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Computer Science

D-Index
54
Citations
12846
World Ranking
4530
National Ranking
2123

Overview

Adam Wierman is affiliated with the California Institute of Technology in the United States. Their research spans primarily within the fields of Computer Science and Engineering, with notable contributions in several subfields including Computer Networks and Communications, Management Science and Operations Research, Electrical and Electronic Engineering, Artificial Intelligence, and Control and Systems Engineering.

Their work focuses on a range of topics, particularly:

  • Advanced Bandit Algorithms Research
  • Optimization and Search Problems
  • Auction Theory and Applications
  • Reinforcement Learning in Robotics
  • Distributed Control Multi-Agent Systems
  • Smart Grid Energy Management
  • Advanced Control Systems Optimization

Adam Wierman has published extensively, with a strong presence in several publication venues including arXiv (Cornell University), ACM SIGMETRICS Performance Evaluation Review, Proceedings of the ACM on Measurement and Analysis of Computing Systems, Operations Research, and the 2022 American Control Conference (ACC).

Recent papers authored or co-authored by Wierman cover diverse research topics and include:

  • Newton Polytopes and Relative Entropy Optimization, 2021, Foundations of Computational Mathematics
  • Competitive Algorithms for the Online Multiple Knapsack Problem with Application to Electric Vehicle Charging, 2020, Proceedings of the ACM on Measurement and Analysis of Computing Systems
  • An Energy Sharing Mechanism Considering Network Constraints and Market Power Limitation, 2022, IEEE Transactions on Smart Grid
  • Signomial and Polynomial Optimization via Relative Entropy and Partial Dualization, 2020, Mathematical Programming Computation
  • Stability Constrained Reinforcement Learning for Real-Time Voltage Control, 2022, 2022 American Control Conference (ACC)

The scientist frequently collaborates with other researchers, including Steven H. Low, Mohammad Hajiesmaili, Nicolas Christianson, Tongxin Li, and Guannan Qu.

In addition to journal and conference papers, Adam Wierman has contributed to academic books, with a publication titled "The Fundamentals of Heavy Tails" released by Cambridge University Press in 2022.

Best Publications

  • Dynamic right-sizing for power-proportional data centers

    Minghong Lin;Adam Wierman;Lachlan L. H. Andrew;Eno Thereska

  • Greening geographical load balancing

    Zhenhua Liu;Minghong Lin;Adam Wierman;Steven Low

  • Data center demand response: avoiding the coincident peak via workload shifting and local generation

    Zhenhua Liu;Adam Wierman;Yuan Chen;Benjamin Razon

  • Renewable and cooling aware workload management for sustainable data centers

    Zhenhua Liu;Yuan Chen;Cullen Bash;Adam Wierman

  • Online algorithms for geographical load balancing

    Minghong Lin;Zhenhua Liu;Adam Wierman;Lachlan L. H. Andrew

  • Open versus closed: a cautionary tale

    Bianca Schroeder;Adam Wierman;Mor Harchol-Balter

  • Power-Aware Speed Scaling in Processor Sharing Systems

    A. Wierman;L. L. H. Andrew;A. Tang

  • Distributed Welfare Games

    Jason R. Marden;Adam Wierman

  • Geographical load balancing with renewables

    Zhenhua Liu;Minghong Lin;Adam Wierman;Steven H. Low

  • Peer effects and stability in matching markets

    Elizabeth Bodine-Baron;Christina Lee;Anthony Chong;Babak Hassibi

  • Classifying scheduling policies with respect to unfairness in an M/GI/1

    Adam Wierman;Mor Harchol-Balter

  • Pricing data center demand response

    Zhenhua Liu;Iris Liu;Steven Low;Adam Wierman

  • Opportunities and challenges for data center demand response

    Adam Wierman;Zhenhua Liu;Iris Liu;Hamed Mohsenian-Rad

  • Optimality, fairness, and robustness in speed scaling designs

    Lachlan L.H. Andrew;Minghong Lin;Adam Wierman

  • GRASS: trimming stragglers in approximation analytics

    Ganesh Ananthanarayanan;Michael Chien-Chun Hung;Xiaoqi Ren;Ion Stoica

  • Hopper: Decentralized Speculation-aware Cluster Scheduling at Scale

    Xiaoqi Ren;Ganesh Ananthanarayanan;Adam Wierman;Minlan Yu

  • How to Determine a Good Multi-Programming Level for External Scheduling

    B. Schroeder;M. Harchol-Balter;A. Iyengar;E. Nahum

  • Real-time deferrable load control: handling the uncertainties of renewable generation

    Lingwen Gan;Adam Wierman;Ufuk Topcu;Niangjun Chen

  • An architectural view of game theoretic control

    Ragavendran Gopalakrishnan;Jason R. Marden;Adam Wierman

  • Multi-Server Queueing Systems with Multiple Priority Classes

    Mor Harchol-Balter;Takayuki Osogami;Alan Scheller-Wolf;Adam Wierman

  • Renewable and cooling aware workload management for sustainable data centers

    Unknown

Frequent Co-Authors

Steven H. Low
Steven H. Low California Institute of Technology
Lachlan L. H. Andrew
Lachlan L. H. Andrew University of Melbourne
Mor Harchol-Balter
Mor Harchol-Balter Carnegie Mellon University
Jason R. Marden
Jason R. Marden University of California, Santa Barbara
Babak Hassibi
Babak Hassibi California Institute of Technology
Shaolei Ren
Shaolei Ren University of California, Riverside
Yisong Yue
Yisong Yue California Institute of Technology
Soon-Jo Chung
Soon-Jo Chung California Institute of Technology
Onno Boxma
Onno Boxma Eindhoven University of Technology
Na Li
Na Li Harvard University

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