Hassan Ashtiani
Hassan Ashtiani is an associate professor in the Department of Computing and Software at McMaster University and a Faculty Member of the Vector Institute. His research centers on sample complexity, which asks how much data a learning method needs. In 2018 his paper on sample complexity bounds for learning Gaussian mixtures won a NeurIPS best paper award. He joined McMaster University in 2018 after completing a Ph.D. at the University of Waterloo. Before that, he earned degrees in AI and Robotics and in computer engineering at the University of Tehran.
- Now at
- McMaster University and Vector Institute
- Works
- 31
- Citations
- 220
- h-index
- 8
Publication numbers from OpenAlex, as of 15 October 2026.
Timeline
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By 2018
Degrees from Tehran and Waterloo
At the University of Tehran he earns degrees in AI and Robotics and in computer engineering; a Ph.D. in computer science at the University of Waterloo follows in 2018.
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2018
Joining McMaster University
He joins McMaster University in 2018 after obtaining his Ph.D.
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2018
A NeurIPS best paper
A NeurIPS 2018 best paper award goes to his paper on sample complexity bounds for learning Gaussian mixtures.
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2025
A Vector Institute faculty member
In 2025 the Vector Institute names him one of 13 new Faculty Members.
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As of October 2026
An associate professor at McMaster
He is an associate professor in the Department of Computing and Software at McMaster University, which he joined in 2018.
Sources and credits
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