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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

Sat Dec 14 10:15 AM -- 10:45 AM (PST) @
in Machine Learning with Guarantees »

Visit https://sites.google.com/view/mlwithguarantees/accepted-papers for the list of papers.

Posters will be up all day.

Author Information

Antonia Marcu (University of Southampton)
Yao-Yuan Yang (UCSD)
Pascale Gourdeau (University of Oxford)
Chen Zhu (University of Maryland)
Thodoris Lykouris (Cornell University)
Jianfeng Chi (University of Virginia)
Mark Kozdoba (Technion)
Arjun Nitin Bhagoji (Princeton University)
Xiaoxia Wu (University of Texas at Austin)
Jay Nandy (NUS)
Michael T Smith (University of Sheffield)

I’m currently a post-doc researcher at the University of Sheffield, in Neil Lawrence’s lab. We’re developing new tools to allow data to be anonymised, through the framework of differential privacy. As part of an innovate UK collaboration we’re building the scikic inference tool, which will provide both a conversation interface and a backend API for inferring demographic and lifestyle features about individuals. It is hoped it will be a useful tool to demonstrate the power of machine learning. In the future we hope to develop a user-centric data model for the analysis and storage of user data, with the motivation that personalised medicine and associated research requires access to user data. I spent most of 2014 lecturing at Makerere University, Kampala, Uganda. There I became involved in the field of Development Informatics, and have several on-going research topics; covering air pollution, nutrition-data, automated microscopy, traffic collision data and malaria distribution prediction. A variety of machine learning methods have been applied (for example Gaussian Process models for the model of malaria distribution). More details about some of these projects can be found at the Artificial Intelligence in the Developing World (AI-DEV) group’s website.

Bingyang Wen (Stevens Institute of Technology)
Yuege Xie (The University of Texas at Austin)
Konstantinos Pitas (EPFL)
Suprosanna Shit (TUM)
Maksym Andriushchenko (University of Tübingen / EPFL)
Dingli Yu (Princeton University)
Gaël Letarte (Université Laval)
Misha Khodak (CMU)
Hussein Mozannar (Massachusetts Institute of Technology)

I am a PhD student at MIT Institute for Data, Systems, and Society interested in algorithmic fairness and modern challenges in data analysis such as robustness and privacy. I recently received my undergraduate degree in Computer and Communications Engineering at the American University of Beirut. In the summer of 2018 I was a visiting student/intern at TTIC working with Mesrob Ohannessian and Nathan Srebro on the long term effects of fair decision making.

Chara Podimata (Harvard University)
James Foulds (University of Maryland, Baltimore County)
Yizhen Wang (University of California, San Diego)
Huishuai Zhang (Microsoft Research Asia)
Ondrej Kuzelka (Czech Technical University in Prague)
Alexander Levine (University of Maryland, College Park)
Nan Lu (University of Tokyo/ RIKEN-AIP)
Zakaria Mhammedi (The Australian National University)
Paul Viallard (Jean Monnet University)
Diana Cai (Princeton University)
Lovedeep Gondara (Simon Fraser University)
James Lucas (University of Toronto)
Yasaman Mahdaviyeh (University of Toronto)
Aristide Baratin (Université de Montreal)
Rishi Bommasani (Cornell University)

M.S. student at Cornell University, researching in NLP under Claire Cardie. My work centers around theoretical soundness in NLP and I will be applying to PhD programs this December.

Alessandro Barp (Imperial College London)
Andrew Ilyas (MIT)
Kaiwen Wu (University of Waterloo)
Jens Behrmann (University of Bremen)
Omar Rivasplata (DeepMind & UCL)

My top-level areas of interest are statistical learning theory, machine learning, probability and statistics. These days I am very interested in deep learning and reinforcement learning. I am a Senior Research Fellow at the Department of Statistical Science, University College London. Before my current post I was for a few months at the Department of Mathematics at UCL. Previously I was for a few years at the Department of Computer Science at UCL, where I did research studies in statistical machine learning, sponsored by DeepMind. In parallel with these studies I was a research scientist intern at DeepMind for three years. Back in the day I studied undergraduate maths (BSc 2000, Pontificia Universidad Católica del Perú) and graduate maths (MSc 2005, PhD 2012, University of Alberta). I've lived in Peru, in Canada, and now I'm based in the UK.

Amir Nazemi (University of Waterloo)
Aditi Raghunathan (Stanford University)
Will Stephenson (MIT)
Sahil Singla (University of Maryland)
Akhil Gupta (University of Illinois, Urbana-Champaign)
YooJung Choi (UCLA)
Yannic Kilcher (ETH Zurich)
Clare Lyle (University of Oxford)
Edoardo Manino (University of Southampton)

Edoardo Manino is a research fellow at the University of Southampton. Currently, he is finishing his PhD in machine learning and crowdsourcing under the supervision of Prof. Nicholas R. Jennings and Dr. Long Tran-Thanh. His research interests range from Bayesian learning to algorithmic game theory and, more recently, influence maximisation on social networks.

Andrew Bennett (Cornell University)
Zhi Xu (MIT)
Niladri Chatterji (UC Berkeley)
Emre Barut (George Washington University)
Flavien Prost (Google)
Rodrigo Toro Icarte (University of Toronto and Vector Institute)

I am a Ph.D. student in the knowledge representation group at the University of Toronto. I am also a member of the Canadian Artificial Intelligence Association and the Vector Institute. My supervisor is Sheila McIlraith. I did my undergrad in Computer Engineering and MSc in Computer Science at Pontificia Universidad Catolica de Chile (PUC). My master's degree was co-supervised by Alvaro Soto and Jorge Baier. While I was at PUC, I taught the undergraduate course "Introduction to Computer Programming Languages."

Arno Blaas (University of Oxford)
Chulhee Yun (MIT)
Sahin Lale (California Institute of Technology)
YiDing Jiang (Google Research)
Tharun Kumar Reddy Medini (Rice University)

I'm a 3rd year PhD student at Rice University working with Prof.Anshumali Shrivastava. I primarily work on scaling up Deep Learning using Hashing techniques. I'm currently interning at Amazon Search in Palo Alto.

Ashkan Rezaei (University of Illinois at Chicago)
Alexander Meinke (Eberhard Karls Universität Tübingen)
Stephen Mell (University of Pennsylvania)
Gary Kazantsev (Bloomberg LP)
Shivam Garg (Stanford University)
Aradhana Sinha (Google)
Vishnu Lokhande (University of Wisconsin Madison)
Geovani Rizk (Université Paris Dauphine)
Han Zhao (Carnegie Mellon University)
Aditya Kumar Akash (University of Wisconsin, Madison)
Jikai Hou (Peking University)
Ali Ghodsi (University of Waterloo)
Matthias Hein (University of Tübingen)
Tyler Sypherd (Arizona State University)
Yichen Yang (MIT)
Anastasia Pentina (SDSC, ETH Zurich)
Pierre Gillot (University of Bergen)
Antoine Ledent (TU Kaiserslautern)

I obtained a PhD in stochastic analysis at the University of Luxembourg, and am now working in statistical learning theory as a postdoc.

Guy Gur-Ari (Google)
Noah MacAulay (Independent Researcher)
Tianzong Zhang (Tsinghua University)

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