Stark Draper (University of Toronto)

Stark Draper cooks up the math that makes your mobile phone work. His other recipes make your computer more energy-efficient and store your personal biometric data more securely. He has held academic, industrial and consulting roles with Arraycomm Inc., a telecommunications start-up in California, the Mitsubishi Electric Research Labs (MERL), Disney Research, UC Berkeley and UW-Madison. He leads his research team in collaborations with 3M, Bell Labs, Disney Research, Facebook, HP Labs, IBM, and Mitsubishi Electric, among others. He is a Professor at the University of Toronto and until 2013 was an Associate Professor at the University of Wisconsin, Madison. His research interests and activities include information theory, coding theory, optimization, statistical signal processing, security, and application of these fields to computer architecture and computing.

Mehmet Aktas (Rutgers University)

Basak Guler (University of Southern California)

Hongyi Wang (University of Wisconsin-Madison, IBM Research)

I’m currently a second-year Ph.D. student at Computer Sciences Department of University of Wisconsin - Madison, advised by Prof. Dimitris Papailiopoulos. My research interests locate in machine learning, distributed system, and large-scale optimization.

Venkata Gandikota (University of Massachusetts)

Hyegyeong Park (Carnegie Mellon University)

Hyegyeong Park is a postdoctoral fellow in the Computer Science Department at Carnegie Mellon University under the mentorship of Prof. Rashmi K. Vinayak. She received her Ph.D. degree in electrical engineering at Korea Advanced Institute of Science and Technology (KAIST) in 2018, and was a postdoctoral researcher at KAIST under the supervision of Prof. Jaekyun Moon. She is a recipient of the KAIST EE Postdoc Fellowship 2019-20 and the BK21 Plus Postdoctoral Fellowship 2018-19. Her research interests lie in the field of coding and information theory for distributed systems with the current focus on coding for distributed computing and distributed machine learning algorithms.

Jinhyun So (University of Southern California)

Lev Tauz (University of California, Los Angeles)

hema venkata krishna giri Narra (University Of Southern California)

PhD candidate in Computer Engineering at University of Southern California

Zhifeng Lin (USC)

Mohammadali Maddahali (Nokia Bell Labs)

Yaoqing Yang (Carnegie Mellon University)

Sanghamitra Dutta (Carnegie Mellon University)

Amirhossein Reisizadeh (University of California, Santa Barbara)

Jianyu Wang (Carnegie Mellon University)

Eren Balevi (The University of Texas at Austin)

Siddharth Jain (Caltech)

Paul McVay (Texas A&M)

Michael Rudow (Carnegie Mellon University)

Pedro Soto (Florida International University)

Jun Li (Florida International University)

Adarsh Subramaniam (Texas A&M)

Umut Demirhan (Arizona State University)

Vipul Gupta (UC Berkeley)

Deniz Oktay (Google Research)

Leighton P Barnes (Stanford University)

Johannes Ballé (Google)

Farzin Haddadpour (Pennsylvania State University)

Haewon Jeong (Carnegie Mellon University)

Rong-Rong Chen (University of Utah)

Mohammad Fahim (Pennsylvania State University)