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Poster Session
Jonathan Scarlett · Piotr Indyk · Ali Vakilian · Adrian Weller · Partha P Mitra · Benjamin Aubin · Bruno Loureiro · Florent Krzakala · Lenka Zdeborová · Kristina Monakhova · Joshua Yurtsever · Laura Waller · Hendrik Sommerhoff · Michael Moeller · Rushil Anirudh · Shuang Qiu · Xiaohan Wei · Zhuoran Yang · Jayaraman Thiagarajan · Salman Asif · Michael Gillhofer · Johannes Brandstetter · Sepp Hochreiter · Felix Petersen · Dhruv Patel · Assad Oberai · Akshay Kamath · Sushrut Karmalkar · Eric Price · Ali Ahmed · Zahra Kadkhodaie · Sreyas Mohan · Eero Simoncelli · Carlos Fernandez-Granda · Oscar Leong · Wesam Sakla · Rebecca Willett · Stephan Hoyer · Jascha Sohl-Dickstein · Samuel Greydanus · Gauri Jagatap · Chinmay Hegde · Michael Kellman · Jonathan Tamir · Nouamane Laanait · Ousmane Dia · Mirco Ravanelli · Jonathan Binas · Negar Rostamzadeh · Shirin Jalali · Tiantian Fang · Alex Schwing · Sébastien Lachapelle · Philippe Brouillard · Tristan Deleu · Simon Lacoste-Julien · Stella Yu · Arya Mazumdar · Ankit Singh Rawat · Yue Zhao · Jianshu Chen · Xiaoyang Li · Hubert Ramsauer · Gabrio Rizzuti · Nikolaos Mitsakos · Dingzhou Cao · Thomas Strohmer · Yang Li · Pei Peng · Gregory Ongie

Author Information

Jonathan Scarlett (National University of Singapore)
Piotr Indyk (MIT)
Ali Vakilian (University of Wisconsin-Madison)
Adrian Weller (Cambridge, Alan Turing Institute)

Adrian Weller is Programme Director for AI at The Alan Turing Institute, the UK national institute for data science and AI, where he is also a Turing Fellow leading work on safe and ethical AI. He is a Principal Research Fellow in Machine Learning at the University of Cambridge, and at the Leverhulme Centre for the Future of Intelligence where he is Programme Director for Trust and Society. His interests span AI, its commercial applications and helping to ensure beneficial outcomes for society. He serves on several boards including the Centre for Data Ethics and Innovation. Previously, Adrian held senior roles in finance.

Partha P Mitra (Cold Spring Harbor Laboratory)
Benjamin Aubin (Ipht Saclay)
Bruno Loureiro (IPhT Saclay)
Florent Krzakala (ENS Paris & Sorbonnes Université)
Lenka Zdeborová (CEA)
Kristina Monakhova (UC Berkeley)
Joshua Yurtsever (University of California Berkeley)
Laura Waller (UC Berkeley)
Hendrik Sommerhoff (University of Siegen)
Michael Moeller (University of Siegen)
Rushil Anirudh (Lawrence Livermore National Laboratory)
Shuang Qiu (University of Michigan)
Xiaohan Wei (University of Southern California)
Zhuoran Yang (Princeton University)
Jayaraman Thiagarajan (Lawrence Livermore National Labs)
Salman Asif (University of California, Riverside)
Michael Gillhofer (LIT AI Lab, Institute for Machine Learning, Johannes Kepler University Linz, Austria)
Johannes Brandstetter (LIT AI Lab / University Linz)
Sepp Hochreiter (LIT AI Lab / University Linz / IARAI)
Felix Petersen (University of Konstanz)
Dhruv Patel (University of Southern California)
Assad Oberai (University of Southern California)
Akshay Kamath (The University of Texas at Austin)
Sushrut Karmalkar (The University of Texas at Austin)
Eric Price (University of Texas at Austin)
Ali Ahmed (Information Technology University)
Zahra Kadkhodaie (New York University)
Sreyas Mohan (NYU)
Eero Simoncelli (HHMI / New York University)

Eero P. Simoncelli received the B.S. degree in Physics in 1984 from Harvard University, studied applied mathematics at Cambridge University for a year and a half, and then received the M.S. degree in 1988 and the Ph.D. degree in 1993, both in Electrical Engineering from the Massachusetts Institute of Technology. He was an Assistant Professor in the Computer and Information Science department at the University of Pennsylvania from 1993 until 1996. He moved to New York University in September of 1996, where he is currently a Professor in Neural Science, Mathematics, and Psychology. In August 2000, he became an Associate Investigator of the Howard Hughes Medical Institute, under their new program in Computational Biology. His research interests span a wide range of topics in the representation and analysis of visual images, in both machine and biological systems.

