Author Information

Shuangjia Zheng (SUN YAT-SEN UNIVERSITY)

Arnav Kapur (MIT)

Umar Asif (IBM Research Australia)

Eyal Rozenberg (Technion - Israel Institute of Technology)

Cyprien Gilet (University of Côte d'Azur CNRS, I3S Laboratory)

Oleksii Sidorov (Facebook)

Yogesh Kumar (Aalto University)

Doctoral Student working on Machine Learning at Aalto University, Finland

Tom Van Steenkiste (Ghent university - imec)

William Boag (MIT)

David Ouyang (Stanford University)

Paul Jaeger (German Cancer Research Center (DKFZ))

Sheng Liu (New York University)

Aparna Balagopalan (University of Toronto / WinterLight Labs)

Deepta Rajan (IBM Research)

Marta Skreta (University of Toronto)

Nikhil Pattisapu (IIIT Hyderabad)

Jann Goschenhofer (Ludwig-Maximilians-University Munich)

Viraj Prabhu (Georgia Tech)

I am a fourth year CS Ph.D. student at Georgia Tech, advised by Judy Hoffman. My research interests are in developing data-efficient and reliable computer vision systems that can be deployed in the real world. Specifically, I am interested in sample-efficient learning (particularly few-shot and active learning), adaptation across visual tasks and domains, and reliable and calibrated uncertainty estimation from deep neural networks.

Di Jin (MIT)

Laura-Jayne Gardiner (IBM Research UK)

Dr. Laura-Jayne Gardiner is a computational biologist with a background in molecular biology . Laura develops tools and pipelines to analyse large scale next-generation sequencing (NGS) datasets for life science research. Currently, Laura is a Postdoctoral Researcher at IBM Research UK within the life sciences team and is applying machine learning to genomics datasets to make predictions, tackling issues of resource integration and large-scale network analysis.

Irene Li (Yale University)

sriram kumar (PerceptiMed)

Qiyuan Hu (University of Chicago)

Mehul Motani (National University of Singapore)

Mehul Motani received the B.E. degree from Cooper Union, New York, NY, the M.S. degree from Syracuse University, Syracuse, NY, and the Ph.D. degree from Cornell University, Ithaca, NY, all in Electrical and Computer Engineering. Dr. Motani is currently an Associate Professor in the Electrical and Computer Engineering Department at the National University of Singapore (NUS) and a Visiting Research Collaborator at Princeton University. Previously, he was a Visiting Fellow at Princeton University. He was also a Research Scientist at the Institute for Infocomm Research in Singapore, for three years, and a Systems Engineer at Lockheed Martin in Syracuse, NY for over four years. His research interests include information theory, machine learning, wireless and sensor networks, and energy harvesting communications. Dr. Motani was the recipient of the Intel Foundation Fellowship for his Ph.D. research, the NUS Annual Teaching Excellence Award, the NUS Faculty of Engineering Innovative Teaching Award, and the NUS Faculty of Engineering Teaching Honours List Award. He actively participates in the Institute of Electrical and Electronics Engineers (IEEE) and the Association for Computing Machinery (ACM). He is a Fellow of the IEEE and has served as the Secretary of the IEEE Information Theory Society Board of Governors. He has served as an Associate Editor for both the IEEE Transactions on Information Theory and the IEEE Transactions on Communications. He has also served on the Organizing and Technical Program Committees of numerous IEEE and ACM conferences.

Justin Lovelace (Texas A&M University)

Usman Roshan (New Jersey Institute of Technology)

Lucy Lu Wang (Allen Institute for Artificial Intelligence (AI2))

Ilya Valmianski (Kaiser Permanente)

I am a Physicist turned Machine Learning Scientist. My current work is focused on developing deep learning models for natural language processing of free text in Electronic Health Records (EHR). Clinical notes present a special challenge for NLP as they often contain many idiosyncratic abbreviations, technical terms, and incomplete sentence structure. This makes it very hard to process using classical techniques. At KP, we have one of the largest in the world EHR clinical note corpora, which allows us to leverage Deep Learning techniques and achieve state of the art performance on auditing and clinical decision support tasks.

