Mark E. Lewis (engineer)

Lewis was Associate Dean for Diversity and Faculty Development for Cornell University's College of Engineering from 2015 to 2020. In this role, he acted as task force chair of the Faculty Diversity Committee, which was convened in 2017. Lewis served as principal investigator on the Cornell University Engineering Success Program to increase the participation of underrepresented minority and first-generation college students.

Lewis founded the Institute for Operations Research and the Management Sciences (INFORMS) Minority Issues Forum in 2001 and served as its first president. In 2009, Lewis co-chaired the 15th INFORMS Applied Probability Conference at Cornell University in Ithaca, NY. Lewis acted as chair of the Applied Probability Society from 2012 to 2014.

After his PhD, Lewis spent a year at the University of British Columbia as a postdoctoral fellow. In 1999, he joined the faculty at the University of Michigan in Ann Arbor as Assistant Professor of Industrial and Operations Engineering. Lewis became Associate Professor at the Operations Research and Information Engineering department at Cornell University in 2005 and was promoted to Full Professor in 2011.

Lewis received a BS degree in mathematics and a BA degree in political science at Eckerd College, graduating in 1992. He proceeded to earn an MS degree in theoretical statistics from Florida State University in 1995 and a PhD degree in industrial and systems engineering from Georgia Tech in 1998. Lewis' PhD thesis Bias Optimality in a Two-Class Nonstationary Queueing System at Georgia Tech was advised by Robert E. Foley.

Mark Edwin Lewis (born 1970) is an industrial engineer and professor at Cornell University. He was the first African-American faculty member hired in Industrial Engineering at University of Michigan and the first tenured African-American faculty member at the School of Operations Research and Information Engineering at Cornell University. Lewis' research is focused on stochastic processes, and queueing theory and Markov decision processes in particular.