Mohammad Emtiyaz Khan
Mohammad Emtiyaz Khan studies how Bayesian principles can help AI systems learn and adapt. His work connects approximate inference, optimization and continual learning. Khan completed his PhD at UBC in 2012 under Kevin Murphy. He was a postdoctoral researcher at EPFL from 2013 and a scientist there from 2014 to 2016. Khan directed a tenured RIKEN team from October 2016 to May 2026. The group studies adaptive learning through Bayesian statistics and optimization.
- Now at
- TU Darmstadt
- Works
- 89
- Citations
- 1,202
- h-index
- 15
Publication numbers from OpenAlex, as of 14 October 2026.
Timeline
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2012–2016
Training and research at UBC and EPFL
Khan completed his PhD at UBC in 2012 under Kevin Murphy. He was a postdoctoral researcher at EPFL from 2013 and a scientist there from 2014 to 2016.
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2016–2026
A Bayesian intelligence team
Khan directed a tenured RIKEN team from October 2016 to May 2026. The group studies adaptive learning through Bayesian statistics and optimization.
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2020
Remembering earlier tasks
Khan coauthored work on continual deep learning through functional regularization of the memorable past. The paper appeared at NeurIPS 2020.
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June 2026
A move to Darmstadt
Khan began a professorship at TU Darmstadt on 1 June 2026. After the move, he served as a visiting team director at RIKEN.
Sources and credits
Photo: www.riken.jp; Mohammad Emtiyaz Khan profile photograph; creator not stated. License: Not stated by source. Source: riken.jp. Cropped to a square and resized. Ask us to remove or replace this photo.