Background

A short
curriculum vitæ.

From applied math at Waterloo to optimization and machine learning at U of T — here's the route I took and the people who shaped it.

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Joe Liang
Toronto, ON · 2026 ↓ photo placeholder
Summary

Applied ML, with a soft spot for clean optimization.

I'm a PhD student in Applied Machine Learning at the University of Toronto (D3M Lab), supervised by Prof. Scott Sanner. My research focus is conversational recommendation systems, memory-augmented LLM agents, and egocentric information retrieval.

I have a strong publication record at top venues — 3 papers at ACL 2026, plus ICLR 2026, AAAI 2026, EMNLP 2025, UMAP 2026, and Sociological Methods & Research — spanning retrieval, NLP, optimization, and embodied AI.

I'm a recipient of the Ontario Graduate Scholarship and multiple U of T fellowships and conference awards, including the MIE Teaching Assistant Award 2024–2025.

PhD, U of T (2025—) MASc, U of T (2025) BMath, Waterloo (2022)
Education
where I trained
Sep 2025 — Present

PhD, Computer Science

University of Toronto · Data Driven & Decision Making Lab

Research: Novel methods and memory access for conversational agents and recommendation systems. Supervised by Prof. Scott Sanner.

  • Ontario Graduate Scholarship
  • U of T Departmental Fellowship
  • School of Graduate Studies Conference Award
  • Departmental Conference Award
Sep 2023 — Aug 2025

MASc, Information Engineering

University of Toronto · Mechanical & Industrial Engineering

Thesis: Novel Optimization Methods for Temporal and Predictive Clustering. Supervised by Prof. Scott Sanner.

  • MIE Fellowships
  • MIE Teaching Assistant Award (2024–2025)
Sep 2018 — Jun 2022

BMath, Computational Mathematics

University of Waterloo
  • Dean's Honour List
  • Graduated with Distinction
Research
labs & collaborations
Sep 2023 — Present

Graduate Research Assistant

D3M Lab, University of Toronto

Researching structured memory systems, agentic information retrieval, and conversational recommendation for XR environments under Prof. Scott Sanner.

  • Co-authored 8+ peer-reviewed papers at ACL, ICLR, AAAI, EMNLP, UMAP, and others.
  • Active contributor to multiple concurrent projects spanning NLP, ML, and embodied AI.
Sep 2023 — Sep 2025

Part-Time Research Assistant

Department of Human Biology, University of Toronto
  • Analyzed 100,000+ encrypted student course records using Python (NumPy, Pandas, Scikit-Learn).
  • Produced executive-level visualizations (Seaborn, Plotly) for academic decision-makers.
Teaching
100+ students / term

Teaching Assistant & Head TA

Recipient of the MIE Teaching Assistant Award 2024–2025. I design tutorial materials and course projects, lead weekly tutorials, deliver Python demos, and mentor students one-on-one.

MIE223 · Head TA
Introduction to Data Science
University of Toronto
MIE451
Decision Support Systems
University of Toronto
MIE370
Introduction to Machine Learning
University of Toronto
Sep — Dec 2021
Teaching Assistant
University of Waterloo
Awards
scholarships & honours
2025 — Present
Ontario Graduate Scholarship
Province of Ontario
2025 — Present
U of T Departmental Fellowship
University of Toronto
2024 — 2025
MIE Teaching Assistant Award
Mechanical & Industrial Engineering
2024
School of Graduate Studies Conference Award
University of Toronto
2024
Departmental Conference Award
University of Toronto
2023 — 2024
MIE Fellowships
University of Toronto
2018 — 2022
Dean's Honour List
University of Waterloo
2022
Graduated with Distinction
University of Waterloo
Service

Academic service

  • Journal Reviewer
    ACM Transactions on Recommender Systems (TORS)
Skills

Programming & tools

Python PyTorch Transformers / LLMs NumPy Pandas Scikit-Learn PySpark SQL LP / MILP Gurobi Linux Git

Transferable

Academic communication Research mentorship Curriculum design Cross-disciplinary collaboration Conference presentation

Curious to read the papers?

Browse publications Google Scholar