H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 97 Citations 73,268 383 World Ranking 166 National Ranking 100

Research.com Recognitions

Awards & Achievements

2017 - SIAM Fellow For contributions to data mining and high performance computing.

2006 - Fellow of the American Association for the Advancement of Science (AAAS)

2005 - ACM Fellow For contributions to the design and analysis of parallel algorithms.

2000 - IEEE Fellow For the development of the isoefficiency metric of scalability and contributions to scalable parallel computing.

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

His primary areas of study are Data mining, Artificial intelligence, Cluster analysis, Parallel computing and Algorithm. His Data mining study integrates concerns from other disciplines, such as Categorization and Data set. His research investigates the connection with Artificial intelligence and areas like Machine learning which intersect with concerns in Combinatorial search.

The Parallel computing study combines topics in areas such as Distributed computing and Search algorithm. His Algorithm study incorporates themes from Hypergraph, Graph partition, Classifier, Graph theory and Vertex. His Graph partition research is multidisciplinary, incorporating perspectives in Sparse matrix, Theoretical computer science and Independent set.

His most cited work include:

  • Introduction to Data Mining (6978 citations)
  • Anomaly detection: A survey (6140 citations)
  • A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs (4174 citations)

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

His main research concerns Data mining, Artificial intelligence, Parallel computing, Parallel algorithm and Algorithm. His Data mining research includes themes of Set, Data set and Cluster analysis. His Artificial intelligence study combines topics from a wide range of disciplines, such as Machine learning and Pattern recognition.

He has included themes like Scalability and Computation in his Parallel computing study. His research on Parallel algorithm frequently connects to adjacent areas such as Sparse matrix. Many of his studies on Algorithm apply to Graph partition as well.

He most often published in these fields:

  • Data mining (21.30%)
  • Artificial intelligence (16.27%)
  • Parallel computing (10.58%)

What were the highlights of his more recent work (between 2015-2021)?

  • Artificial intelligence (16.27%)
  • Machine learning (8.20%)
  • Data science (7.41%)

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

Artificial intelligence, Machine learning, Data science, Data mining and Deep learning are his primary areas of study. His studies in Artificial intelligence integrate themes in fields like Set and Pattern recognition. Vipin Kumar has researched Machine learning in several fields, including Data modeling and Big data.

His study in Data science is interdisciplinary in nature, drawing from both Field and Domain knowledge. His research in Data mining intersects with topics in Domain, Time series, Noise, Scale and Process. His study looks at the intersection of Time series and topics like Series with Multivariate statistics and Interval.

Between 2015 and 2021, his most popular works were:

  • Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data (285 citations)
  • Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling (129 citations)
  • Spatio-Temporal Data Mining: A Survey of Problems and Methods (114 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

Vipin Kumar mostly deals with Artificial intelligence, Machine learning, Data science, Landslide and Shear stress. His work deals with themes such as Consistency and Data modeling, which intersect with Artificial intelligence. His Machine learning research is multidisciplinary, incorporating elements of Land cover and Data mining, Big data.

The study incorporates disciplines such as Variation, Satellite imagery, Deforestation and climate change, Scale and Process in addition to Data mining. His Data science research also works with subjects such as

  • Time series together with Change detection, Spatial analysis, Anomaly detection and Relational database,
  • Healthcare system and Disease prognosis most often made with reference to Health records. He interconnects Field and Cluster analysis in the investigation of issues within Change detection.

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

Introduction to Data Mining

Pang-Ning Tan;Michael M. Steinbach;Vipin Kumar.
(2005)

13791 Citations

Anomaly detection: A survey

Varun Chandola;Arindam Banerjee;Vipin Kumar.
ACM Computing Surveys (2009)

8386 Citations

A Fast and High Quality Multilevel Scheme for Partitioning Irregular Graphs

George Karypis;Vipin Kumar.
SIAM Journal on Scientific Computing (1998)

5920 Citations

Top 10 algorithms in data mining

Xindong Wu;Vipin Kumar;J. Ross Quinlan;Joydeep Ghosh.
Knowledge and Information Systems (2007)

5181 Citations

A Comparison of Document Clustering Techniques

Michael Steinbach;George Karypis;Vipin Kumar.
(2000)

3578 Citations

Chameleon: hierarchical clustering using dynamic modeling

G. Karypis;Eui-Hong Han;V. Kumar.
IEEE Computer (1999)

2913 Citations

Introduction to Parallel Computing

Vipin Kumar.
(2003)

2732 Citations

Introduction to parallel computing: design and analysis of algorithms

Vipin Kumar;Ananth Grama;Anshul Gupta;George Karypis.
(1994)

2435 Citations

Introduction to Data Mining, (First Edition)

Pang-Ning Tan;Michael Steinbach;Vipin Kumar.
(2005)

2048 Citations

Multilevelk-way Partitioning Scheme for Irregular Graphs

George Karypis;Vipin Kumar.
Journal of Parallel and Distributed Computing (1998)

2012 Citations

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