Hyeonwoo Lee (Allen Institute for Cell Science)

Sunil Mallya (AWS)

Elias Chaibub Neto (Sage Bionetworks)

Jonas Kemp (Google Health)

Marie Charpignon (MIT)

Marie grew up in Burgundy, France and studied engineering in Paris. She moved to the US to study Computational and Mathematical Engineering at Stanford University for her master’s (’16). She is passionate about statistics for education and healthcare. After graduation, she joined Microsoft as a data scientist focusing on education technology. There, she built models to better understand online collaboration, studied the impact of technology usage at school and organized workshops for high school girls. She is currently a second-year graduate student in the MIT PhD program in Social & Engineering Systems. Her work on causal inference for drug repurposing using Electronic Health Records combines mathematical modelling, data analysis and policy.

Amber Nigam (Georgia Institute of Technology)

Wei-Hung Weng (MIT)

Sabri Boughorbel (Sidra Medicine)

Alexis Bellot (University of Cambridge / Alan Turing Institute)

Lovedeep Gondara (Simon Fraser University)

Haoran Zhang (University of Toronto)

Taha Bahadori (Amazon)

John Zech (Columbia University Medical Center)

Rulin Shao (Xi'an Jiaotong University)

Edward Choi (Google)

Laleh Seyyed-Kalantari (University of Toronto)

Emily Aiken (University of California, Berkeley)

Ioana Bica (University of Oxford)

Yiqiu Shen (New York University)

Kieran Chin-Cheong (ETH Zurich)

Subhrajit Roy (Google)

Ioana Baldini (IBM Research)

So Yeon Min (MIT)

Dirk Deschrijver (Ghent University)

Pekka Marttinen (Aalto University)

Damian Pascual Ortiz (ETH Zurich)

Supriya Nagesh (Georgia Institute of Technology)

Niklas Rindtorff (Harvard Medical School, DKFZ Heidelberg)

Niklas Rindtorff, MBI, is a joint MD/PhD student at the Max Planck Institute for Medical Research and the German Cancer Research Center, Heidelberg. Here he combines high-throughput drug testing, image analysis and patient derived organoids to study treatment responses of heterogenous cancer models ex-vivo. His prior research at the Broad Institute, the German Cancer Research Center and the ETH Zurich is focused on improving treatment recommendations in precision oncology based on uncertainty-aware predictive algorithms, functional drug testing of patient derived cancer samples, allele-specific genome editing and microscopy image analysis. As a Fulbright scholar, he received a masters degree in biomedical informatics from Harvard Medical School in 2019. The title of his thesis under Jesse Boehm at the Broad Institute was: "Living Biosensors: Predicting Drug Vulnerabilities from Living Tumor Samples by Single-Cell, Label-free imaging. Niklas is a member of the MIT Critical Data initiative and regularly co-organizes Healthcare Datathon events across Europe. Having led a student-run retail company during medical school, he plans to work at the intersection of the digital health and pharmaceutical industry after completion of his clinical training.

Andriy Mulyar (Virginia Commonwealth University)

undergraduate researcher in language processing and machine learning

Katharina Hoebel (Massachusetts Institute of Technology)

Martha Shaka (The University of Dodoma)

Pierre Machart (Universitätsklinikum Hamburg-Eppendorf / ZMNH / Institute for Medical Systems Biology)

Machine Learning researcher currently in a post-doc, focusing on developping and using cutting edge Machine Learning methods (deep generative models) to solve complex biomedical problems (augmentation, debiasing, prediction of unseen events on omics data).

Leon Gatys (Apple)

Nathan Ng (University of Toronto)

I am a first year PhD student with Prof. Marzyeh Ghassemi. I am broadly interested in NLP and machine learning for healthcare. Specifically I am interested in building systems that can understand and build intelligent representations of noisy or unstructured text, especially in a clinical setting.

Matthias Hüser (ETH Zürich)

Devin Taylor (University of Cambridge)

Master's student focussing on the application of machine learning to medicine. Specific interests include cross-modal deep learning and interpretability in deep learning.

Dennis Barbour (Washington University in St. Louis)

Natalia Martinez (Duke University)

Clara McCreery (Stanford University)

Clara McCreery is a master's student in computer science at Stanford University, graduating in June 2020. Her research focuses on how re-structuring data can be used to improve machine learning models. In addition to computer science and data science, Clara enjoys racing with the Stanford Triathlon team and playing the violin.

