Research

Publications and preprints

† Corresponding author. * Equal contribution.

Published

  1. Michael A. Kouritzin, Ian Zhang†, Jyoti Bhadana, Seoyeon Park. Markov Processes for Enhanced Deepfake Generation and Detection. AIMS Mathematics, 2026, 11(4): 11731–11759. doi: 10.3934/math.2026483

Under review

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

Preprints

  1. Ian Zhang†, Thibault Randrianarisoa. The Impact of Likelihood Tempering on the Limiting Predictive Moments of Variational Bayesian Linear Neural Networks. 2026. arXiv: 2610.09132

In progress

  1. Ian Zhang*†, Hanlong Chen*, …, Howard Chertkow, …, Malcolm Binns. Redundancy-Aware Model Assessment for Component and Cluster Selection in Clinical Subtype Discovery. 2026.
  2. Hanlong Chen*, Ian Zhang*, …, Malcolm Binns. Continuous Cognitive Heterogeneity in Dementia: A Severity Factor and an Age-Related Amnestic Axis Without Reproducible Subtypes. 2026.
  3. Ian Zhang†, Finn Tran, Meredith Franklin. Spatial Dependence Regularization for Improved Generalization in Climate Downscaling Models. 2026.
  4. Gabriel Liu*, Ian Zhang*†, …, Daniel Alessi. LiBRE: Statistical Learning for Representative Brine Design and Lithium Enrichment Analysis. 2026.

Research experience

Doctoral Student, Department of Statistical Sciences, University of Toronto — 2026–Present

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

Presentations

Conference talks

Posters