What is he best known for?
The fields of study he is best known for:
- Algorithm
- Combinatorics
- Artificial intelligence
Shang-Hua Teng mainly focuses on Combinatorics, Discrete mathematics, Algorithm, Smoothed analysis and Time complexity.
His Combinatorics research is multidisciplinary, incorporating perspectives in Polygon mesh and Nash equilibrium.
As part of his studies on Discrete mathematics, he often connects relevant areas like Laplace operator.
His biological study spans a wide range of topics, including Webcast, Conformal map, Data mining and Feature.
His studies in Smoothed analysis integrate themes in fields like Computational complexity theory, Property testing and Revised simplex method, Simplex algorithm.
Shang-Hua Teng has researched Time complexity in several fields, including Travelling salesman problem, Database, Heuristics and Metric space.
His most cited work include:
- Metadata search results ranking system (689 citations)
- Nearly-linear time algorithms for graph partitioning, graph sparsification, and solving linear systems (658 citations)
- Smoothed analysis of algorithms: Why the simplex algorithm usually takes polynomial time (644 citations)
What are the main themes of his work throughout his whole career to date?
The scientist’s investigation covers issues in Combinatorics, Discrete mathematics, Algorithm, Theoretical computer science and Time complexity.
His study looks at the relationship between Combinatorics and fields such as Polygon mesh, as well as how they intersect with chemical problems.
His Discrete mathematics research integrates issues from Upper and lower bounds, Bounded function, Nash equilibrium and Computation.
The concepts of his Theoretical computer science study are interwoven with issues in Centrality, Data mining, Social network, Artificial intelligence and Function.
In his research on the topic of Time complexity, Mathematical optimization and Separable space is strongly related with Mathematical economics.
The Smoothed analysis study combines topics in areas such as Condition number and Simplex algorithm.
He most often published in these fields:
- Combinatorics (32.73%)
- Discrete mathematics (33.09%)
- Algorithm (19.64%)
What were the highlights of his more recent work (between 2010-2021)?
- Discrete mathematics (33.09%)
- Theoretical computer science (16.36%)
- Combinatorics (32.73%)
In recent papers he was focusing on the following fields of study:
His scientific interests lie mostly in Discrete mathematics, Theoretical computer science, Combinatorics, Centrality and Algorithm.
His work on Laplacian matrix and Line graph as part of general Discrete mathematics research is frequently linked to Quantum logic, Quantum technology and Quantum gate, bridging the gap between disciplines.
His research integrates issues of Graph, Network dynamics, Dynamic network analysis and Social network in his study of Theoretical computer science.
His study in Combinatorics is interdisciplinary in nature, drawing from both Condition number and Canonical form.
His study in Centrality is interdisciplinary in nature, drawing from both Shapley value, Network science and Artificial intelligence.
His Algorithm research incorporates elements of Matrix, Logarithm and PageRank.
Between 2010 and 2021, his most popular works were:
- A LOCAL CLUSTERING ALGORITHM FOR MASSIVE GRAPHS AND ITS APPLICATION TO NEARLY LINEAR TIME GRAPH PARTITIONING (273 citations)
- Nearly Linear Time Algorithms for Preconditioning and Solving Symmetric, Diagonally Dominant Linear Systems (263 citations)
- Spectral Sparsification of Graphs (219 citations)
In his most recent research, the most cited papers focused on:
- Algorithm
- Combinatorics
- Artificial intelligence
Shang-Hua Teng mainly investigates Discrete mathematics, Combinatorics, Algorithm, Laplacian matrix and Mathematical optimization.
Shang-Hua Teng interconnects System of linear equations and Laplace operator in the investigation of issues within Discrete mathematics.
Combinatorics and Suurballe's algorithm are two areas of study in which Shang-Hua Teng engages in interdisciplinary work.
Shang-Hua Teng studies Algorithm, namely Time complexity.
His Laplacian matrix study combines topics in areas such as Graph theory, Spectral geometry and Planar graph.
His work on Nash equilibrium as part of general Mathematical optimization study is frequently linked to Network traffic control and Quality of service, therefore connecting diverse disciplines of science.
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