Benjamin Moseley

Benjamin Moseley is the Carnegie Bosch Associate Professor of Operations Research at the Tepper School of Business, Carnegie Mellon University (CMU), with a courtesy appointment in the School of Computer Science's Machine Learning Department. He is also a consulting professor at the start-up Relational AI.

Education: PhD in Computer Science from the University of Illinois, advised by Chandra Chekuri. Prior roles include Assistant Professor at Washington University in St. Louis (2014–2017), Research Assistant Professor at Toyota Technological Institute at Chicago (2012–2014), and visiting positions at Sandia National Laboratories and Yahoo Labs. Notable affiliations include the NSF-funded Algorithms, Combinatorics, and Optimization (ACO) PhD program.

Research focuses on algorithm design, analysis, and evaluation, with emphasis on operations research, theoretical computer science, and machine learning. Current projects include algorithmic foundations of machine learning, distributed algorithm design, and scheduling/logistics optimization. His work bridges theoretical rigor and practical applications, addressing challenges in big data analysis, streaming algorithms, and approximation techniques.

Recognition includes multiple best paper awards (IPDPS 2015, SPAA 2013, SODA 2010), top-tier NeurIPS presentations, and prestigious grants from NSF, ONR, Google, Bosch, and others. His research has been supported by a NSF CAREER Award, Google Faculty Research Awards, and the Carnegie-Bosch Chair.

Teaching contributions include developing the Business Analytics and Optimization undergraduate minor at Tepper, courses for UBA/MBA/MSBA programs, and被评为“Top 50 Undergraduate Business School Professor” by Poets and Quants. He emphasizes pedagogy integrating advanced algorithms with business applications.

Labs/Teams: Active in Relational AI collaborations and affiliated with CMU's machine learning and operations research research groups. His work frequently intersects with industrial partners like Google, Yahoo, and Bosch.