Ben Moseley is the Carnegie Bosch Assistant Professor of Operations Research in the Tepper School of Business at Carnegie Mellon University (CMU) and is a consulting professor at the start-up Relational AI. He is an Assistant Professor of Machine Learning in the School of Computer Science (by courtesy) and member of the Ph.D. program Algorithms, Combinatorics and Optimization (ACO). He received a Ph.D. from the University of Illinois in Computer Science and was advised by Chandra Chekuri.

Professor Moseley's research interests are broadly in operations research, theoretical computer science and machine learning. He works on the design, analysis and evaluation of algorithms. He is currently working on scheduling theory, distributed computing, and the theoretical foundations of machine learning.

Ben Moseley has won several best paper awards including a 2015 IPDPS Best Paper Award, a SPAA 2013 Best Paper Award, and a SODA 2010 Best Student Paper Award. His work has been recognized with an oral presentation at NIPS 2017 (top 1.3% of submissions) and a spotlight presentation at NIPS 2018 (top 3.5% of submissions).

Moseley's work has been supported by generous grants from the National Science Foundation, Yahoo, Infor and Google. Financial support for Moseley's work includes a NSF CAREER Award, a NSF Scalable Parallelism in the Extreme (SPX) Award, a NSF Algorithms in the Field Award (AITF) Award , a NSF Algorithmic Foundations Award, two Google Faculty Research Awards, and a Yahoo! Academic Career Enabling (ACE) Award.

In the past, he was an Assistant Professor in the Department of Computer Science and Engineering at Washington University in St. Louis from 2014-2017. He was a 2016 Simons-Berkeley Fellow. From 2012-2014 he was a Research Assistant Professor at the Toyota Technological Institute at Chicago. He was a visiting professor at Sandia National Laboratories in 2013 and has frequently been affiliated with Yahoo Labs.