I am a Research Assistant Professor with the College of Information and Computer Sciences at the University of Massachusetts Amherst. Before joining UMass, I was a postdoc at the Johns Hopkins University and The Chinese University of Hong Kong. I received my Ph.D. and B.Sc. degrees from the University of Tehran and Sharif University of Technology.
My research is centered on carbon-intelligent computing (application) and data-driven online optimization (theory). I develop rigorous algorithms using data-driven online optimization and learning tools that are applicable in several domains such as data center energy optimization, electricity market, electric vehicles, smart energy systems, and networking applications such as multimedia networking and edge/cloud networking. My research is supported by a Google Research Faculty Award, an NSF CAREER Award, and other grants from NSF, Adobe, and VMWare.
Prospective Students and Postdocs
We are actively looking for well-motivated and talented students and postdocs to join our research group. If interested, please apply to our grad program and mention my name.
- October 2021: Our paper on competitive algorithms for online multidimensional knapsack problems is accepted to ACM Sigmetrics 2022.
- September 2021: Two papers on learning-augmented algorithms for online conversion problems and cooperative bandits with asynchronous agents and constrained feedback were accepted to NeurIPS 2021.
- September 2021: Our new vision paper on sustainable cloud infrastructure was accepted to ACM SoCC 2021.
- August 2021: We received a new collaborative NSF CPS grant on integrating distributed energy resources into electricity markets. This is a joint grant between JHU, UMass, and Caltech.
- July 2021: A new paper on online bidding strategy design accepted to IFIP Performance 2021.
- July 2021: A new NSF grant on theory and applications of dynamic data-driven systems. A collaborative project between Ramesh Sitaraman at UMass Amherst, Adam Wierman and Steven Low at Caltech, and Zhenhua Liu at Stony Brook.
- July 2021: Our paper on video super resolution using foveated rendering accepted to ACM Multimedia 2021.
- July 2021: We received an NSF grant on dynamic pricing and procurement for distributed networked platforms. This is collaborative research with Carlee Joe-Wong at CMU.
- April 2021: Thanks to NSF/VMWare for supporting our CarbonFirst project, the press release here and here!
- April 2021: A new paper on online energy scheduling accepted to ACM eEnergy 2021. Best paper runner-up!
- February 2021: A big thanks to NSF for an NSF CAREER Award, more information here!
- January 2021: Our paper on carbon benefits of bike sharing accepted to ACM IMWUT/UbiComp 2021.
- December 2020: Our paper on data-driven online algorithms accepted to AAAI 2021.
- September 2020: Our paper on online multiple knapsacks accepted to Sigmetrics 2021.
- September 2020: Our paper on adversarial bandits with corruptions accepted to NeurIPS 2020. Congratulations to Lin!
- June 2020: Our ACM e-Energy 2020 paper on emission-aware energy scheduling won the Best Paper Award Runner-up.
- August 2019: I received an NSF grant on data center energy optimization. Find out more here and here!
- February 2019: I received a Google Faculty Research Award. Find out more here!
- June 2020: I will be serving on ACM Sigmetrics’21 PC, which will be held in Beijing, China.
- April 2020: Our paper on emission-aware energy storage scheduling for a greener grid has been accepted at ACM eEnergy 2020.
- December 2019: Our paper on online linear optimization with inventory management constraints has been accepted at ACM Sigmetrics 2020.
- December 2019: Our paper on online EV charging scheduling has been accepted at IEEE Trans. on Sustainable Computing.
- October 2019: I will be serving on ACM eEnergy’20 PC, please consider submitting!
- January 2019: I am organizing an invited session on “online optimization and learning” at CISS 2019.
- August 2018: I joined the College of Information and Computer Sciences at UMass Amherst as a Research Assistant Professor.
- Lin Yang, Ali Zeynali, Mohammad H. Hajiesmaili, Ramesh Sitaraman, Don Towsley, Competitive Algorithms for Online Multidimensional Knapsack Problems, in Proc. of ACM SIGMETRICS 2022, to appear.
- Bo Sun, Russell Lee, Mohammad H. Hajiesmaili, Adam Wierman, Danny Tsang, Pareto-optimal Learning-Augmented Algorithms for Online Conversion Problems, in Proc. of NeurIPS 2021, to appear.
