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Poster session 2 and coffee break
Sean McGregor · Tobias Hagge · Markus Stoye · Trang Thi Minh Pham · Seungkyun Hong · Amir Farbin · Sungyong Seo · Susana Zoghbi · Daniel George · Stanislav Fort · Steven Farrell · Arthur Pajot · Kyle Pearson · Adam McCarthy · Cecile Germain · Dustin Anderson · Mario Lezcano Casado · Mayur Mudigonda · Benjamin Nachman · Luke de Oliveira · Li Jing · Lingge Li · Soo Kyung Kim · Timothy Gebhard · Tom Zahavy
Author Information
Sean McGregor (XPRIZE Foundation)
Sean received a PhD in Machine Learning at Oregon State under the direction of Thomas Dietterich. Sean's machine learning and visualization research focus on the optimization, testing, and interpretation of reinforcement learning policies. Sean has spoken during the conferences and workshops of NIPS, RLDM, AAAI, OSCON, VL/HCC, CompSustNet, OpenSourceBridge, and the United Nations. Sean is originally from San Diego and enjoys riding waves. In Oregon he picked up whitewater kayaking, as well as rock climbing.
Tobias Hagge (Pacific Northwest National Laboratory)
Markus Stoye (CERN)
- Head of deep learning in REEXEN - Machine learning representative at CERN laboratory for CMS experiment
Trang Thi Minh Pham (Deakin University)
Seungkyun Hong (Korea Institute of Science and Technology Information)
Amir Farbin (University of Texas at Arlington)
Sungyong Seo (University of Southern California)
Susana Zoghbi (SETI)
Daniel George (University of Illinois at Urbana-Champaign)
Daniel George is a PhD student in Astronomy, with a fellowship in Computational Science and Engineering (CSE), at the University of Illinois at Urbana-Champaign. He obtained his Bachelor's degree in Engineering Physics from IIT Bombay. He is currently a Research Assistant in the Gravity Group at the National Center for Supercomputing Applications (NCSA), a member of the LIGO, NANOGrav, and Dark Energy Survey (DES) collaborations, and an LSST Data Science Fellow, working at the interface of deep learning, signal processing, high-performance computing, and gravitational wave and multimessenger astrophysics. His long-term interests lie in applying cutting-edge computer science and technology, especially artificial intelligence, to accelerate discoveries in the fundamental sciences.
Stanislav Fort (Stanford University)
Steven Farrell (Lawrence Berkeley National Laboratory)
Arthur Pajot (UPMC, LIP6)
Kyle Pearson (University of Arizona)
Adam McCarthy (CCDS)
Cecile Germain (Universite Paris Sud)
Dustin Anderson (California Institute of Technology)
Mario Lezcano Casado (University of Oxford)
Mayur Mudigonda (UC Berkeley)
Benjamin Nachman (Lawrence Berkeley National Laboratory)
Luke de Oliveira (Berkeley Lab / Vai Technologies)
I'm a founder at Vai Technologies, where we are building software to help organizations and enterprises make sense of and leverage large volumes of text using deep learning. I am also a visiting researcher at Lawrence Berkeley National Laboratory (LBNL) where I work on deep generative modeling in the natural sciences. I've published a few papers on learning aspects of high energy particle collisions using Generative Adversarial Networks. I'm also an advisor at a handful of startups.
Li Jing (MIT)
Lingge Li (University of California Irvine)
Soo Kyung Kim (Lawrence Livermore National Laboratory)
Timothy Gebhard (Max Planck Institute for Intelligent Systems)
Tom Zahavy (The Technion)
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