About me

I am a Program-Specific Postdoctoral Researcher at Kyoto University, working at the intersection of data-driven stochastic dynamical systems, Koopman operator theory, and AI for scientific modeling.

My research develops operator-theoretic and machine-learning methods for understanding complex nonlinear dynamics. I am particularly interested in generative modeling, spectral analysis of Koopman semigroups, computational neuroscience, and scientific machine learning for stochastic systems.

News

• 2025: Joined Kyoto University as a Program-Specific Postdoctoral Researcher.

• 2025: Ph.D. in Applied Mathematics, University of Alberta.

• 2025: Faculty of Science Doctoral Dissertation Award.

• 2025: ResKoopNet accepted to ICML 2025.

• Education

• Ph.D. in Applied Mathematics, University of Alberta, 2021-2025

• M.S. in Mathematics, University of Manitoba, 2018-2020

• B.S. in Mathematics, University of Oregon, 2015-2017

Teaching

University of Alberta

Winter 2025: MATH 102 Lab, Applied Linear Algebra

Fall 2024 and Spring 2024: MATH 209 Lab, Calculus for Engineering III

Winter 2024: MATH 102 Lab, Applied Linear Algebra

Fall 2023 and Winter 2023: MATH 201 Lab, Differential Equations

Spring 2024: MATH 101 Lab, Calculus for Engineering II

• Awards

• Faculty of Science Doctoral Dissertation Award, 2025

• Mary Louise Imrie Graduate Student Award, 2025

• Dr. Josephine M. Mitchell Recruitment Scholarship, 2021

• International Graduate Student Entrance Scholarship, 2020 and 2018

• Clarence and Lucille Dunbar Scholarship, 2017

• Selected Publications and Preprints

• ResKoopNet: Learning Koopman Representations for Complex Dynamics with Spectral Residuals
  ICML 2025.

• A Data-Driven Framework for Koopman Semigroup Estimation in Stochastic Dynamical Systems
  Chaos, 2025.

• Generative Modeling through Koopman Spectral Analysis: An Operator-Theoretic Perspective
  arXiv preprint.

• Reinforced Data-Driven Estimation for Spectral Properties of Koopman Semigroup in Stochastic Dynamical Systems
  arXiv preprint.

• Spectral analysis of Koopman operator through pseudo-resolvent
  arXiv preprint.

• Koopman Spectral Analysis Uncovers the Temporal Structure of Spontaneous Neural Event
  COSYNE 2024.

• Data-Driven Approaches for Analyzing Complex Dynamical Systems through Koopman Framework
  Ph.D. thesis, 2025.

• Decentralized Multi-Agent Reinforcement Learning for Task Offloading Under Uncertainty
  arXiv preprint.

• Machine Learning With Echo State Networks
  M.S. thesis, 2020.