Tim Tsz-Kit Lau

About Tim Tsz-Kit Lau

My research lies broadly at the interface of machine learning, optimization and statistics. In particular, I am interested in theory and applications of optimization and sampling techniques to generative artificial intelligence (GenAI), e.g, training strategies of large language models (LLMs) and attention-based vision models (e.g, vision transformer), and score-based generative models (SGMs; a.k.a. diffusion models). These are rooted in my research expertise in optimization for machine learning and statistics, particularly stochastic, nonsmooth, nonconvex and/or distributionally robust optimization algorithms, as well as the interplay between optimization and sampling.

Experience

1. Ai Researcher

   DRW

   Jun 2025 — Present · Palo Alto, CA, US

   GenAI for trading

Education

• The University of Hong Kong

  Bachelor of Science (BSc), Major in Mathematics and Minor in Economics

  2012 — 2015

• Northwestern University

  Doctor of Philosophy - PhD, Statistics and Data Science

  2018 — 2023

• CentraleSupélec

  Exchange Program, Option Mathématiques Appliquées - Data Sciences Track

  2017 — 2017

• The Hong Kong University of Science and Technology

  Master of Science (MSc), Big Data Technology

  2016 — 2017

• The University of Hong Kong

  Master of Statistics (MStat)

  2015 — 2016

• Duke Kunshan University

  Duke-Tsinghua Machine Learning Summer School, Machine Learning, Deep Learning

  2017 — 2017