Misha Denil

I am a Research Scientist at DeepMind.

I was previously a PhD student in the Computer Science department at the University of Oxford, supervised by Nando de Freitas.

Before that I was a Master's student in the Computer Science department at the University of British Columbia, where I also worked with Nando de Freitas.

I did my undergraduate degree in Computer Science at Dalhousie University where I worked with Thomas Trappenberg.

News

• Oct 2019 We published our Framework for Data-Driven Robotics.
• Dec 2018 Our paper on Hyperbolic Attention Networks will appear at ICLR 2019.
• Jan 2018 Our paper on Learning Awareness Models will appear at ICLR 2018.
• May 2017 We have two papers on learning optimizers that will appear at ICML 2017.
• Feb 2017 My paper on Learning to Experiment will appear at ICLR 2017.
• Nov 2016 There have been several news articles covering my paper on Learning to Experiment.
• Sep 2016 Our paper on Learning to Learn will appear at NIPS 2016.
• Jun 2016 Our paper on Noisy Activation Functions will appear at ICML 2016.
• Feb 2016 Our paper on ACDC will appear at ICLR 2016.
• Jan 2016 Our Deep Multi-Instance Learning paper won the Yelp Dataset Challenge.
• Aug 2015 Our Deep Fried Convnets paper was accepted to ICCV.
• Jun 2015 Our paper on deep multi instance learning for NLP will appear at KDD.
• Jan 2015 I joined Google DeepMind as a Research Scientist.
• Jul 2014 Internship at Facebook AI Research in Menlo Park.
• Apr 2014 Our paper on distributed parameter learning in MRFs was accepted to ICML.
• Mar 2014 My work on random forests was selected for an MSR PhD Scholarship project.
• Feb 2014 Our lab received a Google award for my work on parameter prediction in deep learning.