What is he best known for?
The fields of study he is best known for:
- Algorithm
- Combinatorics
- Discrete mathematics
Johan Håstad spends much of his time researching Discrete mathematics, Combinatorics, Algorithm, Upper and lower bounds and Power.
His research integrates issues of Interactive proof system and Zero-knowledge proof in his study of Discrete mathematics.
His Combinatorics study combines topics from a wide range of disciplines, such as Computational complexity theory and System of linear equations.
His System of linear equations study incorporates themes from Modulo, Vertex cover and Prime.
His work on Pseudorandom generator, Pseudorandomness and Pseudorandom function family as part of general Algorithm research is frequently linked to Extraction and Self-shrinking generator, thereby connecting diverse disciplines of science.
Johan Håstad works mostly in the field of Upper and lower bounds, limiting it down to topics relating to Hadamard code and, in certain cases, Hardness of approximation.
His most cited work include:
- A Pseudorandom Generator from any One-way Function (1372 citations)
- Clique is hard to approximate within n1−ε (1286 citations)
- Some optimal inapproximability results (1284 citations)
What are the main themes of his work throughout his whole career to date?
Johan Håstad focuses on Discrete mathematics, Combinatorics, Time complexity, Upper and lower bounds and Approximation algorithm.
His Unique games conjecture study, which is part of a larger body of work in Discrete mathematics, is frequently linked to Omega, bridging the gap between disciplines.
His Combinatorics study combines topics in areas such as Bounded function and Constant.
As a member of one scientific family, Johan Håstad mostly works in the field of Time complexity, focusing on Prime and, on occasion, PCP theorem and Linear equation.
His Upper and lower bounds research includes themes of Space, Satisfiability and Proof complexity.
Johan Håstad interconnects Optimization problem, Semidefinite programming, System of linear equations and Approximation theory in the investigation of issues within Approximation algorithm.
He most often published in these fields:
- Discrete mathematics (65.34%)
- Combinatorics (61.93%)
- Time complexity (13.64%)
What were the highlights of his more recent work (between 2013-2021)?
- Discrete mathematics (65.34%)
- Combinatorics (61.93%)
- Omega (5.68%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Discrete mathematics, Combinatorics, Omega, Logarithm and Binary code.
His research in Discrete mathematics intersects with topics in Approximation algorithm and Hierarchy.
His biological study spans a wide range of topics, including Upper and lower bounds and Factor graph.
The various areas that Johan Håstad examines in his Upper and lower bounds study include Disjunctive normal form and Limit.
His studies deal with areas such as Polynomial and Discrete logarithm as well as Logarithm.
His Hypergraph research focuses on subjects like Short Code, which are linked to Hardness of approximation, Binary logarithm and Multiplicative function.
Between 2013 and 2021, his most popular works were:
- On the Correlation of Parity and Small-Depth Circuits (35 citations)
- An improved bound on the fraction of correctable deletions (34 citations)
- Super-polylogarithmic hypergraph coloring hardness via low-degree long codes (17 citations)
In his most recent research, the most cited papers focused on:
- Combinatorics
- Algorithm
- Discrete mathematics
His primary areas of investigation include Discrete mathematics, Combinatorics, Logarithm, Upper and lower bounds and Hierarchy.
Hypergraph is the focus of his Discrete mathematics research.
Specifically, his work in Combinatorics is concerned with the study of Arity.
His Logarithm research incorporates themes from Discrete logarithm and Integer.
His Upper and lower bounds study integrates concerns from other disciplines, such as Graph theory, Polynomial, Limit and Decoding methods.
The Hierarchy study combines topics in areas such as Polynomial hierarchy, Circuit complexity and Average-case complexity.
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