Benjamin Eyre (Winterlight Labs)

Vivek Natarajan (Google Brain)

Working on AI + healthcare at Google AI Brain. Previously: Facebook AI Research (FAIR) Engineer where I worked on speech, conversational AI and multimodal models

Ren Yi (New York University)

Ruibin Ma (University of North Carolina at Chapel Hill)

I am a PhD student in CS Department of UNC-Chapel Hill. My research interest is in medical image analysis and 3D computer vision.

Chirag Nagpal (Carnegie Mellon University)

Nan Du (Google Brain)

Chufan Gao (Carnegie Mellon Univeristy)

Anup Tuladhar (University of Calgary)

My focus is on machine learning solutions for medicine, with specific focus on convolutional neural networks and distributed learning. I come from an alternative background: My PhD thesis was on a biomaterials-based drug delivery system for local drug release in the stroke-injured brain.

Sam Shleifer (Stanford University)

Jason Ren (Harvard University)

Pouria Mashouri (The Hospital For Sick Children)

Ming Yang Lu (Pathology, Brigham and Women's Hospital, Harvard Medical School)

Farideh Bagherzadeh-Khiabani (University of Alberta)

Olivia Choudhury (IBM Research)

I am a postdoctoral researcher at IBM Research Cambridge. My areas of interest include federated learning, blockchain technology, healthcare informatics, cloud computing, data privacy, and genomics. My current research focuses on developing privacy-preserving federated learning models to analyze large-scale distributed data. I am also interested in blockchain technology and its application in healthcare and composite cloud solutions. I am a Visiting Scientist at the Broad Institute of MIT and Harvard, where I am designing methods to improve the predictive power of polygenic risk scores to help clinicians identify patients at serious risk for cardiovascular disease. I received my Ph.D. in Computer Science and Engineering from University of Notre Dame, IN. My doctoral thesis focused on designing cloud computing-based infrastructures to expedite analysis and learning-based algorithms to improve quality of large-scale genomic data. Prior to joining IBM Research, I worked at the Broad Institute of MIT and Harvard on comparative genomics to control Zika outbreak. During my internship at IBM Watson, I built automated tools to optimize cloud-based resource allocation for SoftLayer Infrastructure as a Service (IaaS) and deploy Watson applications (Watson Oncology and Watson Engagement Advisor) on the cloud.

Maithra Raghu (Cornell University and Google Brain)

Scott Fleming (Stanford University)

Mika Jain (Stanford University)

GUO YANG (A*STAR)

Alena Harley (Human Longevity Inc)

Stephen Pfohl (Stanford University)

Elisabeth Rumetshofer (LIT AI Lab / University Linz)

Alex Fedorov (Georgia Institute of Technology)

Saloni Dash (Birla Institute of Technology and Science Pilani - K.K. Birla Goa Campus)

Jacob Pfau (UCSF)

Sabina Tomkins (Stanford University)

Colin Targonski (JP Morgan Chase)

Michael Brudno (University of Toronto)

Xinyu Li (Carnegie Mellon University)

Yiyang Yu (University Paris Diderot)

Nisarg Patel (University of California, San Francisco)

