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Poster session
Sebastian Farquhar · Erik Daxberger · Andreas Look · Matt Benatan · Ruiyi Zhang · Marton Havasi · Fredrik Gustafsson · James A Brofos · Nabeel Seedat · Micha Livne · Ivan Ustyuzhaninov · Adam Cobb · Felix D McGregor · Patrick McClure · Tim R. Davidson · Gaurush Hiranandani · Sanjeev Arora · Masha Itkina · Didrik Nielsen · William Harvey · Matias Valdenegro-Toro · Stefano Peluchetti · Riccardo Moriconi · Tianyu Cui · Vaclav Smidl · Taylan Cemgil · Jack Fitzsimons · He Zhao · · mariana vargas vieyra · Apratim Bhattacharyya · Rahul Sharma · Geoffroy Dubourg-Felonneau · Jonathan Warrell · Slava Voloshynovskiy · Mihaela Rosca · Jiaming Song · Andrew Ross · Homa Fashandi · Ruiqi Gao · Hooshmand Shokri Razaghi · Joshua Chang · Zhenzhong Xiao · Vanessa Boehm · Giorgio Giannone · Ranganath Krishnan · Joe Davison · Arsenii Ashukha · Jeremiah Liu · Sicong (Sheldon) Huang · Evgenii Nikishin · Sunho Park · Nilesh Ahuja · Mahesh Subedar · · Artyom Gadetsky · Jhosimar Arias Figueroa · Tim G. J. Rudner · Waseem Aslam · Adrián Csiszárik · John Moberg · Ali Hebbal · Kathrin Grosse · Pekka Marttinen · Bang An · Hlynur Jónsson · Samuel Kessler · Abhishek Kumar · Mikhail Figurnov · Omesh Tickoo · Steindor Saemundsson · Ari Heljakka · Dániel Varga · Niklas Heim · Simone Rossi · Max Laves · Waseem Gharbieh · Nicholas Roberts · Luis Armando Pérez Rey · Matthew Willetts · Prithvijit Chakrabarty · Sumedh Ghaisas · Carl Shneider · Wray Buntine · Kamil Adamczewski · Xavier Gitiaux · Suwen Lin · Hao Fu · Gunnar Rätsch · Aidan Gomez · Erik Bodin · Dinh Phung · Lennart Svensson · Juliano Tusi Amaral Laganá Pinto · Milad Alizadeh · Jianzhun Du · Kevin Murphy · Beatrix Benkő · Shashaank Vattikuti · Jonathan Gordon · Christopher Kanan · Sontje Ihler · Darin Graham · Michael Teng · Louis Kirsch · Tomas Pevny · Taras Holotyak

Fri Dec 13 09:35 AM -- 10:35 AM (PST) @
in Bayesian Deep Learning »

Author Information

Sebastian Farquhar (University of Oxford)
Erik Daxberger (University of Cambridge)
Andreas Look (Bosch Center for Artificial Intelligence)
Matt Benatan (IBM Research UK)
Ruiyi Zhang (Duke University)

I am currently a fourth-year Ph.D. student at Department of Computer Science, Duke University. My research interest is Deep Learning.

Marton Havasi (University of Cambridge)
Fredrik Gustafsson (Uppsala University)
James A Brofos (The MITRE Corporation)
Nabeel Seedat (Cornell University (USA) & University of Witwatersrand (South Africa))
Micha Livne (University of Toronto, Vector Institute, Seraph Computer Vision Labs)

Micha is a PhD candidate towards the end of his PhD, in the [Computational Vision Group][uoft-cv] / Artificial Intelligence Lab, part of the [Department of Computer Science][dcs] at University of Toronto, and in the [Vector Institute][vector], Toronto. He is supervised by prof. [David Fleet][fleet], and has been concentrating for the better part of the last decade on machine learning and optimization problems. Specifically on 3D video tracking combined with physical models. Micha holds a BSc. in Electrical Engineering and a BSc. in Physics from the [Technion, Israel Institute of Technology][technion], both with Summa Cum Laude honors (top 3% of his class). He obtained his MSc. from University of Toronto under [David][fleet]'s supervision, where he researched inferring attributes, such as gender, weight, happiness and anxiety level, from motion capture data and from video tracking. Micha also founded a Computer Vision/Machine Learning lab, with the goal of pushing ahead CV/ML research, while giving smaller start-ups (who typically cannot afford to hire ML researchers) accessibility to one of the biggest revolutions that mankind is about to experience. He also believes that the social aspect of that revolution is ignored, by large. As part of his efforts for a better future for all, he is working to encourage an open discussion about the social implications of the AI revolution, in order reduce fears from AI, and replace it with openness and better understanding of what possibilities lies ahead. In his spare time he enjoys hiking, canoeing, SUP, bike riding, skiing, ice skating, or basically every outdoor/indoor sport activity he finds the time to put into. [fleet]: http://www.cs.toronto.edu/~fleet [dcs]: http://web.cs.toronto.edu/ [uoft-cv]: http://www.cs.toronto.edu/vis/ [vector]: http://vectorinstitute.ai/ [seraphlabs]: http://seraphlabs.ca/ [technion]: https://www.technion.ac.il/en/

