Mohammad Bavarian obtained his Ph.D. under Prof. Madhu Sudan from MIT in 2017 working on quantum computing and complexity theory. He now works as a software developer at Rubrik Inc. and spends his free time thinking about startups, business, and engineering. While not busy with above, he also dabbles in programming competitions and Machine Learning. He enjoys the beautiful palm trees and sunshine of California, but still sometimes misses the city life of the East Coast.

Badih Ghazi is a Research Scientist in the Algorithms team at Google. His current research interests include algorithmic aspects of machine learning, differential privacy, error-correcting codes and communication under uncertainty. He completed his Ph.D. in 2018 at the Electrical Engineering and Computer Science (EECS) department at MIT where he was advised by Professors Madhu Sudan and Ronitt Rubinfeld. Previously, he got his M.S. in EECS also from MIT, and his B.Eng. in Computer and Communications Engineering from the American University of Beirut. During his graduate studies, he was awarded an IBM Ph.D. Fellowship and an MIT Irwin and Joan Jacobs Presidential Fellowship.

Elad Haramaty is a Research Scientist at Amazon Israel. Previously, he held postdoctoral researcher positions at Harvard University (hosted by Madhu Sudan) and at Northeastern University (hosted by Emanuele Viola). He earned his Ph.D. from the Technion Israel Institute of Technology under the guidance of Amir Shpilka. His research interests lie in a broad range of areas of theoretical computer science, especially in algebraic complexity. In his work he has studied mostly the structure, testability and applications of polynomials and algebraic codes. He nowadays mostly works on various aspects of Search and Machine Learning.

Pritish Kamath is a postdoctoral scholar at the Toyota Technological Institute at Chicago. He completed his Ph.D. at MIT, co-advised by Professors Madhu Sudan and Ronitt Rubinfeld. Prior to that, he completed a B.Tech. in Computer Science at IIT Bombay in 2012 after which he was a Research Fellow at Microsoft Research India until 2013, where he was mentored by Neeraj Kayal. He has broad interests in complexity theory and has worked in areas touching upon communication complexity, information theory, Boolean and algebraic circuit complexity and proof complexity and most recently is also interested in foundational aspects of machine learning. He likes to juggle multiple things in life; sometimes on a bicycle.

Ronald L. Rivest is an Institute Professor in the Department of Electrical Engineering and Computer Science at MIT. He is a member of MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL), a member of the lab's Theory of Computation Group and is a leader of its Cryptography and Information Security Group.

Ron has current research interests in cryptography, computer and network security, voting systems, and algorithms. In the past he has also worked extensively in the area of machine learning.

Ron is a coauthor (with Thomas Cormen, Charles Leiserson, and Clifford Stein) of the well-known text Introduction to Algorithms, published by MIT Press. Over 500,000 copies of this text have been sold. It has been translated into 12 languages.

Ron is an inventor of the RSA public-key cryptosystem. He has extensive experience in cryptographic design and cryptanalysis, and has published numerous papers in these areas. He is a founder of RSA Data Security. (RSA was bought by Security Dynamics; the combined company was renamed to RSA Security, and later purchased by EMC), and is also a co-founder of Verisign and of Peppercoin.

Ron is a member of the CalTech/MIT Voting Technology Project. He served 2004--2009 on the Technical Guidelines Development Committee (TGDC), advisory to the Election Assistance Commission, developing recommendations for voting system certification standards; he was chair of the TGDC's Computer Security and Transparency Subcommittee. He also serves on the Board of the Verified Voting Foundation. He is a member of a Scantegrity team developing and testing voting systems that are verifiable “end-to-end.” He has worked extensively on statistical post-election tabulation audits, of both the “risk-limiting audit” and “Bayesian” flavors.

Ron is a member of the Center for Science of Information.

Madhu Sudan is a Gordon McKay Professor in the John A. Paulson School of Engineering and Applied Sciences at Harvard University, where he has been since 2015. Madhu got his Bachelors degree (apparently in Technology) from IIT Delhi in 1987 where he was introduced to theoretical computer science by Sachin Maheshwari. He got his Ph.D. from U.C. Berkeley in 1992 under the supervision of Umesh Vazirani. Madhu subsequently spent time at, and was even paid by, IBM, MIT and Microsoft.

While Madhu's research explores communication and computational complexity, he prefers simplicity, and is especially proud of his exposition (with Peter Gemmell) on the Berlekemp-Welch decoding algorithm and his exposition (with David Xiang) of the analysis of the Lempel-Ziv compression algorithm.