What is he best known for?
The fields of study he is best known for:
- Algorithm
- Computer network
- Mathematical optimization
Kirk Pruhs mainly investigates Mathematical optimization, Competitive analysis, Scheduling, Online algorithm and Power management.
His work on Greedy algorithm as part of general Mathematical optimization study is frequently linked to Schedule and Constant, bridging the gap between disciplines.
His Competitive analysis study is associated with Upper and lower bounds.
His work investigates the relationship between Scheduling and topics such as Parallel computing that intersect with problems in Adversary and Least slack time scheduling.
In his research, Kirk Pruhs performs multidisciplinary study on Online algorithm and Ellipsoid method.
His Fixed-priority pre-emptive scheduling research includes themes of Round-robin scheduling and Two-level scheduling.
His most cited work include:
- Speed is as powerful as clairvoyance (444 citations)
- Speed scaling to manage energy and temperature (328 citations)
- Algorithmic problems in power management (245 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Scheduling, Mathematical optimization, Competitive analysis, Online algorithm and Algorithm.
His work on Fair-share scheduling as part of his general Scheduling study is frequently connected to Flow time, thereby bridging the divide between different branches of science.
Kirk Pruhs combines subjects such as Speed scaling, Bounded function and Job shop scheduling with his study of Mathematical optimization.
The Competitive analysis study which covers Combinatorics that intersects with Server and Power function.
His Online algorithm study incorporates themes from Matching, Graph theory, Discrete mathematics and Greedy algorithm.
His Algorithm research incorporates elements of Frequency allocation and Notation.
He most often published in these fields:
- Scheduling (42.04%)
- Mathematical optimization (36.31%)
- Competitive analysis (29.94%)
What were the highlights of his more recent work (between 2010-2020)?
- Scheduling (42.04%)
- Mathematical optimization (36.31%)
- Online algorithm (26.75%)
In recent papers he was focusing on the following fields of study:
Kirk Pruhs mostly deals with Scheduling, Mathematical optimization, Online algorithm, Competitive analysis and Upper and lower bounds.
The study incorporates disciplines such as Discrete mathematics and Parallel computing in addition to Scheduling.
His Mathematical optimization research focuses on Job shop scheduling and how it relates to Algorithm.
His Online algorithm study combines topics from a wide range of disciplines, such as Routing, Computer network, Logarithm and Greedy algorithm.
His work in Competitive analysis tackles topics such as Simulation which are related to areas like Telecommunications.
His Fair-share scheduling research is multidisciplinary, incorporating elements of Theoretical computer science and Dynamic priority scheduling.
Between 2010 and 2020, his most popular works were:
- Online Primal-Dual for Non-linear Optimization with Applications to Speed Scaling (57 citations)
- Scheduling heterogeneous processors isn't as easy as you think (53 citations)
- A tutorial on amortized local competitiveness in online scheduling (47 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Computer network
- Scheduling
Kirk Pruhs focuses on Scheduling, Mathematical optimization, Competitive analysis, Online algorithm and Fair-share scheduling.
His research integrates issues of Special case and Parallel computing in his study of Scheduling.
His study in the field of Linear programming and Greedy algorithm also crosses realms of Weak duality and Virtual circuit.
His Competitive analysis research includes elements of Quality of service, Theory of computation, Simulation and Combinatorics.
His Simulation study combines topics in areas such as Flow, Algorithm and Speed scaling.
His biological study spans a wide range of topics, including Database server and Theoretical computer science.
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