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Poster Session 2
Jinwuk Seok · Bo Liu · Ryotaro Mitsuboshi · David Martinez-Rubio · Weiqiang Zheng · Ilgee Hong · Chen Fan · Kazusato Oko · Bo Tang · Miao Cheng · Aaron Defazio · Tim G. J. Rudner · Gabriele Farina · Vishwak Srinivasan · Ruichen Jiang · Peng Wang · Jane Lee · Nathan Wycoff · Nikhil Ghosh · Yinbin Han · David Mueller · Liu Yang · Amrutha Varshini Ramesh · Siqi Zhang · Kaifeng Lyu · David Yunis · Kumar Kshitij Patel · Fangshuo Liao · Dmitrii Avdiukhin · Xiang Li · Sattar Vakili · Jiaxin Shi

Sat Dec 03 01:50 PM -- 02:50 PM (PST) @
in OPT 2022: Optimization for Machine Learning »

Author Information

Jinwuk Seok (Electronics and Telecommunications Research Institute)

Jinwuk Seok received his BS and MS degrees in Electrical Control Engineering from Hong-Ik University, Seoul, Republic of Korea, in 1993 and 1995, respectively. Additionally, he received his Ph.D. degree in Electrical Engineering from Hong-Ik University, Seoul, Republic of Korea, in 1998. He has been a principal member of engineering staff at Electronics and Telecommunications Research Institute in Korea since 2000, and an adjunct professor of the Computer Software Engineering Department at the University of Science and Technology in Korea since 2009. His research interests include artificial intelligence, machine learning, and stochastic nonlinear control.

Bo Liu (The University of Texas at Austin)
Ryotaro Mitsuboshi (Kyushu University)
David Martinez-Rubio (Zuse Institute Berlin)
Weiqiang Zheng (Yale University)
Ilgee Hong (University of Chicago)
Chen Fan (University of British Columbia)
Kazusato Oko (The University of Tokyo)
Bo Tang (University of Toronto)
Bo Tang

I am a Ph.D. candidate in the MIE department at the University of Toronto. Elias Khalil is my supervisor. And my current research area is the intersection of Operations Research and Machine learning, particularly in End-to-End Predict-then-Optimize.

Miao Cheng (LinkedIn)
Miao Cheng

I am currently part of the Data/AI team at LinkedIn, building end-to-end innovative AI/ML solutions for products at scale. Tsinghua University (Bachelor's degrees in Automation/EECS and Economics) + UPenn Computer Science Grad.

Aaron Defazio (Facebook AI Research)
Tim G. J. Rudner (University of Oxford)

Tim G. J. Rudner is a Computer Science PhD student at the University of Oxford supervised by Yarin Gal and Yee Whye Teh. His research interests span Bayesian deep learning, reinforcement learning, and variational inference. He obtained a master’s degree in statistics from the University of Oxford and an undergraduate degree in mathematics and economics from Yale University. Tim is also a Rhodes Scholar and a Fellow of the German National Academic Foundation.

Gabriele Farina (Meta AI; Carnegie Mellon University)
Vishwak Srinivasan (Massachusetts Institute of Technology)
Ruichen Jiang (UT Austin)
Peng Wang (University of Michigan - Ann Arbor)
Jane Lee (Yale University)
Nathan Wycoff (Georgetown University)
Nikhil Ghosh (UC Berkeley)
Yinbin Han (University of Southern California)
David Mueller (Johns Hopkins University)
Liu Yang (University of Wisconsin, Madison)
Amrutha Varshini Ramesh (University of British Columbia)
Siqi Zhang (Johns Hopkins University)
Kaifeng Lyu (Princeton University)
David Yunis (TTIC)
Kumar Kshitij Patel (Toyota Technological Institute at Chicago)
Fangshuo Liao (Rice University)
Dmitrii Avdiukhin (Indiana University)
Xiang Li (ETH Zurich)
Sattar Vakili (MediaTek Research)
Jiaxin Shi (Stanford University)

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