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  Rameswar Panda · Prasanna Sattigeri · Kush Varshney · Karthikeyan Natesan Ramamurthy · Harvineet Singh · Vishwali Mhasawade · Shalmali Joshi · Laleh Seyyed-Kalantari · Matthew McDermott · Gal Yona · James Atwood · Hansa Srinivasan · Yonatan Halpern · D. Sculley · Behrouz Babaki · Margarida Carvalho · Josie Williams · Narges Razavian · Haoran Zhang · Amy Lu · Irene Y Chen · Xiaojie Mao · Angela Zhou · Nathan Kallus
• 2019 : Break / Poster Session 1 »
  Antonia Marcu · Yao-Yuan Yang · Pascale Gourdeau · Chen Zhu · Thodoris Lykouris · Jianfeng Chi · Mark Kozdoba · Arjun Nitin Bhagoji · Xiaoxia Wu · Jay Nandy · Michael T Smith · Bingyang Wen · Yuege Xie · Konstantinos Pitas · Suprosanna Shit · Maksym Andriushchenko · Dingli Yu · Gaël Letarte · Misha Khodak · Hussein Mozannar · Chara Podimata · James Foulds · Yizhen Wang · Huishuai Zhang · Ondrej Kuzelka · Alexander Levine · Nan Lu · Zakaria Mhammedi · Paul Viallard · Diana Cai · Lovedeep Gondara · James Lucas · Yasaman Mahdaviyeh · Aristide Baratin · Rishi Bommasani · Alessandro Barp · Andrew Ilyas · Kaiwen Wu · Jens Behrmann · Omar Rivasplata · Amir Nazemi · Aditi Raghunathan · Will Stephenson · Sahil Singla · Akhil Gupta · YooJung Choi · Yannic Kilcher · Clare Lyle · Edoardo Manino · Andrew Bennett · Zhi Xu · Niladri Chatterji · Emre Barut · Flavien Prost · Rodrigo Toro Icarte · Arno Blaas · Chulhee Yun · Sahin Lale · YiDing Jiang · Tharun Kumar Reddy Medini · Ashkan Rezaei · Alexander Meinke · Stephen Mell · Gary Kazantsev · Shivam Garg · Aradhana Sinha · Vishnu Lokhande · Geovani Rizk · Han Zhao · Aditya Kumar Akash · Jikai Hou · Ali Ghodsi · Matthias Hein · Tyler Sypherd · Yichen Yang · Anastasia Pentina · Pierre Gillot · Antoine Ledent · Guy Gur-Ari · Noah MacAulay · Tianzong Zhang
• 2019 : Coffee break, posters, and 1-on-1 discussions »
  Yangyi Lu · Daniel Chen · Hongseok Namkoong · Marie Charpignon · Maja Rudolph · Amanda Coston · Julius von Kügelgen · Niranjani Prasad · Paramveer Dhillon · Yunzong Xu · Yixin Wang · Alexander Markham · David Rohde · Rahul Singh · Zichen Zhang · Negar Hassanpour · Ankit Sharma · Ciarán Lee · Jean Pouget-Abadie · Jesse Krijthe · Divyat Mahajan · Nan Rosemary Ke · Peter Wirnsberger · Vira Semenova · Dmytro Mykhaylov · Dennis Shen · Kenta Takatsu · Liyang Sun · Jeremy Yang · Alexander Franks · Pak Kan Wong · Tauhid Zaman · Shira Mitchell · min kyoung kang · Qi Yang
• 2019 : Coffee Break + Poster Session I »
  Wei-Hung Weng · Simon Kohl · Aiham Taleb · Arijit Patra · Khashayar Namdar · Matthias Perkonigg · Shizhan Gong · Abdullah-Al-Zubaer Imran · Amir Abdi · Ilja Manakov · Johannes C. Paetzold · Ben Glocker · Dushyant Sahoo · Shreyas Fadnavis · Karsten Roth · Xueqing Liu · Yifan Zhang · Alexander Preuhs · Fabian Eitel · Anusua Trivedi · Tomer Weiss · Darko Stern · Liset Vazquez Romaguera · Johannes Hofmanninger · Aakash Kaku · Oloruntobiloba Olatunji · Anastasia Razdaibiedina · Tao Zhang
• 2019 : Poster Spotlights »
  Hongseok Namkoong · Marie Charpignon · Maja Rudolph · Amanda Coston · Yuta Saito · Paramveer Dhillon · Alexander Markham
• 2019 : Oral Session I – Methods »
  Wei-Hung Weng · Simon Kohl · Arijit Patra
• 2019 : Poster Session »
