What is he best known for?
The fields of study he is best known for:
- Statistics
- Operating system
- Microeconomics
His primary scientific interests are in Distributed computing, Data center, Scheduling, Real-time computing and Workload.
His Distributed computing research is multidisciplinary, relying on both Speculative execution, Theoretical computer science, Resource allocation and Operations research.
His Data center study also includes
- Demand response and related Environmental economics and Flexibility,
- Load balancing and related Distributed algorithm.
His Scheduling research is multidisciplinary, incorporating perspectives in Queue and Scalability.
His work is dedicated to discovering how Real-time computing, Server are connected with Online algorithm and other disciplines.
His Processor sharing research integrates issues from Mathematical optimization and Robustness.
His most cited work include:
- Greening geographical load balancing (408 citations)
- Renewable and cooling aware workload management for sustainable data centers (341 citations)
- Dynamic right-sizing for power-proportional data centers (332 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Mathematical optimization, Scheduling, Distributed computing, Competitive analysis and Online algorithm.
His Mathematical optimization study combines topics from a wide range of disciplines, such as Control, Upper and lower bounds and Regret.
Adam Wierman combines subjects such as Workload, Queue, Queueing theory and Response time with his study of Scheduling.
Adam Wierman has included themes like Real-time computing and Operations research in his Workload study.
The Real-time computing study which covers Data center that intersects with Supply.
His study looks at the relationship between Distributed computing and topics such as Server, which overlap with Load balancing.
He most often published in these fields:
- Mathematical optimization (28.68%)
- Scheduling (18.11%)
- Distributed computing (16.98%)
What were the highlights of his more recent work (between 2019-2021)?
- Mathematical optimization (28.68%)
- Electric power system (7.92%)
- Distributed computing (16.98%)
In recent papers he was focusing on the following fields of study:
Adam Wierman spends much of his time researching Mathematical optimization, Electric power system, Distributed computing, Control and Competitive analysis.
Adam Wierman interconnects State and Server in the investigation of issues within Mathematical optimization.
The various areas that Adam Wierman examines in his Electric power system study include Automatic frequency control, Control theory and Reliability.
While the research belongs to areas of Distributed computing, Adam Wierman spends his time largely on the problem of Scalability, intersecting his research to questions surrounding Structure, Workload and Entropy.
His work deals with themes such as Online algorithm and Online optimization, which intersect with Competitive analysis.
His work in Throughput addresses issues such as Queue, which are connected to fields such as Scheduling.
Between 2019 and 2021, his most popular works were:
- Finite-Time Analysis of Asynchronous Stochastic Approximation and $Q$-Learning (16 citations)
- Signomial and Polynomial Optimization via Relative Entropy and Partial Dualization (9 citations)
- Online Optimization with Predictions and Non-convex Losses (9 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Operating system
- Computer network
His primary areas of investigation include Mathematical optimization, Control, Constant, Competitive analysis and Online optimization.
His studies deal with areas such as Nonlinear control, Temporal difference learning, Contrast, Dynamical system and State as well as Mathematical optimization.
His Control research includes elements of Upper and lower bounds and Regret.
His Competitive analysis research incorporates elements of Connection, Online algorithm, Leverage and Descent.
Borrowing concepts from Class, Adam Wierman weaves in ideas under Convex optimization.
Class is intertwined with Scalability, Structure, Distributed computing, Distance and Property in his study.
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