Stephen Thomas

Stephen Thomas

Executive Director, Analytics & AI Ecosystem

Overview

Dr. Stephen W. Thomas is an adjunct faculty member at Smith School of Business at Queen’s University in Kingston, ON, Canada. He is also the Executive Director of Smith's Analytics & AI Ecosystem. He was named the Professor of the Year in the MMA program in 2017 and 2018.

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Academic Area

  • Digital Technology
  • Management Analytics

Interest Topics

Faculty Details

Profile

Full Bio

Dr. Stephen W. Thomas is an adjunct faculty member at Smith School of Business at Queen’s University in Kingston, ON, Canada. He is also the Executive Director of Smith's Analytics & AI Ecosystem. He was named the Professor of the Year in the MMA program in 2017 and 2018.

Dr. Thomas holds PhD, MSc, and BSc degrees in Computer Science. His main interests are databases, data analytics, and natural language processing. His research has been published in IEEE Transactions on Knowledge and Data Engineering, IEEE Transactions on Software Engineering, Empirical Software Engineering, and others. He is a recipient of the Scotiabank Scholar research grant.

Dr. Thomas previously ran a tech startup in the world of big data. He consults with several large companies in the areas of big data, text analytics, and AI. He previously held an industrial data analytics position at Raytheon in Tucson, AZ.

Dr. Thomas teaches several courses on natural language processing, machine learning, database design, big data, and mathematical analysis in Smith Commerce and MMA, and MMAI programs. He serves on the MMA advisory board.

Academic Degrees

PhD, Computer Science
Queen’s University (2012)

MS, Computer Science
University of Arizona (2009)

BS, Computer Science
New Mexico State University (2006)

Academic Experience

Smith School of Business, Queen's University
Executive Director, Analytics and AI Ecosystem (2021 - Present)
Director, Master of Management Analytics (2018-2020)
Director, Master of Management in Artificial Intelligence (2018-2020)
Adjunct Assistant Professor (2013 - Present)

School of Computing, Queen’s University
Research Assistant (PhD Student) (2009-2012)

Publications

Refereed Papers

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. (2016). Topic-based software defect explanation. Journal of Systems and Software. 129: 79-106.

Chen, T., Thomas, S. W., and Hassan, A. E. (2015). 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 of Software Engineering 39(10), 1427–1443.

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 16th European Conference on Software Maintenance and Reengineering.

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.

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

Thomas, S.W. (2011). Mining software repositories with topic models. In: Proceedings of the 33rd 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 8th 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 10th International Working Conference on Source Code Analysis and Manipulation, pp. 55–64. 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. PhD 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.

Case Studies and Essays

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. (2017). Advanced Analytics at SCENE. Smith Living Case.

Technical Reports

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. TimeCenter.

Other

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.

November 30, 2012. PhD thesis defense. Mining unstructured software repositories using IR models. Kingston, ON, Canada.

December 9, 2011. Presentation for School of Computing Open House. Effective bug localization. Kingston, ON, Canada.

December 10, 2010. Presentation for School of Computing Open House. Statistical topic models. Kingston, ON, Canada.

March 6, 2009. Master’s thesis defense. The implementation and evaluation of temporal representations in XML. Tucson, AZ, USA.

In the Media

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.

Rosa Saba. “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

“In AI, There are No Magical Unicorns.” Smith Business Insight. June 5, 2019.

Montgomerie, Adrienne. “Hack the Language of Loan Defaults.” Smith Business Insight. April 2, 2019.

Montgomerie, Adrienne. “Ping! Click! How One Mega-Mall Finds Its Big Data Edge.” Smith Business Insight. March 26, 2019.

“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.

Webinars and Podcasts

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).

Teaching

Courses Taught

Commerce, Smith School of Business, Queen’s University

  • COMM 161: Introduction to Mathematical Analysis for Management. Fall 2013.

  • COMM 492: Managing Data for Business Intelligence. Winter 2014. Fall 2014. Fall 2015. Fall 2016. Fall 2017.

Master of Management Analytics, Smith School of Business, Queen’s University

  • MMA 865: Big Data. 2017. 2018W. 2018S. 2019W. 2019S. 