  Gergely Flamich · Shashanka Ubaru · Charles Zheng · Josip Djolonga · Kristoffer Wickstrøm · Diego Granziol · Konstantinos Pitas · Jun Li · Robert Williamson · Sangwoong Yoon · Kwot Sin Lee · Julian Zilly · Linda Petrini · Ian Fischer · Zhe Dong · Alexander Alemi · Bao-Ngoc Nguyen · Rob Brekelmans · Tailin Wu · Aditya Mahajan · Alexander Li · Kirankumar Shiragur · Yair Carmon · Linara Adilova · SHIYU LIU · Bang An · Sanjeeb Dash · Oktay Gunluk · Arya Mazumdar · Mehul Motani · Julia Rosenzweig · Michael Kamp · Marton Havasi · Leighton P Barnes · Zhengqing Zhou · Yi Hao · Dylan Foster · Yuval Benjamini · Nati Srebro · Michael Tschannen · Paul Rubenstein · Sylvain Gelly · John Duchi · Aaron Sidford · Robin Ru · Stefan Zohren · Murtaza Dalal · Michael A Osborne · Stephen J Roberts · Moses Charikar · Jayakumar Subramanian · Xiaodi Fan · Max Schwarzer · Nicholas Roberts · Simon Lacoste-Julien · Vinay Prabhu · Aram Galstyan · Greg Ver Steeg · Lalitha Sankar · Yung-Kyun Noh · Gautam Dasarathy · Frank Park · Ngai-Man (Man) Cheung · Ngoc-Trung Tran · Linxiao Yang · Ben Poole · Andrea Censi · Tristan Sylvain · R Devon Hjelm · Bangjie Liu · Jose Gallego-Posada · Tyler Sypherd · Kai Yang · Jan Nikolas Morshuis
• 2019 : Poster Session »
  Nathalie Baracaldo · Seth Neel · Tuyen Le · Dan Philps · Suheng Tao · Sotirios Chatzis · Toyo Suzumura · Wei Wang · WENHANG BAO · Solon Barocas · Manish Raghavan · Samuel Maina · Reginald Bryant · Kush Varshney · Skyler D. Speakman · Navdeep Gill · Nicholas Schmidt · Kevin Compher · Naveen Sundar Govindarajulu · Vivek Sharma · Praneeth Vepakomma · Tristan Swedish · Jayashree Kalpathy-Cramer · Ramesh Raskar · Shihao Zheng · Mykola Pechenizkiy · Marco Schreyer · Li Ling · Chirag Nagpal · Robert Tillman · Manuela Veloso · Hanjie Chen · Xintong Wang · Michael Wellman · Matthew van Adelsberg · Ben Wood · Hans Buehler · Mahmoud Mahfouz · Antonios Alexos · Megan Shearer · Antigoni Polychroniadou · Lucia Larise Stavarache · Dmitry Efimov · Johnston P Hall · Yukun Zhang · Emily Diana · Sumitra Ganesh · Vineeth Ravi · · Swetasudha Panda · Xavier Renard · Matthew Jagielski · Yonadav Shavit · Joshua Williams · Haoran Wei · Shuang (Sophie) Zhai · Xinyi Li · Hongda Shen · Daiki Matsunaga · Jaesik Choi · Alexis Laignelet · Batuhan Guler · Jacobo Roa Vicens · Ajit Desai · Jonathan Aigrain · Robert Samoilescu
• 2019 : Poster Spotlights B (13 posters) »
  Alberto Camacho · Chris Percy · Vaishak Belle · Beliz Gunel · Toryn Klassen · Tillman Weyde · Mohamed Ghalwash · Siddhant Arora · León Illanes · Jonathan Raiman · Qing Wang · Alexander Lew · So Yeon Min
• 2019 : Spotlight Paper Talks »
  Eyal Rozenberg · Jerry Wei · Xiaojing Xu
• 2019 : Poster Session »
  Rishav Chourasia · Yichong Xu · Corinna Cortes · Chien-Yi Chang · Yoshihiro Nagano · So Yeon Min · Benedikt Boecking · Phi Vu Tran · Kamyar Ghasemipour · Qianggang Ding · Shouvik Mani · Vikram Voleti · Rasool Fakoor · Miao Xu · Kenneth Marino · Lisa Lee · Volker Tresp · Jean-Francois Kagy · Marvin Zhang · Barnabas Poczos · Dinesh Khandelwal · Adrien Bardes · Evan Shelhamer · Jiacheng Zhu · Ziming Li · Xiaoyan Li · Dmitrii Krasheninnikov · Ruohan Wang · Mayoore Jaiswal · Emad Barsoum · Suvansh Sanjeev · Theeraphol Wattanavekin · Qizhe Xie · Sifan Wu · Yuki Yoshida · David Kanaa · Sina Khoshfetrat Pakazad · Mehdi Maasoumy