- Lin Yang, Yu-Zhen Janice Chen, Stephen Pasteris, Mohammad H. Hajiesmaili, John Lui, Don Towsley, Cooperative Stochastic Bandits with Asynchronous Agents and Constrained Feedback, in Proc. of NeurIPS 2021, to appear.
- Noman Bashir, Tian Guo, Mohammad H. Hajiesmaili, David Irwin, Prashant Shenoy, Ramesh Sitaraman, Abel Souza, Adam Wierman, Enabling Sustainable Clouds: The Case for Virtualizing the Energy System, in Proc. of ACM SoCC 2021, to appear.
- Russell Lee, Yutao Zhou, Lin Yang, Mohammad H. Hajiesmaili, Ramesh Sitaraman, Competitive Bidding Strategies for Online Linear Optimization with Inventory Management Constraints, in Proc. of IFIP Performance 2021, to appear.
- Lingdong Wang, Mohammad H. Hajiesmaili, and Ramesh Sitaraman, FOCAS: Practical Video Super Resolution using Foveated Rendering, in Proc. of ACM Multimedia 2021, to appear.
- Russell Lee, Jessica Maghakian, Mohammad H. Hajiesmaili, Jian Li, Ramesh Sitaraman, and Zhenhua Liu Online Peak-Aware Energy Scheduling with Untrusted Advice, in Proc. of ACM eEnergy 2021, Best paper runner-up!
- John Wamburu, Stephen Lee, Mohammad H. Hajiesmaili, David Irwin, and Prashant Shenoy, Ride Substitution Using Electric Bike Sharing: Feasibility, Cost, and Carbon Analysis, in Proc. of ACM IMWUT/UbiComp 2021.
- Ali Zeynali, Bo Sun, Mohammad H. Hajiesmaili, and Adam Wierman, Data-driven Competitive Algorithms for Online Knapsack and Set Cover, in Proc. of AAAI 2021.
- Bo Sun, Ali Zeynali, Tongxin Li, Mohammad H. Hajiesmaili, Adam Wierman, and Danny H.K. Tsang, Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging, in Proc. of ACM SIGMETRICS 2021.
- Lin Yang, Mohammad H. Hajiesmaili, M. Sadegh Talebi, John C.S. Lui, and Wing S. Wong, Adversarial Bandits with Corruptions, in Proc. of NeurIPS 2020.
- Lin Yang, Mohammad H. Hajiesmaili, Ramesh Sitaraman, Adam Wierman, Enrique Mallada, and Wing S. Wong, Online Linear Optimization with Inventory Management Constraints, in Proc. of ACM SIGMETRICS 2020.
- Rishikesh Jha, Stephen Lee, Srinivasan Iyengar, Mohammad H. Hajiesmaili, David Irwin, and Prashant Shenoy, Emission-aware Energy Storage Scheduling for a Greener Grid, in Proc. of ACM eEnergy 2020. Best Paper Runner-up
- Lin Yang, Lei Deng, Mohammad H. Hajiesmaili, Cheng Tan, Wing S. Wong, and An Optimal Algorithm for Online Non-Convex Learning, in Proc. of ACM SIGMETRICS 2018.
- Lin Yang, Wing S. Wong, and Mohammad H. Hajiesmaili, An Optimal Randomized Online Algorithm for QoS Buffer Management, in Proc. of ACM SIGMETRICS 2018.
- Mohammad H. Hajiesmaili, Sid Chi-Kin Chau, Minghua Chen, and Longbo Huang, Online Microgrid Energy Generation Scheduling Revisited: The Benefits of Randomization and Interval Prediction, in Proc. of ACM eEnergy 2016. Best Paper Runner-up
- Lei Deng, Mohammad H. Hajiesmaili, Minghua Chen, Haibo Zeng, Energy-Efficient Timely Transportation of Long-Haul Heavy-Duty Trucks, in Proc. of ACM eEnergy 2016. Best Paper Runner-up
- Ying Zhang, Mohammad H. Hajiesmaili, and Minghua Chen, Peak-Aware Online Economic Dispatching for Microgrids, in Proc. of ACM eEnergy 2015. Best Paper Runner-up