Ivan Ustyuzhaninov (University of Tübingen)
Adam Cobb (University of Oxford)
Felix D McGregor (Stellenbosch University)
Patrick McClure (NIH)
Tim R. Davidson (University of Amsterdam, Aiconic)
Gaurush Hiranandani (University of Illinois at Urbana-Champaign)
Sanjeev Arora (Princeton University)
Masha Itkina (Stanford University)
Didrik Nielsen (DTU Compute)
William Harvey (University of British Columbia)

I'm a second year PhD student at the University of British Columbia, supervised by Frank Wood. My research interests are in AI, currently focusing on how attention can improve statistical inference.

Matias Valdenegro-Toro (Heriot-Watt University)
Stefano Peluchetti (Cogent Labs)
Riccardo Moriconi (Imperial College London)
Tianyu Cui (Aalto University)
Vaclav Smidl (Institute of Information Theory and Automation)
Taylan Cemgil (DeepMind)
Jack Fitzsimons (University of Oxford)
He Zhao (Monash University)
mariana vargas vieyra (Inria Lille Nord Europe)
Apratim Bhattacharyya (Max Planck Institute for Informatics)
Rahul Sharma (IIT Kanpur)

I am currently pursuing a Ph.D. degree from IIT Kanpur in the department of Computer Science. My research interest lies in the area of Bayesian machine learning.

Geoffroy Dubourg-Felonneau (Cambridge Cancer Genomics)
Jonathan Warrell (Yale University)
Slava Voloshynovskiy (University of Geneva)
Mihaela Rosca (Google DeepMind)
Jiaming Song (Stanford University)

I am a first year Ph.D. student in Stanford University. I think about problems in machine learning and deep learning under the supervision of Stefano Ermon. I did my undergrad at Tsinghua University, where I was lucky enough to collaborate with Jun Zhu and Lawrence Carin on scalable Bayesian machine learning.

Andrew Ross (Harvard University)
Homa Fashandi (LG Electronics Toronto AI lab)
Ruiqi Gao (University of California, Los Angeles)
Hooshmand Shokri Razaghi (Columbia University)
Joshua Chang (NIH)
Zhenzhong Xiao (University of Oxford)
Vanessa Boehm (UC Berkeley)
Giorgio Giannone (NNAISENSE)

Science is built up with data, as a house is with stones. But a collection of data is no more a science than a heap of stones is a house. (J.H. Poincaré)

Ranganath Krishnan (Intel Labs)
Joe Davison (Harvard University)
Arsenii Ashukha (Samsung AI)

PhD Candidate at Bayesian Methods Research Group and Samsung AI Center Moscow supervised by Dmitriy Vetrov, working on probabilistic deep learning.

Jeremiah Liu (Google Research / Harvard)
Sicong (Sheldon) Huang (Vector Institute, University of Toronto)

I am a student of the human condition. I'm equally interested in people and machine and my long term goal is to empower the former with the latter, towards their full potential. I am interested in deep learning, statistics and information theory, cognitive neuroscience and clinical psychology, brain computer interface and machine learning for health, and music. I am currently a first year PhD Student in CS and Neuroscience at U of T and the Vector Institute advised by Prof. Marzyeh Ghassemi and Prof. Frank Rudzicz, I also work with Prof. Roger Grosse and Prof. Alireza Makhzani, more detailed and up to date information can be found in my CV

Evgenii Nikishin (Cornell University)
Sunho Park (Cleveland Clinic)
Nilesh Ahuja (Intel)
Mahesh Subedar (Intel Corporation)
Artyom Gadetsky (National Research University Higher School of Economics)
Jhosimar Arias Figueroa (Independent)
Tim G. J. Rudner (University of Oxford)
Waseem Aslam (University of Oxford)
Adrián Csiszárik (Alfred Renyi Institute of Mathematics)
John Moberg (Peltarion)
Ali Hebbal (ONERA)

PhD student at ONERA- The French Aerospace Lab

Kathrin Grosse (CISPA Helmholtz Center for Information Security)
Pekka Marttinen (Aalto University)
Bang An (State University of New York at Buffalo)
Hlynur Jónsson (IBM Zürich)
Samuel Kessler (University of Oxford)
Abhishek Kumar (Google)
Mikhail Figurnov (DeepMind)
Omesh Tickoo (Intel)
Steindor Saemundsson (Imperial College London)
Ari Heljakka (Aalto University)
Dániel Varga (Alfréd Rényi Institute of Mathematics)
Niklas Heim (Czech Technical University)
Simone Rossi (EURECOM)
Max Laves (Leibniz Universität Hannover)
Waseem Gharbieh (Element AI)
Nicholas Roberts (Carnegie Mellon University)
Luis Armando Pérez Rey (Eindhoven University of Technology)
Matthew Willetts (University of Oxford)
Prithvijit Chakrabarty (University of Massachusetts, Amherst)

I am currently an applied scientist at Amazon. I recently completed my Master's in Computer Science at University of Massachusetts, Amherst.

