Research

Experimental Design

• Genetic Algorithm-Based Bayesian Optimal Design for Network Experiments - with Steiner and Nathaniel T. Stevens. Technometrics (2025). pp 1-20. doi 10.1080/00401706.2025.2584500.

Networks

• General additive network effects model - with Stefan H. Steiner and Nathaniel T. Stevens. New England Journal of Statistics and Data Science (2023). pp 1-19, doi 10.51387/23-NEJSDS29.

  • Featured in the “Design and Analysis of Experiments for Data Science” webinar by the New England Journal of Statistics in Data Science.

Causal Inference

• Causal inference for the expected number of recurrent events in the presence of a terminal event - with Benjamin R. Baer, Daniel Mork, Robert L. Strawderman, Ashkan Ertefaie.

AI Verification

• Outperformance Score: A Universal Standardization Method for Confusion-Matrix-Based Classification Performance Metrics - with Ningsheng Zhao, Jia Yuan Yu and Krzysztof Dzieciolowski.

• Correcting Biases of Shapley Value Attributions for Informative Machine Learning Model Explanations - with Ningsheng Zhao, Jia Yuan Yu and Krzysztof Dzieciolowski. Proceedings of the 33rd ACM International Conference on Information and Knowledge Management (2024), pp 3331–3340. doi:10.1145/3627673.3679846

• Error Analysis of Shapley Value-Based Model Explanations: An Informative Perspective - with Ningsheng Zhao, Jia Yuan Yu and Krzysztof Dzieciolowski. In: Avni, G., et al. AI Verification. SAIV (2024). Lecture Notes in Computer Science, vol 14846, pp 29–48. Springer, Cham. doi 10.1007/978-3-031-65112-0_2.

Applied Research

• Understanding the Impact of Seasonal Climate Change on Canada’s Economy by Region and Sector - with Shiyu He, Yuying Huang, Wenling Zhang, Jie Jian, Samuel W.K. Wong, and Tony S. Wirjanto.

  • Won the Case Studies in Data Analysis Poster Competition during the SSC Annual Meeting, 2023.

• In all fairness: A meta-analysis of the tax fairness-tax compliance literature - with Jonathan Farrar, Mary Marshall, Dawn Massey, Linda Thorne, and Anita Wu. Behavioral Research in Accounting (2023), 1–26, doi 10.2308/BRIA-2022-040.

• Outperformance Score: A Universal Standardization for Confusion Matrix-Based Classification Performance Metrics: The Thirteenth Annual Conference of the Upstate Chapters of the American Statistical Association (2025); Quality and Productivity Research Conference (2025); Data Science Research Group at Rochester Institute of Technology (2025); Ploutos AI Community Livestream (2025).

• Optimal Bayesian Designs for Network A/B Testing: Joint Research Conference on Statistics in Quality, Industry, and Technology (2024); ASA/IMS Spring Research Conference (2025).

• Analysis Of Experiments On Networks With Binary Outcomes: Statistical Society of Canada Annual Meeting (2024).

• General Additive Network Effects Model for Network Experimentation: Virtual ISI World Statistics Congress (2021); Research Presentation Day at Department of Statistics and Actuarial Science, University of Waterloo (2022); Statistical Society of Canada Annual Meeting (2023).

• Introduction to Experimental Design on Networks: Student Seminar Series UWaterloo (2020); Invited Seminar for Program Analysis Section, Canada Revenue Agency (2024).

Undergraduates

• Sanika Poojary. UWaterloo’s WiM DRP (2024). Project: Introduction to Explanable AI → Master of Data Science and Artificial Intelligence at University of Waterloo.

• Jamiee Yeung. UWaterloo’s WiM DRP (2023, 2024). Projects: Visualizing and Analyzing Spatially Correlated Data, Introduction to Explanable AI → Analyst at Evercore.

• Sagun Malwatkar. UWaterloo’s WiM DRP (2023). Project: Asymptotics for Linear Regression → Software Development Engineer at Amazon.