  • MMA 869: Machine Learning and AI. 2019S. 2020W.

  • Text Analytics and Sentiment Analysis. 2015. 2016. 2017. 2018W. 2018S. 2019W.

Master of Management in Artificial Intelligence, Smith School of Business, Queen’s University

  • MMAI 869: Machine Learning and AI. 2019. 2020.

  • MMAI 891: Natural Language Processing. 2019. 2020.

Executive MBA Americas, Smith School of Business, Queen’s University/Cornell University

  • NBAB5950-MBQC960: Big Data Analytics. 2019. 2020.

Summer Enrichment Program, Smith School of Business, Queen’s University

  • MBQC960: Big Data Analytics. 2019.

Master of Business Administration, Smith School of Business, Queen’s University

  • MBAS 862: Text Analytics. Fall 2019.

Queen’s Executive Education

  • Text Analytics and Sentiment Analysis. 2015-2016 

  • Big Data and Text Analytics. 2017-

  • Digital Transformation. 2019-

  • AI Essentials for Managers. 2019-

Student Supervision

MSc

Co-supervisor, Cecilia Ying. Topic TBD. 2019 –

External examiner, Julianne Jakobek. You Are Never Alone with a Robot: A Qualitative Content Analysis on the Use of Anthropomorphic Technologies. 2019.

External examiner, Kristopher Jones. Toward a Political Sociology of Blockchain. 2018.

Research Assistant

Co-supervisor, Arnoosh Golestanian, Conflict Analytics Lab. 2019. 

Co-supervisor, Karandeep Singh. Analytics at iTrade. 2019.

Co-supervisor, Neal Gilmore. Conflict Analytics Lab. 2019.

Co-supervisor, Ross Couldrey. Analytics at iTrade. 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

Co-supervisor, Amir Emami Gohari. Interpretation of Black-box Models. 2017

Guest Lectures and Workshops

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. Conference Presentations

August 20, 2012. Mining unstructured software repositories. Poster. MSR 2020 Vision. Kingston, ON, Canada.

June 21, 2011. Mining software repositories with topic models. Poster. ICPC 2011. Kingston, ON, Canada.

June 17, 2011. Mining software repositories with topic models. Poster. PASED 2011. Montreal, QB, Canada.

May 23, 2011. Mining software repositories with topic models. ICSE 2011. Honolulu, HI, USA.

May 22, 2011. Modeling the evolution of topics in source code histories. MSR 2011. Honolulu, HI, USA. 

September 12, 2010. Validating the use of topic models for software evolution. SCAM 2010. Timisoara, Romania.

Awards

Teaching Awards

2019. MMA Professor of the Year (Class of Summer 2019)

2019. MMA Professor of the Year (Class of Winter 2019)

2018. MMA Professor of the Year (Class of Summer 2018)

2018. MMA Professor of the Year (Class of Winter 2018)

2017. MMA Professor of the Year (Class of Summer 2017)

Scholarships

2016–present. Scotiabank Scholar, Smith School of Business, Queen’s University

2009–2012. Queen’s Graduate Award Scholarship, Queen’s University

2009. Advanced Scholarship Program, Raytheon Missile Systems

2009. Graduate Tuition Scholarship, University of Arizona

2004–2006. Crimson Scholar, New Mexico State University

Other Awards

2004–2006. Dean’s List, New Mexico State University

2005–present. Member, Pi Mu Epsilon, New Mexico State University

Presentations

Invited Presentations

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.

Service

Academic Service

  • Member, Queen’s University Alterative Assets Fund (QUAAF) Executive Board, 2019–
  • Executive Advisor, Analytics By Design Conference, 2018–
  • Member, Queen’s MMAI Faculty Development Fund committee, 2018–
  • Member, Queen’s Master of Management Analytics Curriculum Review Committee. 2017.
  • Member, Queen’s Master of Management Analytics Advisory Board. 2016
  • 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–
  • Scholar, the Scotiabank Centre for Customer Analytics. 2016–

Professional Affiliations

  • 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)