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 the algorithmic foundations of machine learning, distributed algorithm design, and algorithms for scheduling and logistics.

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 presentaion at NeurIPS 2021 (top 1% of submissions), an oral presentation at NIPS 2017 (top 1.3% of submissions) and spotlight presentations at NeurIPS 2023 and NIPS 2018 (top 3.5% of submissions).