What is he best known for?
The fields of study he is best known for:
- Algorithm
- Algebra
- Combinatorics
Combinatorics, Discrete mathematics, Algorithm, Parallel algorithm and Polygon mesh are his primary areas of study.
His studies link Upper and lower bounds with Combinatorics.
The concepts of his Discrete mathematics study are interwoven with issues in Primality test, Symmetric matrix and Diagonally dominant matrix.
Gary L. Miller works mostly in the field of Algorithm, limiting it down to topics relating to Parallel mesh generation and, in certain cases, Pitteway triangulation and Ruppert's algorithm.
His Parallel algorithm research is multidisciplinary, incorporating elements of Binary logarithm, Simple and Theoretical computer science.
Structure, Mathematical proof, Finite difference method, Partition and Randomized algorithm is closely connected to Finite element method in his research, which is encompassed under the umbrella topic of Polygon mesh.
His most cited work include:
- Riemann's hypothesis and tests for primality (585 citations)
- Optimal route selection in a content delivery network (427 citations)
- Parallel tree contraction and its application (364 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Combinatorics, Discrete mathematics, Algorithm, Parallel algorithm and Theoretical computer science.
His Combinatorics study frequently draws connections to adjacent fields such as Diagonally dominant matrix.
His studies deal with areas such as Linear system and Spanning tree as well as Diagonally dominant matrix.
His Discrete mathematics study deals with Voronoi diagram intersecting with Subset and superset.
His Algorithm research is multidisciplinary, incorporating perspectives in Graph, Mesh generation and Polygon mesh.
The various areas that Gary L. Miller examines in his Parallel algorithm study include Tree, Graph algorithms and Parallel processing.
He most often published in these fields:
- Combinatorics (48.26%)
- Discrete mathematics (42.61%)
- Algorithm (21.30%)
What were the highlights of his more recent work (between 2010-2020)?
- Combinatorics (48.26%)
- Discrete mathematics (42.61%)
- Linear system (9.57%)
In recent papers he was focusing on the following fields of study:
His main research concerns Combinatorics, Discrete mathematics, Linear system, Graph and Maximum flow problem.
His Combinatorics research includes themes of Parallel algorithm and Exponential function.
He does research in Discrete mathematics, focusing on Hopcroft–Karp algorithm specifically.
His Linear system research includes themes of Solver, Theoretical computer science and Diagonally dominant matrix.
The Graph study combines topics in areas such as Algorithm, Mathematical optimization and Data structure.
His work deals with themes such as Flow, Vertex, Bounded function and Isotropy, which intersect with Maximum flow problem.
Between 2010 and 2020, his most popular works were:
- Coordinating Pebble Motion on Graphs, the Diameter of Permutation Groups and Applications (196 citations)
- A Nearly-m log n Time Solver for SDD Linear Systems (132 citations)
- Efficient Triangle Counting in Large Graphs via Degree-Based Vertex Partitioning (115 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Algebra
- Combinatorics
Gary L. Miller focuses on Combinatorics, Linear system, Discrete mathematics, Diagonally dominant matrix and Mathematical optimization.
His Combinatorics study integrates concerns from other disciplines, such as Parallel algorithm, Sequential algorithm and Algorithm design.
His Linear system research incorporates elements of Solver and Theoretical computer science.
His studies in Discrete mathematics integrate themes in fields like Power diagram, Centroidal Voronoi tessellation and Dimension.
His Diagonally dominant matrix study which covers Spanning tree that intersects with Chain and Matrix.
His study in Mathematical optimization is interdisciplinary in nature, drawing from both Covering problems, Graph and Core.
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