Carlos Fernandez-Granda (NYU)
Oscar Leong (Rice University)
Wesam Sakla (Lawrence Livermore National Laboratory)
Rebecca Willett (U Chicago)
Stephan Hoyer (Google Research)
Jascha Sohl-Dickstein (Google Brain)
Samuel Greydanus (Oregon State University)

I am a recent graduate of Dartmouth College, where I majored in physics and dabbled in everything else. I have interned at CERN, Microsoft Azure, and the DARPA Explainable AI Project. I like to use memory-based models to generate sequences and policies. So far, I have used them to approximate the Enigma cipher, generate realistic handwriting, and visualize how reinforcement-learning agents play Atari games. One of my priorities as a scientist is to explain my work clearly and make it easy to replicate.

Gauri Jagatap (Iowa State University)

Graduate student at Iowa State University

Chinmay Hegde (Iowa State University)
Michael Kellman (University of California Berkeley)

I am a PhD graduate student at UC Berkeley in the EECS department, where I work on problems in the fields of signal processing, computational imaging, and machine learning. I am advised by Prof. Laura Waller and Prof. Michael Lustig and am funded by NSF GRFP. I am also affiliated with the Berkeley Artificial Intelligence Research Laboratory and the Berkeley Center for Computational Imaging. In broadest terms, the goal of my research is to improve the limitation of modern computational imaging systems through data-driven design. I'm particularly interested in the areas of signal processing, machine learning theory, image reconstruction algorithms, and optical modeling. Specifically, my work is focused on the applications of microscopy, medical imaging, and photography.

Jonathan Tamir (University of California, Berkeley)
Nouamane Laanait (Oak Ridge National Laboratory)
Ousmane Dia (Element AI)
Mirco Ravanelli (Montreal Istitute for Learning Algorithms)

I received my master's degree in Telecommunications Engineering (full marks and honours) from the University of Trento, Italy in 2011. I then joined the SHINE research group (led by Prof. Maurizio Omologo) of the Bruno Kessler Foundation (FBK), contributing to some projects on distant-talking speech recognition in noisy and reverberant environments, such as DIRHA and DOMHOS. In 2013 I was visiting researcher at the International Computer Science Institute (University of California, Berkeley) working on deep neural networks for large-vocabulary speech recognition in the context of the IARPA BABEL project (led by Prof. Nelson Morgan). I received my PhD (with cum laude distinction) in Information and Communication Technology from the University of Trento in December 2017. During my PhD I worked on “deep learning for distant speech recognition”, with a particular focus on recurrent and cooperative neural networks (see my PhD thesis here). In the context of my PhD I recently spent 6 months in the MILA lab led by Prof. Yoshua Bengio. I'm currently a post-doc researcher at the University of Montreal, working on deep learning for speech recognition in the MILA Lab.

Jonathan Binas (Mila, Montreal)
Negar Rostamzadeh (Elemenet AI)
Shirin Jalali (Nokia Bell Labs)
Tiantian Fang (University of Illinois Urbana-Champaign)
Alex Schwing (University of Illinois at Urbana-Champaign)
Sébastien Lachapelle (Mila, Université de Montréal)
Philippe Brouillard (Université de Montréal)
Tristan Deleu (Mila - Universite de Montreal)
Simon Lacoste-Julien (Mila, Université de Montréal)

Simon Lacoste-Julien is an associate professor at Mila and DIRO from Université de Montréal, and Canada CIFAR AI Chair holder. He also heads part time the SAIT AI Lab Montreal from Samsung. His research interests are machine learning and applied math, with applications in related fields like computer vision and natural language processing. He obtained a B.Sc. in math., physics and computer science from McGill, a PhD in computer science from UC Berkeley and a post-doc from the University of Cambridge. He spent a few years as a research faculty at INRIA and École normale supérieure in Paris before coming back to his roots in Montreal in 2016 to answer the call from Yoshua Bengio in growing the Montreal AI ecosystem.

Stella Yu (UC Berkeley / ICSI)
Arya Mazumdar (University of Massachusetts Amherst)
Ankit Singh Rawat (Google Research)
Yue Zhao (Stony Brook University)
Jianshu Chen (Tencent AI Lab)
Xiaoyang Li (University of Houston)
Hubert Ramsauer (LIT AI Lab / University Linz)
Gabrio Rizzuti (Georgia Institute of Technology)
Nikolaos Mitsakos (Anadarko Petroleum - OXY)
Dingzhou Cao (Occidental)
Thomas Strohmer (University of California, Davis)
Yang Li (Facebook)
Pei Peng (Rutgers, the State University of New Jersey)
Gregory Ongie (University of Chicago)

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