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Emtiyaz Khan

I am a team leader (equivalent to Full Professor) at the RIKEN center for Advanced Intelligence Project (AIP) in Tokyo where I lead the Approximate Bayesian Inference (ABI) Team. From April 2018, I am a visiting professor at the EE department in Tokyo University of Agriculture and Technology (TUAT). I am an Action Editor for the Journal of Machine Learning (JMLR). From 2014 to 2016, I was a scientist at EPFL in Matthias Grossglausser's lab. During my time at EPFL, I taught two large machine learning courses for which I received a teaching award. I first joined EPFL as a post-doc with Matthias Seeger in 2013 and before that I finished my PhD at UBC in 2012 under the supervision of Kevin Murphy.

emtiyaz [at] gmail.com [or] emtiyaz.khan [at] riken.jp

Research Publications Teaching People News Blog


  • Open positions: (Update) I do not have any open positions until April 2020. Applications will open sometime in September 2019.
  • Upcoming talks/events/papers
  • My talk at NeurIPS 2018 Advances in Approximate Bayesian Inference Symposium summarising my work on natural-gradient variational inference:


"My main goal is to understand the principles of learning from data and use them to develop algorithms that can learn like living beings."

My current focus is on sequential learning and exploration. I am working on problems in several areas of machine learning, such as approximate inference, deep learning, reinforcement learning, active learning, online learning, and reasoning in computer vision. In my recent works, I have worked on ideas from a wide range of fields, such as, optimization, Bayesian statistic, information geometry, signal processing, and control systems.

Research Highlights


I am tutorials chair at ACML 2019. I am an Area Chair for ICLR 2020, NeurIPS 2019 (23 papers), ACML 2019 (3 papers), ICML 2019 (7 papers), and a reviewer for ICASSP 2019 (5 papers) and Bayesian Analysis (1 paper). In 2018, I reviewed around 70 papers, and in 2017, I reviewed 54 papers.