Research seminars

Our virtual seminar series is where we exchange ideas with guest speakers, keeping you up to date with the latest developments and inspiring research topics. Occasionally, Secondmind researchers present their own work as well.

Coming soon

Emtiyaz Khan - Bayesian Principles for Learning-Machines

September 17, 2021 - Emtiyaz Khan - Team leader at the RIKEN center for Advanced Intelligence Project (AIP) in Tokyo

Javier González Hernández

September 30, 2021 - Javier González Hernández - Microsoft Research, Cambridge

Roberto Calandra

October 14, 2021 - Roberto Calandra - Research Scientist at Facebook AI Research

François-Xavier Briol

October 28, 2021 - François-Xavier Briol - Lecturer in the Department of Statistical Science at University College London, Group Leader at The Alan Turing Institute

Frank Hutter

November 11, 2021 - Frank Hutter - Professor of Computer Science at the University of Freiburg

Noémie Jaquier

November 25, 2021 - Noémie Jaquier - Lecturer in the Department of Statistical Science at University College London, Group Leader at The Alan Turing Institute

Dino Sejdinovic

December 2, 2021 - Dino Sejdinovic - Associate Professor at the Department of Statistics, University of Oxford, a Fellow of Mansfield College, Oxford, and a Turing Fellow of the Alan Turing Institute

Victor Picheny - Revisiting Bayesian optimisation in the light of the COCO benchmark

Date pending - Victor Picheny - Senior Applied Scientist, Secondmind

Past seminars

Ciara Pike-Burke - A unifying view of optimism in episodic reinforcement learning

September 2, 2021 - Ciara Pike-Burke - Lecturer in Statistics at Imperial College London

José Miguel Hernández Lobato - Probabilistic Methods for Increased Robustness in Machine Learning

July 15, 2021 - José Miguel Hernández Lobato - University Lecturer in Machine Learning at the Department of Engineering in the University of Cambridge, UK

Carl Henrik Ek - Modulating surrogates for bayesian optimization

June 10, 2021 - Carl Henrik Ek - Senior Lecturer in the Computer Laboratory at the University of Cambridge, UK, and a Docent in Machine Learning at the Royal Institute of Technology, Sweden

Peter Stone - Efficient Robot Skill Learning

May 13, 2021 - Peter Stone - Professor, University of Texas, Austin; Executive Director, Sony AI America

Laurence Aitchison - Deep Kernel Processes

March 4, 2021 - Laurence Aitchison - Senior Lecturer, Computational Neuroscience Unit, University of Bristol

Andrew G. Wilson - How do we build models that learn and generalize?

January 21, 2021 - Andrew G. Wilson - Assistant Professor, Courant Institute of Mathematical Sciences and Center for Data Science, New York University

Vincent Adam - Sparse methods for markovian GPs

January 14, 2021 - Vincent Adam - Senior Machine Learning Researcher, Secondmind; Postdoctoral researcher, Aalto University

M. E. Taylor - Reinforcement Learning in the real world: How to “cheat” and still feel good about it

December 17, 2020 - Matthew E. Taylor - Associate Professor, Department of Computing Science, Director at The Intelligence Robot Learning Laboratory, University of Alberta

Arthur Guez - Value-driven Hindsight Modelling

November 19, 2020 - Arthur Guez - Google DeepMind

Alexandra Gessner - Integration for and as Bayesian inference

November 12, 2020 - Alexandra Gessner - Ph.D. candidate, Probabilistic Numerics group, The Max Planck Institute for Intelligent Systems in Tübingen

Arno Solin - Stationary Activations for Uncertainty Calibration in Deep Learning

October 29, 2020 - Arno Solin - Assistant Professor in Machine Learning, Department of Computer Science, Aalto University

Siddharth Reddy - Assisting Human Perception and Control using Theory of Mind -

October 22, 2020 - Siddharth Reddy - Ph.D. candidate, Berkeley Artificial Intelligence Research Lab, University of California, Berkeley

Peter Frazier - Knowledge Gradient Methods for Bayesian Optimization

October 8, 2020 - Peter Frazier - Associate Professor of Operations & Information Engineering, Cornell University; Staff Data Scientist, Uber

Gabriel Dulac-Arnold - Challenges of Real-world RL: Definition, Implementation, Analysis

October 1, 2020 - Gabriel Dulac-Arnold - Researcher at Google Research

Philipp Hennig - Computation under Uncertainty

September 24, 2020 - Philipp Hennig - Professor for the Methods of Machine Learning, University of Tuebingen; Adjunct scientist, Max Planck Institute for Intelligent Systems in Tuebingen

Magnus Rattray - Non-parametric modelling of gene expression in time and space

September 10, 2020 - Magnus Rattray - Professor of Computational & Systems Biology, University of Manchester

Andreas Krause - Safe and Efficient Exploration in Reinforcement Learning

August 27, 2020 - Andreas Krause - Professor of Computer Science, Director of Learning & Adaptive Systems Group, ETH Zurich

Rahul Kidambi - MOReL: Model-Based Offline Reinforcement Learning

August 6, 2020 - Rahul Kidambi - Post-doctoral researcher, Department of Computer Science, Cornell University

Arthur Gretton - Generalized Energy-Based Models

July 30, 2020 - Arthur Gretton - Professor, Gatsby Computational Neuroscience Unit, Director of the Centre for Computational Statistics and Machine Learning, University College London

Gergely Neu - A unified view of entropy-regularized Markov decision processes

May 21, 2020 - Gergely Neu - Research Assistant Professor, AI group, DTIC, Universitat Pompeu Fabra

Want to get involved?

If you have interesting research that you'd like to share, please get in touch.

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