• 2019 : Paper spotlight talks »
  Umar Asif · Paul Jaeger
• 2019 : AI Driving Olympics 3 »
  Caglayan Dicle · Liam Paull · Jacopo Tani · Sunil Mallya · Sahika Genc · Kirsten Bowser · Tao Sun · Yunzhe Tao · Philippe Marcotte · Hsu-kuang Chiu · Eric Wolff
• 2019 : 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
• 2019 : Spotlight Paper Talks »
  Arnav Kapur · Maithra Raghu · Xinyu Li
• 2019 Poster: Park: An Open Platform for Learning-Augmented Computer Systems »
  Hongzi Mao · Parimarjan Negi · Akshay Narayan · Hanrui Wang · Jiacheng Yang · Haonan Wang · Ryan Marcus · Ravichandra Addanki · Mehrdad Khani Shirkoohi · Songtao He · Vikram Nathan · Frank Cangialosi · Shaileshh Venkatakrishnan · Wei-Hung Weng · Song Han · Tim Kraska · Dr.Mohammad Alizadeh
• 2019 Poster: Transfusion: Understanding Transfer Learning for Medical Imaging »
  Maithra Raghu · Chiyuan Zhang · Jon Kleinberg · Samy Bengio
• 2019 Poster: Conditional Independence Testing using Generative Adversarial Networks »
  Alexis Bellot · Mihaela van der Schaar
• 2019 Spotlight: Conditional Independence Testing using Generative Adversarial Networks »
  Alexis Bellot · Mihaela van der Schaar
• 2018 : Poster Session »
  Phillipp Schoppmann · Patrick Yu · Valerie Chen · Travis Dick · Marc Joye · Ningshan Zhang · Frederik Harder · Olli Saarikivi · Théo Ryffel · Yunhui Long · Théo JOURDAN · Di Wang · Antonio Marcedone · Negev Shekel Nosatzki · Yatharth A Dubey · Antti Koskela · Peter Bloem · Aleksandra Korolova · Martin Bertran · Hao Chen · Galen Andrew · Natalia Martinez · Janardhan Kulkarni · Jonathan Passerat-Palmbach · Guillermo Sapiro · Amrita Roy Chowdhury
• 2018 : Live competition The AI Driving Olympics: AWS and Sagemaker as enablers in the competition »
  Sunil Mallya
• 2018 : Lunch »
  Hong Yu · Bhanu Pratap Singh Rawat · Arijit Ukil · Waheeda Saib · Jekaterina Novikova · John Hughes · Yuhui Zhang · Rahul V · Mi Jung Kim · Babak Taati · Hariharan Ravishankar · Harry Clifford · Hirofumi Kobayashi · Babak Taati · Keyang Xu · Yen-Chi Cheng · Timothy Cannings · Jayashree Kalpathy-Cramer · Jayashree Kalpathy-Cramer · Parinaz Sobhani · Kimis Perros · Wei-Hung Weng · Yordan Raykov · Lars Lorch · Mengqi Jin · Xue Teng · Michael Ferlaino · Marek Rei · Cédric Beaulac · Aman Verma · Sebastian Keller · Edmond Cunningham · Luc Evers · Victor Rodriguez · Vipul Satone · Dianbo Liu · Angeline Yasodhara · Geoff Tison · Ligin Solamen · Bryan He · Rahul Ladhania · Yipeng Shi · Md Nafiz Hamid · Pouria Mashouri · Woochan Hwang · Sejin Park · Xu Chen · Rachneet Kaur · Davis Blalock · Holly Wiberg · Parminder Bhatia · Kezi Yu · RUMENG LI · Jun Sakuma · Charles Ding · Aaron Babier · Yong Cai · A Pratap · Luke O'Connor · Allen Nie · Martin Kang · Ian Covert · Xun Wang · Zelun Luo · Serena Yeung · William Boag · Kazuki Tachikawa · Mary Saltz · Owen Lahav · Edward Lee · Eric Teasley · Michael Kamp · Nirmesh Patel · Vishwali Mhasawade · Maxim Samarin · Ryo Uchimido · Farzad Khalvati · Francisco Cruz · Laura Symul · Zaid Nabulsi · Mads Mihailescu · Rosalind Picard
• 2018 : Poster session: Contributed papers »
