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Poster Session
Lili Yu · Aleksei Kroshnin · Alex Delalande · Andrew Carr · Anthony Tompkins · Aram-Alexandre Pooladian · Arnaud Robert · Ashok Vardhan Makkuva · Aude Genevay · Bangjie Liu · Bo Zeng · Charlie Frogner · Elsa Cazelles · Esteban G Tabak · Fabio Ramos · François-Pierre PATY · Georgios Balikas · Giulio Trigila · Hao Wang · Hinrich Mahler · Jared Nielsen · Karim Lounici · Kyle Swanson · Mukul Bhutani · Pierre Bréchet · Piotr Indyk · samuel cohen · Stefanie Jegelka · Tao Wu · Thibault Sejourne · Tudor Manole · Wenjun Zhao · Wenlin Wang · Wenqi Wang · Yonatan Dukler · Zihao Wang · Chaosheng Dong

Fri Dec 13 05:20 PM -- 06:00 PM (PST) @
in Optimal Transport for Machine Learning »

Author Information

Lili Yu (ASAPP Inc)
Aleksei Kroshnin (Institute for Information Transmission Problems)
Alex Delalande (CentraleSupélec)
Andrew Carr (Brigham Young University)
Anthony Tompkins (The University of Sydney)
Aram-Alexandre Pooladian (McGill University)

PhD student at the CDS at NYU; interested in statistical optimal transport and optimization theory.

Arnaud Robert (Center for Mathematical Modeling, University of Chile)
Ashok Vardhan Makkuva (University of Illinois at Urbana-Champaign)
Aude Genevay (Ecole Normale Supérieure)
Bangjie Liu (Citadel)
Bo Zeng (pitt)
Charlie Frogner (MIT)
Elsa Cazelles (Center for Mathematical Modeling, University of Chile)
Esteban G Tabak (New York University, Courant Institute)
Fabio Ramos (University of Sydney)
François-Pierre PATY (ENSAE Paris)
Georgios Balikas (Salesforce Inc)
Giulio Trigila (Baruch College, CUNY)
Hao Wang (Citadel)
Hinrich Mahler (TU Braunschweig)
Jared Nielsen (Brigham Young University)
Karim Lounici (Ecole Polytechnique)
Kyle Swanson (ASAPP, Inc.)
Kyle Swanson

Kyle Swanson is a PhD student at Stanford University advised by James Zou. He is interested in applications of machine learning to biology, medicine, and drug discovery.

Mukul Bhutani (Carnegie Mellon University)
Pierre Bréchet (Technical University Munich)
Piotr Indyk (MIT)
samuel cohen (University College London)

Samuel is a first-year PhD student in Machine Learning at University College London (UCL), supervised by Professor Marc Deisenroth. He graduated with an MSc in Statistical Science from Oxford University and a BSc in Mathematics from Imperial College London. His main areas of interest are Reinforcement Learning, Gaussian Processes, Optimal Transport, and Deep Generative Modeling.

Stefanie Jegelka (MIT)

Stefanie Jegelka is an X-Consortium Career Development Assistant Professor in the Department of EECS at MIT. She is a member of the Computer Science and AI Lab (CSAIL), the Center for Statistics and an affiliate of the Institute for Data, Systems and Society and the Operations Research Center. Before joining MIT, she was a postdoctoral researcher at UC Berkeley, and obtained her PhD from ETH Zurich and the Max Planck Institute for Intelligent Systems. Stefanie has received a Sloan Research Fellowship, an NSF CAREER Award, a DARPA Young Faculty Award, the German Pattern Recognition Award and a Best Paper Award at the International Conference for Machine Learning (ICML). Her research interests span the theory and practice of algorithmic machine learning.

Tao Wu (Technical University of Munich)
Thibault Sejourne (DMA, ENS, Paris)

After graduating from Ecole Polytechnique, I enrolled into the master’s degree MVA (“Mathematiques, Visison, Apprentissage”) of Ecole Normale Superieure Paris-Saclay. I am now a second year PhD candidate at ENS Paris under the supervision of Gabriel Peyré and François-Xavier Vialard. I am currently working on the applications of the theory of Optimal Transport for Machine learning applications.

Tudor Manole (Carnegie Mellon University)
Wenjun Zhao (Courant Institute of Mathematical Sciences)
Wenlin Wang (Duke Univeristy)
Wenqi Wang (Facebook)
Yonatan Dukler (UCLA)

I am a second year PhD student in Department of Mathematics at UCLA working under the joint supervision of [Guido Montufar](http://www.math.ucla.edu/~montufar/) and [Andrea Bertozzi](http://www.math.ucla.edu/~bertozzi/). My research is in the field of machine learning, applied mathematics, high dimensional statistics and specifically in their intersection. I am very fortunate to be supported by the NSF Graduate Research Fellowship (NSF GRFP). Before my PhD I was studying (pure) mathematics at UCLA with interest in analysis. I received my BS and MA concurrently from UCLA under the Departmental Scholar Program.

Zihao Wang (Tsinghua University)
Chaosheng Dong (University of Pittsburgh)

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