What is he best known for?
The fields of study he is best known for:
- Algorithm
- Artificial intelligence
- Computer network
Mathematical economics, Nash equilibrium, Mathematical optimization, Price of anarchy and Latency are his primary areas of study.
His Mathematical economics study combines topics in areas such as Common value auction and Inefficiency.
The various areas that Tim Roughgarden examines in his Nash equilibrium study include Network planning and design, Marginal cost, Game theory and Correlated equilibrium.
His research integrates issues of Function, Optimal mechanism, Scheduling and Probabilistic analysis of algorithms in his study of Mathematical optimization.
In Price of anarchy, Tim Roughgarden works on issues like Outcome, which are connected to Hardness of approximation.
His work deals with themes such as Network traffic control and Network performance, which intersect with Latency.
His most cited work include:
- How bad is selfish routing (1351 citations)
- Algorithmic Game Theory: Quantifying the Inefficiency of Equilibria (1177 citations)
- Algorithmic Game Theory: Computing in Games (1176 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Mathematical economics, Mathematical optimization, Common value auction, Theoretical computer science and Nash equilibrium.
His biological study spans a wide range of topics, including Computational complexity theory, Incentive and Price of anarchy.
His Mathematical optimization research is multidisciplinary, incorporating elements of Network planning and design and Function.
His Common value auction study often links to related topics such as Mechanism design.
His Nash equilibrium study incorporates themes from Correlated equilibrium, Shapley value and Latency.
His research in Algorithmic game theory is mostly concerned with Algorithmic mechanism design.
He most often published in these fields:
- Mathematical economics (31.69%)
- Mathematical optimization (29.07%)
- Common value auction (16.28%)
What were the highlights of his more recent work (between 2017-2021)?
- Mathematical economics (31.69%)
- Computational complexity theory (6.40%)
- Theoretical computer science (13.08%)
In recent papers he was focusing on the following fields of study:
Tim Roughgarden spends much of his time researching Mathematical economics, Computational complexity theory, Theoretical computer science, Algorithm and Mathematical optimization.
His work in the fields of Fair division overlaps with other areas such as Class.
His studies deal with areas such as Game theory, Stochastic game and Algorithmic game theory as well as Computational complexity theory.
His Algorithmic game theory study combines topics from a wide range of disciplines, such as Revenue maximization and Auction theory.
The Theoretical computer science study combines topics in areas such as Learnability and Robustness.
The concepts of his Mathematical optimization study are interwoven with issues in Optimal mechanism and Rule of thumb.
Between 2017 and 2021, his most popular works were:
- Almost envy-freeness with general valuations (63 citations)
- Beyond worst-case analysis (32 citations)
- Making the Most of Your Samples (27 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Artificial intelligence
- Computer network
The scientist’s investigation covers issues in Mathematical economics, Monotone polygon, Submodular set function, Fair division and Algorithm.
Specifically, his work in Mathematical economics is concerned with the study of Game theory.
There are a combination of areas like Equilibrium point, Binary search algorithm, Optimization problem, Graph and Boolean function integrated together with his Monotone polygon study.
His research in Fair division intersects with topics in Discrete mathematics, Submodular function minimization and Pareto principle.
His work carried out in the field of Algorithm brings together such families of science as Function and Maximization.
His Class research spans across into areas like Communication complexity, Valuation, Polynomial, Proportionality and Discount points.
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