What is he best known for?
The fields of study he is best known for:
- Computer network
- Algorithm
- Artificial intelligence
Algorithm, Combinatorics, Mathematical optimization, Distributed computing and Computer network are his primary areas of study.
His work deals with themes such as Piecewise linear function, Probabilistic analysis of algorithms, Floyd–Warshall algorithm, Path and Trajectory, which intersect with Algorithm.
His Combinatorics research is multidisciplinary, incorporating elements of Discrete mathematics, Plane and Convex polytope.
His work carried out in the field of Mathematical optimization brings together such families of science as Bidding, Combinatorial auction, Spectrum auction and Auction algorithm.
The study incorporates disciplines such as Mobile ad hoc network, Wireless ad hoc network, Wireless sensor network and Communications protocol in addition to Distributed computing.
Computer network is closely attributed to Scalability in his study.
His most cited work include:
- Towards realistic mobility models for mobile ad hoc networks (575 citations)
- Fast and scalable layer four switching (555 citations)
- Packet classification using tuple space search (509 citations)
What are the main themes of his work throughout his whole career to date?
His primary scientific interests are in Combinatorics, Discrete mathematics, Algorithm, Theoretical computer science and Mathematical optimization.
His Combinatorics study incorporates themes from Point, Plane and Polygon.
His Polygon research is multidisciplinary, relying on both Visibility and Regular polygon.
His Discrete mathematics research includes themes of Upper and lower bounds and Data structure.
His studies in Algorithm integrate themes in fields like Data stream and Wireless sensor network.
The concepts of his Mathematical optimization study are interwoven with issues in Auction theory, Convex hull and Combinatorial auction.
He most often published in these fields:
- Combinatorics (40.95%)
- Discrete mathematics (18.40%)
- Algorithm (13.06%)
What were the highlights of his more recent work (between 2013-2021)?
- Combinatorics (40.95%)
- Discrete mathematics (18.40%)
- Point (8.31%)
In recent papers he was focusing on the following fields of study:
His primary areas of study are Combinatorics, Discrete mathematics, Point, Plane and Approximation algorithm.
His research in Combinatorics intersects with topics in Rectangle, Upper and lower bounds and Regular polygon.
His work in Discrete mathematics addresses issues such as Hyperbolic space, which are connected to fields such as Book embedding.
His Point study combines topics in areas such as Probabilistic logic, Art gallery problem, Convex hull and k-nearest neighbors algorithm.
His study focuses on the intersection of Plane and fields such as Path with connections in the field of Function.
His Approximation algorithm study deals with the bigger picture of Mathematical optimization.
Between 2013 and 2021, his most popular works were:
- On the Complexity of Time-Dependent Shortest Paths (54 citations)
- Metric Embedding, Hyperbolic Space, and Social Networks (37 citations)
- Convex Hulls under Uncertainty (28 citations)
In his most recent research, the most cited papers focused on:
- Computer network
- Algorithm
- Operating system
Subhash Suri mainly investigates Combinatorics, Point, Discrete mathematics, Convex hull and Approximation algorithm.
His Combinatorics study combines topics from a wide range of disciplines, such as Upper and lower bounds, Pursuit-evasion and k-nearest neighbors algorithm.
His research investigates the link between Point and topics such as Computational geometry that cross with problems in Closest pair of points problem, Data structure, Star-shaped polygon, Art gallery problem and Monotone polygon.
The Discrete mathematics study combines topics in areas such as Function, Linear function, Hyperbolic space and Shortest path problem.
Approximation algorithm is a subfield of Mathematical optimization that Subhash Suri studies.
Subhash Suri focuses mostly in the field of Mathematical optimization, narrowing it down to topics relating to Representation and, in certain cases, Algorithm, Regret, Very large database, Greedy algorithm and Minification.
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