  Michael Cvitkovic · Arijit Patra · Yunpeng Li · RAHMAN BANYA SAFF SANYA · Guanghua Chi · Benjamin Huynh · Hamed Alemohammad · Simón Ramírez Amaya · Nazmus Saquib · Jade Abbott · Teo de Campos · Viraj Prabhu · Alvaro Riascos · Hafte Abera · praney dubey · Tanushyam Chattopadhyay · Hsiang Hsu · Mayank Jain · Kartikeya Bhardwaj · Gabriel Cadamuro · Bradley Gram-Hansen · Georg Dorffner
• 2018 : Poster Session I »
  Aniruddh Raghu · Daniel Jarrett · Kathleen Lewis · Elias Chaibub Neto · Nicholas Mastronarde · Shazia Akbar · Chun-Hung Chao · Henghui Zhu · Seth Stafford · Luna Zhang · Jen-Tang Lu · Changhee Lee · Adityanarayanan Radhakrishnan · Fabian Falck · Liyue Shen · Daniel Neil · Yusuf Roohani · Aparna Balagopalan · Brett Marinelli · Hagai Rossman · Sven Giesselbach · Jose Javier Gonzalez Ortiz · Edward De Brouwer · Byung-Hoon Kim · Rafid Mahmood · Tzu Ming Hsu · Antonio Ribeiro · Rumi Chunara · Agni Orfanoudaki · Kristen Severson · Mingjie Mai · Sonali Parbhoo · Albert Haque · Viraj Prabhu · Di Jin · Alena Harley · Geoffroy Dubourg-Felonneau · Xiaodan Hu · Maithra Raghu · Jonathan Warrell · Nelson Johansen · Wenyuan Li · Marko Järvenpää · Satya Narayan Shukla · Sarah Tan · Vincent Fortuin · Beau Norgeot · Yi-Te Hsu · Joel H Saltz · Veronica Tozzo · Andrew Miller · Guillaume Ausset · Azin Asgarian · Francesco Paolo Casale · Antoine Neuraz · Bhanu Pratap Singh Rawat · Turgay Ayer · Xinyu Li · Mehul Motani · Nathaniel Braman · Laetitia M Shao · Adrian Dalca · Hyunkwang Lee · Emma Pierson · Sandesh Ghimire · Yuji Kawai · Owen Lahav · Anna Goldenberg · Denny Wu · Pavitra Krishnaswamy · Colin Pawlowski · Arijit Ukil · Yuhui Zhang
• 2018 : Spotlight talks (session 3) »
  Farzaneh Mahdisoltani · Frederik Kratzert · SUBBAREDDY OOTA · Mehul Motani · Tryambak Gangopadhyay · Sathwik Tejaswi Madhusudhan · Marc Rußwurm · Mahta Mousavi · Mihir Jain
• 2018 Poster: Multitask Boosting for Survival Analysis with Competing Risks »
  Alexis Bellot · Mihaela van der Schaar
• 2018 Poster: Insights on representational similarity in neural networks with canonical correlation »
  Ari Morcos · Maithra Raghu · Samy Bengio
• 2018 Poster: MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare »
  Edward Choi · Cao Xiao · Walter Stewart · Jimeng Sun
• 2018 Poster: Learning Temporal Point Processes via Reinforcement Learning »
  Shuang Li · Shuai Xiao · Shixiang Zhu · Nan Du · Yao Xie · Le Song
• 2018 Spotlight: Learning Temporal Point Processes via Reinforcement Learning »
  Shuang Li · Shuai Xiao · Shixiang Zhu · Nan Du · Yao Xie · Le Song
• 2018 Poster: Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces »
  Yu-An Chung · Wei-Hung Weng · Schrasing Tong · Jim Glass
• 2018 Spotlight: Unsupervised Cross-Modal Alignment of Speech and Text Embedding Spaces »
  Yu-An Chung · Wei-Hung Weng · Schrasing Tong · Jim Glass
• 2017 : Poster session - Afternoon »
  Yongchan Kwon · Young-geun Kim · Ender Konukoglu · Peter Li · John Guibas · Tejpal Virdi · Kuldeep Kumar · Morteza Mardani · Jelmer Wolterink · Enhao Gong · Natalia Antropova · Johannes Stelzer · Rene Bidart · Wei-Hung Weng · Martin Rajchl · Marc Górriz · Vineeta Singh · Christopher Sandino · Hiba Chougrad · Bob Hu · Isaac Godfried · Ke Xiao · Heliodoro Tejeda Lemus · Jordan Harrod · ILSANG WOO · Vincent Chen · Joseph Cheng · Vikash Gupta · Chuck-Hou Yee · Ben Glocker · Hervé Lombaert · Maximilian Ilse · Aneta Lisowska · Andrew Doyle · Milad Makkie
