D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 45 Citations 13,325 128 World Ranking 3549 National Ranking 44

Research.com Recognitions

Awards & Achievements

1996 - ACM Fellow For contributions to knowledge-based systems research and applications, to statistical methods in pattern recognition, and to leadership in artificial intelligence.

1986 - IEEE Fellow For contributions to statistical pattern recognition and artificial intelligence.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Programming language
  • Operating system

B. Chandrasekaran mainly focuses on Artificial intelligence, Knowledge base, Model-based reasoning, Knowledge-based systems and Task. The concepts of his Artificial intelligence study are interwoven with issues in Machine learning, Sample size determination and Pattern recognition. His Knowledge base research focuses on subjects like Expert system, which are linked to Knowledge acquisition.

He focuses mostly in the field of Model-based reasoning, narrowing it down to matters related to Subject-matter expert and, in some cases, Knowledge representation and reasoning, Intelligent decision support system and Context. His work carried out in the field of Knowledge representation and reasoning brings together such families of science as Knowledge management and Data science. B. Chandrasekaran combines subjects such as Knowledge modeling, Management science, Function and Human–computer interaction with his study of Task.

His most cited work include:

  • What are ontologies, and why do we need them? (1411 citations)
  • Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design (688 citations)
  • 39 Dimensionality and sample size considerations in pattern recognition practice (473 citations)

What are the main themes of his work throughout his whole career to date?

B. Chandrasekaran spends much of his time researching Artificial intelligence, Diagrammatic reasoning, Task, Theoretical computer science and Expert system. Function is closely connected to Structure in his research, which is encompassed under the umbrella topic of Artificial intelligence. His study in Diagrammatic reasoning is interdisciplinary in nature, drawing from both Domain, Cognitive architecture, Representation and Inference.

His research in Theoretical computer science intersects with topics in Representation and Component. His work deals with themes such as Knowledge management, Knowledge-based systems, Software engineering and Knowledge base, which intersect with Expert system. His Knowledge base research is multidisciplinary, relying on both Domain knowledge and Knowledge engineering.

He most often published in these fields:

  • Artificial intelligence (47.21%)
  • Diagrammatic reasoning (14.21%)
  • Task (13.71%)

What were the highlights of his more recent work (between 2003-2019)?

  • Diagrammatic reasoning (14.21%)
  • Artificial intelligence (47.21%)
  • Theoretical computer science (12.69%)

In recent papers he was focusing on the following fields of study:

B. Chandrasekaran mostly deals with Diagrammatic reasoning, Artificial intelligence, Theoretical computer science, Cognitive architecture and Domain. His Diagrammatic reasoning research includes themes of Diagram, Inference, Component and Knowledge representation and reasoning. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Cognitive science and Set.

His Theoretical computer science research incorporates elements of Space, Representation and Representation. His Cognitive architecture study combines topics in areas such as Soar, Task, Perception and Computational model. His Domain research integrates issues from Constraint satisfaction, Solver and Constraint satisfaction problem.

Between 2003 and 2019, his most popular works were:

  • Representing function: Relating functional representation and functional modeling research streams (85 citations)
  • Microbenchmark performance comparison of high-speed cluster interconnects (78 citations)
  • An Architecture for Problem Solving with Diagrams (38 citations)

In his most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Programming language
  • Algorithm

B. Chandrasekaran focuses on Diagrammatic reasoning, Theoretical computer science, Artificial intelligence, Domain and Cognitive architecture. His studies deal with areas such as Symbol, Diagram and Component as well as Diagrammatic reasoning. His studies in Component integrate themes in fields like Spatial relation, Knowledge base, Matching, Software architecture and Model-based reasoning.

His Theoretical computer science study incorporates themes from Ontology, Structure, Layer and Knowledge representation and reasoning. The study incorporates disciplines such as Solver, Decision problem and Constraint satisfaction problem in addition to Domain. The various areas that B. Chandrasekaran examines in his Set study include Representation and Expert system.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

What are ontologies, and why do we need them?

B. Chandrasekaran;J.R. Josephson;V.R. Benjamins.
IEEE Intelligent Systems & Their Applications (1999)

2725 Citations

Generic Tasks in Knowledge-Based Reasoning: High-Level Building Blocks for Expert System Design

B. Chandrasekaran.
IEEE Intelligent Systems (1986)

1074 Citations

39 Dimensionality and sample size considerations in pattern recognition practice

Anil K. Jain;B. Chandrasekaran.
Handbook of Statistics (1982)

740 Citations

The paradoxical success of fuzzy logic

C. Elkan;H.R. Berenji;B. Chandrasekaran;C.J.S. de Silva.
IEEE Intelligent Systems (1994)

435 Citations

Generic tasks for knowledge-based reasoning: the “right” level of abstraction for knowledge acquisition

T. Bylander;B. Chandrasekaran.
International Journal of Human-computer Studies / International Journal of Man-machine Studies (1987)

408 Citations

What Are They? Why Do We Need Them?

B. Chandrasekaran;J.R. Josephson;V.R. Benjamins.
IEEE Intelligent Systems (1999)

404 Citations

Task-structure analysis for knowledge modeling

B. Chandrasekaran;Todd R. Johnson;Jack W. Smith.
Communications of The ACM (1992)

400 Citations

Diagrammatic Reasoning: Cognitive and Computational Perspectives

Janice Glasgow;N. Hari Narayanan;B. Chandrasekaran.
Computational Imagery (1995)

363 Citations

Towards a Taxonomy of Problem Solving Types

B. Chandrasekaran.
Ai Magazine (1983)

353 Citations

Design Problem Solving: Knowledge Structures and Control Strategies

David C. Brown;B. Chandrasekaran.
(1989)

350 Citations

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