Joshua Comden
Abstract
Brief Biography: Joshua Comden is currently a Ph.D. Candidate at Stony Brook University studying Operations Research in the Department of Applied Mathematics and Statistics and is expected to graduate in December 2019. He received his M.S. in Operations Research from the Department of Applied Mathematics and Statistics in 2015 from Stony Brook University and his B.E. in Chemical Engineering from the University of Delaware in 2009.
In the Summer of 2019, he was a Graduate Student Intern at the National Renewable Energy Laboratory using Matrix Completion techniques to improve Power System State Estimation which resulted in a publication. From 2017 to 2018, he was awarded a STRIDE Fellowship from the Institute for Advanced Computational Science to learn how to communicate research to policy makers so that they can make well informed decisions.
His research interests are in the design and analysis of online and distributed optimization algorithms with applications in computing and energy systems.
- Online Optimization in Cloud Resource Provisioning: Predictions, Regrets, and Algorithms (ACMSIGMETRICS 2019) with S. Yao, N. Chen, H. Xing, and Z. LiuGoogle Scholar
- Using Predictions in Online Optimization: Looking Forward with an Eye on the Past (ACM SIGMETRICS 2016) with N. Chen, Z. Liu, A. Gandhi, and A. WiermanGoogle Scholar
- Geographically Coordinated Primary Frequency Control (IEEE Transactions on Control of Network Systems 2019) with T. Le, Y. Zhao, B. Choi, and Z. LiuGoogle Scholar
- Harnessing Flexible and Reliable Demand Response under Customer Uncertainties (ACM e-Energy 2017) with Z. Liu, and Y. ZhaoGoogle Scholar
Recommendations
Optimization Algorithms for Large-Scale Systems: From Deep Learning to Energy Markets
Brief Biography: Navid Azizan is a fifth-year PhD candidate in Computing and Mathematical Sciences (CMS) at the California Institute of Technology (Caltech), where he is co-advised by Adam Wierman and Babak Hassibi, and is a member of multiple research ...
SIGACT news online algorithms column 8
Pros and cons of the competitive analysis have been discussed in the literature by many authors. Continuing this discussion in this quarter s column, Reza Dorrigiv and Alejandro Lopez-Ortiz review and compare various performance measures for online ...
Comments