Sumedh Ghaisas (DeepMind)
Carl Shneider (Dutch National Center for Mathematics and Computer Science (CWI))

Carl Shneider has studied at Rensselaer Polytechnic Institute in the US, the Swiss Federal Institute of Technology (ETH Zurich) in Switzerland, the University of Cambridge in the UK, and at Utrecht University and Leiden University in the Netherlands. He currently works as a postdoc in space weather and machine learning in the Multiscale Dynamics group at the Dutch National Institute for Mathematics and Computer Science (CWI) at the Amsterdam Science Park. He holds a PhD in astrophysics from Leiden Observatory, Leiden University. After his PhD, Carl also worked in precision medicine, first at the Diagnostic Image Analysis Group (DIAG) at the Radboud University Medical Center, followed by a postdoc at the Utrecht University Medical Center where his research focused on cancer genomics and utilized techniques from bioinformatics and machine learning. Carl enjoys participating in public science outreach activities and is the event manager for the Utrecht city branch of the annual Pint of Science Public Science Festival which takes place worldwide. He also has language competencies in Russian, Spanish, German, and Dutch.

Wray Buntine (Monash University)

Wray Buntine is a full professor at Monash University where he is directory of the Machine Learning Group. He was previously at NICTA in Canberra, Helsinki Institute for Information Technology where he ran a semantic search project, NASA Ames Research Center, University of California, Berkeley, and Google. In the '90s he was involved in a string of startups for both Wall Street and Silicon Valley. He is known for Bayesian machine learning, non-parametrics and document analysis, having been a driving force in the use of ensembling, graphical models, and nonparametric algorithms.

Kamil Adamczewski (Max Planck Institute for Intelligent Systems)
Xavier Gitiaux (George Mason University)
Suwen Lin (university of notre dame)
Hao Fu (Duke University)
Gunnar Rätsch (ETH Zürich)
Aidan Gomez (Oxford University)
Erik Bodin (University of Bristol)
Dinh Phung (Monash University)
Lennart Svensson (Chalmers University of Technology, Göteborg)
Juliano Tusi Amaral Laganá Pinto (Chalmers University of Technology)
Milad Alizadeh (University of Oxford)
Jianzhun Du (Harvard University)
Kevin Murphy (Google)
Beatrix Benkő (Eötvös Loránd University)
Shashaank Vattikuti (National Institutes of Health)
Jonathan Gordon (University of Cambridge)
Christopher Kanan (Rochester Institute of Technology)

I'm an assistant professor running a lab that works on lifelong learning, low-show learning, and visual question answering. Most of my lab's work uses deep neural networks. I received my PhD from UC San Diego. I am also a Visiting Assistant Professor at Cornell Tech and a Senior AI Scientist at Paige, where I lead a team working on building deep learning systems for detecting cancer.

Sontje Ihler (Leibniz University Hanover)
Darin Graham (LG Electronics Toronto AI Lab)

Darin has over 20 years of experience leading innovative initiatives that take creative ideas to the marketplace. He brings extensive international experience in leading R&D programs and helping build innovation ecosystems in Canada, the United States, New Zealand, and the United Kingdom. A champion of collaboration, he has worked closely with a variety of unique groups to engage industry with academic and research institutions to enhance technology-based applied outcomes, particularly related to Artificial Intelligence (AI), facilitating economic growth through increasing knowledge and helping develop human capital. Darin has just taken on a new role to head-up R&D strategy and operational AI activities for LG Electronics, establishing their new lab in Toronto. Recently as a member of the founding operational team, Darin helped lead the creation and formation of the Vector Institute – the premier AI research institute in Canada. He also helped build and launch Samsung’s AI lab in Toronto. He has held the primary leadership position in a number of organizations, including ORION (Ontario's Research and Innovation Optical Network), NZi3 (New Zealand's ICT Innovation Institute), and CITO (Communications and Information Technology Ontario, an Ontario Centre of Excellence). Darin received his PhD in Aerospace Engineering from the University of Toronto, with his thesis focused on advanced neural networks for autonomous robotic control systems; MASc in Aerospace Engineering from the University of Toronto, and BMath in Computer Science and Applied Mathematics from the University of Waterloo.

Michael Teng (University of Oxford (visiting at University of British Columbia))
Louis Kirsch (The Swiss AI Lab IDSIA)
Tomas Pevny (Czech Technical University)
Taras Holotyak (University of Geneva)

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