Mohammad Hajiesmaili

Mohammad Hajiesmaili is an assistant professor in the Manning College of Information and Computer Sciences (CICS). Hajiesmaili's research centers on studying fundamental design problems under uncertainty in a wide range of application domains. More specifically, he uses theoretical tools from optimization, machine learning, and algorithm to design rigorous systems that work provably efficient in uncertain settings. The current target application domains are (1) computer networks and data center optimization, and (2) energy systems, including electric vehicles. 

Mohammad's research centers on studying fundamental design problems under uncertainty in a wide range of application domains. More specifically, Mohammad uses theoretical tools from optimization, machine learning, and algorithm, to design rigorous systems that work provably efficient in uncertain settings. The current target application domains are (i) computer networks and data center optimization; and (ii) energy systems, including electric vehicles. 

Hajiesmaili's research is supported by an NSF CAREER Award, a Google Faculty Research Award, and other grants from NSF, VMWare, and Adobe. Five of his recent papers were selected as finalists for the best paper award in ACM eEnergy 2015, 2016, 2020, and 2021. He serves on the Program Committee for multiple conferences such as ACM Sigmetrics and ACM eEnergy. 

Before joining UMass, Mohammad was a postdoctoral fellow with Johns Hopkins University, from 2017 to 2018, and with the Chinese University of Hong Kong, from 2015 to 2016.