. Mitacs. With Ryan Riordan and Cecilia Ying. CAD 15,000.

Fellowships & Early Academic Awards

• 2009–2012. Queen’s Graduate Award Scholarship, Queen’s University
• 2009. Advanced Scholarship Program recipient, Raytheon Missile Systems
• 2009. Graduate Tuition Scholarship, University of Arizona
• 2005–2006. Member, Pi Mu Epsilon, New Mexico State University
• 2004–2006. Dean’s List, New Mexico State University
• 2004–2006. Crimson Scholar, New Mexico State University

Selected Academic Service

• Member, Queen’s AI Nexus Committee, 2025–present
• Member, Smith Analytics and AI Curriculum Review Committee, 2023–2024
• Chair, Smith Management Analytics Comprehensive Exam Committee, 2022–2023
• Area Coordinator, Smith Management Analytics, 2022–2025
• Reviewer, Association for Computational Linguistics (ACL) Open Review, 2022–present
• Member, Comprehensive Exam Committee, 2021–2022
• Chair, Smith Analytics and AI Advisory Board Curriculum Subcommittee, 2019–2024
• Member, Analytics by Design Advisory Board, 2019–present
• Member, Queen’s University Alternative Assets Fund (QUAAF) Executive Board, 2019–2024
• Executive Advisor, Analytics by Design, 2018–2019
• Member, Smith MMAI Faculty Development Fund Committee, 2018–2020
• Member, Smith Master of Management Analytics Curriculum Review Committee, 2017
• Member, Smith Analytics and AI Advisory Board, 2016–2023
• Conference Reviewer, MSR Challenge, 2013
• Journal co-reviewer: IEEE Transactions on Software Engineering, Software: Practice and Experience
• Conference co-reviewer: MSR Challenge 2012, MSR 2012, ICSE 2012, CASCON 2011, WCRE 2011, ESEM 2011, MSR 2011, ICSM 2010, WCRE 2010, GI 2010, MSR 2010

Research Affiliations

• Data Scientist, The Conflict Analytics Lab. 2018–2022.
• Research Scholar, The Scotiabank Centre for Customer Analytics. 2016–present

Professional Affiliations

• 2020–present. Member, INFORMS
• 2010–present. Member, ACM Special Interest Group on Software Engineering (SIGSOFT)
• 2008–present. Member, Association for Computing Machinery (ACM)
• 2008–present. Member, Institute of Electrical and Electronics Engineers (IEEE)