Curriculum Vitae

Download PDF Last updated: June 2026

Education

PhD in Statistics, University of Toronto
Sep 2026 –
- Advisors: Joshua Speagle, Thibault Randrianarisoa
MSc in Statistics, University of Toronto
Sep 2025 – Jun 2026
- Advisor: Nancy Reid
Honours BSc in Statistics/Mathematics, University of Toronto
Sep 2021 – Jun 2025
- Advisor: Jun Young Park
- Graduated with high distinction

^†: Corresponding Author *: Equal contribution

Michael A. Kouritzin, Ian Zhang^†, Jyoti Bhadana, Seoyeon Park. Markov processes for enhanced deepfake generation and detection[J]. AIMS Mathematics, 2026, 11(4): 11731–11759. doi: 10.3934/math.2026483

Aditya Khan, Ian Zhang
2026
Parametric Hotspot Analysis with the Getis-Ord Statistic.

Ian Zhang^†, Thibault Randrianarisoa
2026
Likelihood Tempering to Mitigate Prior Dominance in Variational Posteriors for Bayesian Neural Networks.
Ian Zhang^*,†, Hanlong Chen^*, …, Howard Chertkow, …, Malcolm Binns
2026
Redundancy-Aware Model Assessment for Component and Cluster Selection in Clinical Subtype Discovery.
Hanlong Chen^*, Ian Zhang^*, …, Malcolm Binns
2026
Continuous Cognitive Heterogeneity in Dementia: A Severity Factor and an Age-Related Amnestic Axis Without Reproducible Subtypes.
Ian Zhang^†, Finn Tran, Meredith Franklin
2026
Spatial Dependence Regularization for Improved Generalization in Climate Downscaling Models.

Graduate Research Assistant, Baycrest Institute/University of Toronto
2025 – Present
Supervisor: Malcolm Binns
Summer Research Trainee, McGill University
2025
Supervisor: Jianguo (Jeff) Xia
Research Assistant, University of Alberta
2023 – 2024
Supervisor: Mike Kouritzin

2026 Joint Statistical Meetings
2026
Will be presenting RAMA: Redundancy-Aware Model Assessment for PCA-Based Clinical Subtype Discovery.
2026 SSC Annual Meeting in Hamilton
2026
Presented Likelihood Tempering to Mitigate Prior Dominance in Variational Posteriors for Bayesian Neural Networks in the New Frontiers in Bayesian Analysis session.
2025 SSC Annual Meeting in Saskatoon
2025
Presented Markov Processes for Enhanced Deepfake Generation and Detection in the Probability session.
Third Joint SIAM/CAIMS Annual Meetings
2025
Presented Markov Processes for Enhanced Deepfake Generation and Detection in the Machine Learning and Stochastic Processes session.

The Thirteenth Annual Canadian Statistics Student Conference
2025
Presented Comparing Exact and Approximate Inference for Spatial Autocorrelation Tests: A Power Analysis.

Anna & Alex Beverly Memorial Fellowship
2025
Awarded by University College (University of Toronto) for general proficiency during my undergraduate degree.
NSERC Undergraduate Student Research Award (x2)
2023, 2024
Awarded by the University of Alberta to research Markov process methods for deepfake generation and detection.
Jack Zwaigenbaum Scholarship
2022
Awarded by University College (University of Toronto) for academic excellence in my first year of undergraduate studies.
Dean's List Scholar (x4)
2022, 2023, 2024, 2025
Awarded by the Faculty of Arts and Science (University of Toronto) for maintaining academic excellence every year of my undergraduate degree.

CSSC Travel Grant
2025
Awarded to full-time Canadian students presenting a poster or giving a talk at the Canadian Statistics Student Conference.

Session chair, 2025 Third Joint SIAM/CAIMS Annual Meetings
Chaired the “Machine Learning and Stochastic Processes” session.