H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science D-index 111 Citations 61,577 511 World Ranking 83 National Ranking 52

Research.com Recognitions

Awards & Achievements

2021 - W. Wallace McDowell Award, IEEE Computer Society For contributions to knowledge discovery and data mining.

2015 - SIAM Fellow For contributions to knowledge discovery and data mining algorithms.

2013 - ACM Fellow For contributions to knowledge discovery and data mining algorithms.

Overview

What is she best known for?

The fields of study she is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

Charu C. Aggarwal mostly deals with Data mining, Cluster analysis, Artificial intelligence, Data science and Data stream mining. Her studies in Data mining integrate themes in fields like Data stream, Outlier and Data set. Her Cluster analysis research integrates issues from Spatial analysis and Search engine indexing.

In her study, Classifier is strongly linked to Machine learning, which falls under the umbrella field of Artificial intelligence. Her Data science study incorporates themes from Variety, Field and World Wide Web, Social network. Her Clustering high-dimensional data research includes themes of Nearest neighbor search and Curse of dimensionality.

Her most cited work include:

  • A framework for clustering evolving data streams (1459 citations)
  • On the Surprising Behavior of Distance Metrics in High Dimensional Spaces (1174 citations)
  • On the design and quantification of privacy preserving data mining algorithms (905 citations)

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

Charu C. Aggarwal spends much of her time researching Data mining, Artificial intelligence, Cluster analysis, Data stream mining and Machine learning. Her study explores the link between Data mining and topics such as Clustering high-dimensional data that cross with problems in Curse of dimensionality. Her study in the field of Class, Subspace topology and Training set is also linked to topics like Process.

Cluster analysis is a component of her Fuzzy clustering, Correlation clustering, Data stream clustering, CURE data clustering algorithm and Canopy clustering algorithm studies. Charu C. Aggarwal frequently studies issues relating to Data science and Data stream mining. Her work carried out in the field of Data science brings together such families of science as Variety, Social media and Social network.

She most often published in these fields:

  • Data mining (45.26%)
  • Artificial intelligence (25.52%)
  • Cluster analysis (15.89%)

What were the highlights of her more recent work (between 2016-2021)?

  • Artificial intelligence (25.52%)
  • Data mining (45.26%)
  • Machine learning (13.64%)

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

Charu C. Aggarwal focuses on Artificial intelligence, Data mining, Machine learning, Theoretical computer science and Graph. Her Artificial intelligence research focuses on Pattern recognition and how it connects with Data set. Charu C. Aggarwal interconnects Feature extraction and Social network in the investigation of issues within Data mining.

Her research in Machine learning intersects with topics in Matrix decomposition and Optimization problem. Her Theoretical computer science research includes elements of Graph classification and Link. Her work investigates the relationship between Graph and topics such as Graph that intersect with problems in Embedding.

Between 2016 and 2021, her most popular works were:

  • Outlier Detection with Autoencoder Ensembles. (141 citations)
  • Signed network embedding in social media (130 citations)
  • Neural Networks and Deep Learning (120 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Her scientific interests lie mostly in Artificial intelligence, Theoretical computer science, Data mining, Machine learning and Artificial neural network. In her work, Data set is strongly intertwined with Pattern recognition, which is a subfield of Artificial intelligence. Her work deals with themes such as Embedding, Network model, Manifold, Graph and Social media, which intersect with Theoretical computer science.

Her Data mining research incorporates themes from Evolving networks and Urban economics. Her Machine learning research is multidisciplinary, relying on both Class, Semantics, Algorithm design and Image. Her Anomaly detection research incorporates elements of Radial basis function kernel, Autoencoder, Outlier, Cluster analysis and Ensemble 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.

Best Publications

A framework for clustering evolving data streams

Charu C. Aggarwal;Jiawei Han;Jianyong Wang;Philip S. Yu.
very large data bases (2003)

2309 Citations

Data Classification: Algorithms and Applications

Charu C. Aggarwal.
(2014)

1729 Citations

On the Surprising Behavior of Distance Metrics in High Dimensional Spaces

Charu C. Aggarwal;Alexander Hinneburg;Daniel A. Keim.
international conference on database theory (2001)

1686 Citations

Outlier Analysis

Charu C. Aggarwal.
(2013)

1500 Citations

Outlier detection for high dimensional data

Charu C. Aggarwal;Philip S. Yu.
international conference on management of data (2001)

1455 Citations

Fast algorithms for projected clustering

Charu C. Aggarwal;Joel L. Wolf;Philip S. Yu;Cecilia Procopiuc.
international conference on management of data (1999)

1406 Citations

On the surprising behavior of distance metrics in high dimensional space

Charu C. Aggarwal;Alexander Hinneburg;Daniel A. Keim.
Lecture Notes in Computer Science (2001)

1403 Citations

Mining Text Data

Charu C. Aggarwal;Cheng Xiang Zhai.
(2012)

1400 Citations

On the design and quantification of privacy preserving data mining algorithms

Dakshi Agrawal;Charu C. Aggarwal.
symposium on principles of database systems (2001)

1349 Citations

A General Survey of Privacy-Preserving Data Mining Models and Algorithms

Charu C. Aggarwal;Philip S. Yu.
Privacy-Preserving Data Mining (2008)

1163 Citations

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