H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 61 Citations 17,717 237 World Ranking 1453 National Ranking 141

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of study are Data mining, Artificial intelligence, Machine learning, Intrusion detection system and Data stream mining. In his research, he undertakes multidisciplinary study on Data mining and Credit card fraud. Wei Fan has researched Artificial intelligence in several fields, including Weighting, Graph and Pattern recognition.

His Machine learning study frequently links to related topics such as Classifier. His work carried out in the field of Intrusion detection system brings together such families of science as Security policy, Anomaly detection and Computer network, Mobile computing. His research integrates issues of Data stream and Training set in his study of Data stream mining.

His most cited work include:

  • Mining concept-drifting data streams using ensemble classifiers (1075 citations)
  • Method and system for using intelligent agents for financial transactions, services, accounting, and advice (554 citations)
  • Mining big data: current status, and forecast to the future (521 citations)

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

Wei Fan spends much of his time researching Artificial intelligence, Data mining, Machine learning, Pattern recognition and Information retrieval. His studies in Artificial intelligence integrate themes in fields like Graph, Computer vision and Natural language processing. The Data mining study combines topics in areas such as Scalability and Cluster analysis.

His studies in Semi-supervised learning, Decision tree, Unsupervised learning, Boosting and Transfer of learning are all subfields of Machine learning research. His research ties Feature and Pattern recognition together. Many of his studies on Data stream mining involve topics that are commonly interrelated, such as Data stream.

He most often published in these fields:

  • Artificial intelligence (46.31%)
  • Data mining (29.79%)
  • Machine learning (25.37%)

What were the highlights of his more recent work (between 2018-2021)?

  • Artificial intelligence (46.31%)
  • Pattern recognition (11.21%)
  • Information retrieval (10.03%)

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

His primary areas of investigation include Artificial intelligence, Pattern recognition, Information retrieval, Natural language processing and Computer vision. As part of his studies on Artificial intelligence, Wei Fan frequently links adjacent subjects like Machine learning. His study explores the link between Machine learning and topics such as Reduction that cross with problems in Class.

His research in Pattern recognition intersects with topics in Convolution and Code. His studies examine the connections between Information retrieval and genetics, as well as such issues in Key, with regards to Annotation. His Natural language processing research integrates issues from Classifier and Graph.

Between 2018 and 2021, his most popular works were:

  • AnatomyNet: Deep learning for fast and fully automated whole‐volume segmentation of head and neck anatomy (141 citations)
  • Joint Slot Filling and Intent Detection via Capsule Neural Networks (70 citations)
  • Multi-grained Named Entity Recognition. (20 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Wei Fan mostly deals with Artificial intelligence, Information retrieval, Artificial neural network, Question answering and Pattern recognition. His work deals with themes such as Computer vision and Natural language processing, which intersect with Artificial intelligence. The concepts of his Information retrieval study are interwoven with issues in Ranking, Key and Knowledge base.

The various areas that he examines in his Artificial neural network study include Psoriasis, Utterance, Data mining and Medical record. His Question answering research includes themes of Transfer of learning, Closed captioning, Knowledge extraction and Federated learning. His Deep learning study improves the overall literature in Machine learning.

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.

Top Publications

Mining concept-drifting data streams using ensemble classifiers

Haixun Wang;Wei Fan;Philip S. Yu;Jiawei Han.
knowledge discovery and data mining (2003)

1658 Citations

Distributed data mining in credit card fraud detection

P.K. Chan;W. Fan;A.L. Prodromidis;S.J. Stolfo.
IEEE Intelligent Systems & Their Applications (1999)

1218 Citations

Mining big data: current status, and forecast to the future

Wei Fan;Albert Bifet.
Sigkdd Explorations (2013)

942 Citations

AdaCost: Misclassification Cost-Sensitive Boosting

Wei Fan;Salvatore J. Stolfo;Junxin Zhang;Philip K. Chan.
international conference on machine learning (1999)

770 Citations

Method and system for using intelligent agents for financial transactions, services, accounting, and advice

Daniel Schutzer;William Hull Forster;Huanrui Hu;Wenke Lee.
(1998)

685 Citations

Cost-based modeling for fraud and intrusion detection: results from the JAM project

S.J. Stolfo;Wei Fan;Wenke Lee;A. Prodromidis.
darpa information survivability conference and exposition (2000)

607 Citations

ViST: a dynamic index method for querying XML data by tree structures

Haixun Wang;Sanghyun Park;Wei Fan;Philip S. Yu.
international conference on management of data (2003)

460 Citations

Toward cost-sensitive modeling for intrusion detection and response

Wenke Lee;Wei Fan;Matthew Miller;Salvatore J. Stolfo.
Journal of Computer Security (2002)

450 Citations

Real time data mining-based intrusion detection

Wenke Lee;S.J. Stolfo;P.K. Chan;E. Eskin.
darpa information survivability conference and exposition (2001)

400 Citations

Knowledge transfer via multiple model local structure mapping

Jing Gao;Wei Fan;Jing Jiang;Jiawei Han.
knowledge discovery and data mining (2008)

370 Citations

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

If you think any of the details on this page are incorrect, let us know.

Contact us

Top Scientists Citing Wei Fan

Philip S. Yu

Philip S. Yu

University of Illinois at Chicago

Publications: 113

Jiawei Han

Jiawei Han

University of Illinois at Urbana-Champaign

Publications: 63

Jing Gao

Jing Gao

Purdue University West Lafayette

Publications: 56

Charu C. Aggarwal

Charu C. Aggarwal

IBM (United States)

Publications: 46

Xingquan Zhu

Xingquan Zhu

Florida Atlantic University

Publications: 41

Lu Su

Lu Su

Purdue University West Lafayette

Publications: 38

João Gama

João Gama

University of Porto

Publications: 36

Latifur Khan

Latifur Khan

The University of Texas at Dallas

Publications: 36

Qiang Yang

Qiang Yang

Hong Kong University of Science and Technology

Publications: 34

Xindong Wu

Xindong Wu

Hefei University of Technology

Publications: 31

Haixun Wang

Haixun Wang

Instacart

Publications: 31

Scott Faber

Scott Faber

DuPont (United States)

Publications: 30

Kun-Lung Wu

Kun-Lung Wu

IBM (United States)

Publications: 30

Bugra Gedik

Bugra Gedik

Facebook (United States)

Publications: 29

Salvatore J. Stolfo

Salvatore J. Stolfo

Columbia University

Publications: 29

Something went wrong. Please try again later.