Keith Ross is the Dean of Engineering and Computer Science at NYU Shanghai and the Leonard J. Shustek Chair Professor of Computer Science at NYU Tandon. He also holds an affiliated appointment with the Department of Computer Science at the Courant Institute of Mathematical Sciences and with the Center for Data Science at NYU.
Prior to joining NYU Shanghai in 2013, Dean Ross was a professor at the University of Pennsylvania for 13 years, a professor at Eurecom Institute for 5 years, and the Department Head of the CSE Department at NYU from 2008 to 2013. He received a PhD in Computer and Control Engineering from The University of Michigan.
Dean Ross's current research interests are in reinforcement learning. He has also worked in Internet privacy, peer-to-peer networking, Internet measurement, stochastic modeling of computer networks, queuing theory, and Markov decision processes. At NYU Shanghai he has been teaching Machine Learning, Reinforcement Learning, and Introduction to Computer Programming.
He is an ACM Fellow and an IEEE Fellow. He is also the recipient of several prestigious best paper awards, and his work has been featured in the mainstream press, including the New York Times, NPR, Bloomberg Television, Huffington Post, Fast Company, Ars Technia, and the New Scientist.
Dean Ross is co-author (with James F. Kurose) of the popular textbook Computer Networking: A Top-Down Approach Featuring the Internet, published by Pearson (first edition in 2000, eighth edition 2020). It is the most popular textbook on computer networking, both nationally and internationally, and has been translated into fourteen languages. He is also the author of the research monograph Multiservice Loss Models for Broadband Communication Networks, published by Springer in 1995.
In 1999, he co-founded and led Wimba, which develops voice and video applications for online learning. He was the Wimba CEO and CTO from 1999 to 2001. Wimba was acquired by Blackboard in 2010.
Read more about his work with students in Faculty-Student Research: Teaching Robots to Run.