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 33 Citations 5,861 75 World Ranking 6804 National Ranking 3249

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Algorithm

Kumar Chellapilla spends much of his time researching Artificial intelligence, Mathematical proof, Machine learning, Evolutionary programming and Genetic programming. He works mostly in the field of Artificial intelligence, limiting it down to topics relating to The Internet and, in certain cases, Pattern recognition. His Evolutionary programming research focuses on Algorithm and how it relates to Reverse engineering, Bitmap and Image warping.

His Genetic programming research incorporates themes from Programming language and Genetic algorithm, Mathematical optimization. As a member of one scientific family, Kumar Chellapilla mostly works in the field of Mathematical optimization, focusing on Crossover and, on occasion, Theoretical computer science. His work deals with themes such as Evolutionary algorithm, Contrast and Outcome, which intersect with Artificial neural network.

His most cited work include:

  • High Performance Convolutional Neural Networks for Document Processing (325 citations)
  • Using Machine Learning to Break Visual Human Interaction Proofs (HIPs) (222 citations)
  • Combining mutation operators in evolutionary programming (217 citations)

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

Kumar Chellapilla mainly focuses on Artificial intelligence, Evolutionary programming, Algorithm, Evolutionary computation and Evolutionary algorithm. Kumar Chellapilla interconnects Machine learning, Speech recognition and Pattern recognition in the investigation of issues within Artificial intelligence. His research in Evolutionary programming focuses on subjects like Genetic representation, which are connected to Java Evolutionary Computation Toolkit.

His work in the fields of Bloom filter and Optimization problem overlaps with other areas such as Binary form. Within one scientific family, Kumar Chellapilla focuses on topics pertaining to Genetic algorithm under Evolutionary algorithm, and may sometimes address concerns connected to Genetic programming and Crossover. In Segmentation, Kumar Chellapilla works on issues like Convolutional neural network, which are connected to Speedup.

He most often published in these fields:

  • Artificial intelligence (31.37%)
  • Evolutionary programming (18.63%)
  • Algorithm (16.67%)

What were the highlights of his more recent work (between 2008-2012)?

  • Theoretical computer science (9.80%)
  • Classifier (6.86%)
  • Voltage graph (3.92%)

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

His main research concerns Theoretical computer science, Classifier, Voltage graph, Artificial intelligence and Algorithm. His Theoretical computer science research includes themes of Trie, Scalability and Graph, Graph compression. His work carried out in the field of Classifier brings together such families of science as Data mining, Malware analysis and Top-down and bottom-up design.

His Artificial intelligence research incorporates elements of Web search query, Search engine, Machine learning and Behavioral pattern. His studies deal with areas such as Anomaly detection and Web traffic as well as Web search query. His study looks at the relationship between Algorithm and topics such as Block graph, which overlap with Outerplanar graph, Comparability graph and Butterfly graph.

Between 2008 and 2012, his most popular works were:

  • Finding Dense Subgraphs with Size Bounds (162 citations)
  • Bottom-up analysis of network sites (45 citations)
  • WebCop: locating neighborhoods of malware on the web (40 citations)

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

  • Artificial intelligence
  • Machine learning
  • Algorithm

Kumar Chellapilla focuses on Computer security, Suspect, Top-down and bottom-up design, Classifier and Malware analysis. His Computer security study incorporates themes from Web page, World Wide Web, The Internet and Web crawler. Kumar Chellapilla incorporates Suspect and Data mining in his studies.

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

High Performance Convolutional Neural Networks for Document Processing

Kumar Chellapilla;Sidd Puri;Patrice Simard.
international conference on frontiers in handwriting recognition (2006)

492 Citations

Using Machine Learning to Break Visual Human Interaction Proofs (HIPs)

Kumar Chellapilla;Patrice Y. Simard.
neural information processing systems (2004)

365 Citations

Building segmentation based human-friendly human interaction proofs (HIPs)

Kumar Chellapilla;Kevin Larson;Patrice Y. Simard;Mary Czerwinski.
Lecture Notes in Computer Science (2005)

354 Citations

Combining mutation operators in evolutionary programming

K. Chellapilla.
IEEE Transactions on Evolutionary Computation (1998)

309 Citations

Evolving an expert checkers playing program without using human expertise

K. Chellapilla;D.B. Fogel.
IEEE Transactions on Evolutionary Computation (2001)

265 Citations

Designing human friendly human interaction proofs (HIPs)

Kumar Chellapilla;Kevin Larson;Patrice Simard;Mary Czerwinski.
human factors in computing systems (2005)

264 Citations

Computers beat Humans at Single Character Recognition in Reading based Human Interaction Proofs (HIPs)

Kumar Chellapilla;Kevin Larson;Patrice Y. Simard;Mary Czerwinski.
conference on email and anti-spam (2005)

261 Citations

A scalable pattern mining approach to web graph compression with communities

Gregory Buehrer;Kumar Chellapilla.
web search and data mining (2008)

251 Citations

Evolution, neural networks, games, and intelligence

K. Chellapilla;D.B. Fogel.
Proceedings of the IEEE (1999)

246 Citations

Evolving neural networks to play checkers without relying on expert knowledge

K. Chellapilla;D.B. Fogel.
IEEE Transactions on Neural Networks (1999)

235 Citations

Best Scientists Citing Kumar Chellapilla

G. Glenn Henry

G. Glenn Henry

Centaur Technology

Publications: 28

Xin Yao

Xin Yao

Southern University of Science and Technology

Publications: 23

Graham Kendall

Graham Kendall

University of Nottingham Malaysia Campus

Publications: 22

Simon M. Lucas

Simon M. Lucas

Queen Mary University of London

Publications: 21

Rajarshi Gupta

Rajarshi Gupta

Amazon Web Services

Publications: 17

John R. Koza

John R. Koza

Stanford University

Publications: 17

Francesco Bonchi

Francesco Bonchi

Institute for Scientific Interchange

Publications: 17

Zbigniew Michalewicz

Zbigniew Michalewicz

University of Adelaide

Publications: 15

Ping Li

Ping Li

Baidu (United States)

Publications: 14

Ajith Abraham

Ajith Abraham

Machine Intelligence Research Labs

Publications: 14

Jürgen Schmidhuber

Jürgen Schmidhuber

Dalle Molle Institute for Artificial Intelligence Research

Publications: 13

Christian Igel

Christian Igel

University of Copenhagen

Publications: 12

Willy Susilo

Willy Susilo

University of Wollongong

Publications: 11

Aristides Gionis

Aristides Gionis

Royal Institute of Technology

Publications: 11

Leandro dos Santos Coelho

Leandro dos Santos Coelho

Pontifícia Universidade Católica do Paraná

Publications: 11

Sung-Bae Cho

Sung-Bae Cho

Yonsei University

Publications: 10

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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