• 2017 : Contributed Talks 1 »
  Cinjon Resnick · Ying Wen · Stephan Zheng · Mukul Bhutani · Edward Choi
• 2017 : Poster session - Morning »
  Yongchan Kwon · Young-geun Kim · Ender Konukoglu · Peter Li · John Guibas · Tejpal Virdi · Kuldeep Kumar · Morteza Mardani · Jelmer Wolterink · Enhao Gong · Natalia Antropova · Johannes Stelzer · Rene Bidart · Wei-Hung Weng · Martin Rajchl · Marc Górriz · Vineeta Singh · Christopher Sandino · Hiba Chougrad · Bob Hu · Isaac Godfried · Ke Xiao · Heliodoro Tejeda Lemus · Jordan Harrod · ILSANG WOO · Vincent Chen · Joseph Cheng · Vikash Gupta · Chuck-Hou Yee · Ben Glocker · Hervé Lombaert · Maximilian Ilse · Aneta Lisowska · Andrew Doyle · Milad Makkie
• 2017 Workshop: Deep Learning: Bridging Theory and Practice »
  Sanjeev Arora · Maithra Raghu · Russ Salakhutdinov · Ludwig Schmidt · Oriol Vinyals
• 2017 : DeepArt competition »
  Alexander Ecker · Leon A Gatys · Matthias Bethge
• 2017 : Coffee break and Poster Session I »
  Nishith Khandwala · Steve Gallant · Gregory Way · Aniruddh Raghu · Li Shen · Aydan Gasimova · Alican Bozkurt · William Boag · Daniel Lopez-Martinez · Ulrich Bodenhofer · Samaneh Nasiri GhoshehBolagh · Michelle Guo · Christoph Kurz · Kirubin Pillay · Kimis Perros · George H Chen · Alexandre Yahi · Madhumita Sushil · Sanjay Purushotham · Elena Tutubalina · Tejpal Virdi · Marc-Andre Schulz · Samuel Weisenthal · Bharat Srikishan · Petar Veličković · Kartik Ahuja · Andrew Miller · Erin Craig · Disi Ji · Filip Dabek · Chloé Pou-Prom · Hejia Zhang · Janani Kalyanam · Wei-Hung Weng · Harish Bhat · Hugh Chen · Simon Kohl · Mingwu Gao · Tingting Zhu · Ming-Zher Poh · Iñigo Urteaga · Antoine Honoré · Alessandro De Palma · Maruan Al-Shedivat · Pranav Rajpurkar · Matthew McDermott · Vincent Chen · Yanan Sui · Yun-Geun Lee · Li-Fang Cheng · Chen Fang · Sibt ul Hussain · Cesare Furlanello · Zeev Waks · Hiba Chougrad · Hedvig Kjellstrom · Finale Doshi-Velez · Wolfgang Fruehwirt · Yanqing Zhang · Lily Hu · Junfang Chen · Sunho Park · Gatis Mikelsons · Jumana Dakka · Stephanie Hyland · yann chevaleyre · Hyunwoo Lee · Xavier Giro-i-Nieto · David Kale · Michael Hughes · Gabriel Erion · Rishab Mehra · William Zame · Stojan Trajanovski · Prithwish Chakraborty · Kelly Peterson · Muktabh Mayank Srivastava · Amy Jin · Heliodoro Tejeda Lemus · Priyadip Ray · Tamas Madl · Joseph Futoma · Enhao Gong · Syed Rameel Ahmad · Eric Lei · Ferdinand Legros
• 2017 Poster: SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability »
  Maithra Raghu · Justin Gilmer · Jason Yosinski · Jascha Sohl-Dickstein
• 2016 Poster: RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism »
  Edward Choi · Taha Bahadori · Jimeng Sun · Joshua Kulas · Andy Schuetz · Walter Stewart
• 2016 Poster: Exponential expressivity in deep neural networks through transient chaos »
  Ben Poole · Subhaneil Lahiri · Maithra Raghu · Jascha Sohl-Dickstein · Surya Ganguli
• 2015 Poster: Bayesian Active Model Selection with an Application to Automated Audiometry »
  Jacob Gardner · Gustavo Malkomes · Roman Garnett · Kilian Weinberger · Dennis Barbour · John Cunningham
• 2015 Poster: Texture Synthesis Using Convolutional Neural Networks »
  Leon A Gatys · Alexander Ecker · Matthias Bethge