I am a Research Scientist at Google DeepMind in San Francisco, working on improving Gemini post-training and test-time compute. I have a broad set of interests within machine learning, including:

  • Reasoning, Alignment, and Inference in Large Language Models
  • Deep Generative Models (particularly Diffusion Models)
  • Variational Inference and Monte Carlo Methods
  • Optimization Methods for Neural Networks
  • Computational Optimal Transport
  • Intersection of Machine Learning with Information Theory

Previously, I was an associate professor (status-only) in the Department of Electrical & Computer Engineering at the University of Toronto, a faculty member at the Vector Institute for Artificial Intelligence, and a Canada CIFAR AI Chair from 2018 to 2024.

I completed my PhD thesis at the University of Toronto with Brendan Frey in 2018, where I was part of the Machine Learning Group. During my PhD, I interned at Google DeepMind in 2016 and Google Brain in 2015. I completed my Master’s degree at the University of Toronto in 2012, and received my Bachelor’s degree from Amirkabir University of Technology, Iran, in 2010.

Email: makhzani_at_cs_toronto_edu

Selected Publications