Kanishka Bhaduri

1.0k citations

29 papers · 594 indexed · h-index 15

Artificial Intelligence top 5%
- Data Stream Mining Techniques 10
- Anomaly Detection Techniques and Applications 9
- Privacy-Preserving Technologies in Data 4
Signal Processing top 5%
- Data Management and Algorithms 6
- Time Series Analysis and Forecasting 5
Computer Networks and Communications top 5%
- Peer-to-Peer Network Technologies 4
- Network Security and Intrusion Detection 3
Information Systems top 5%
- Data Mining Algorithms and Applications 5
Statistics, Probability and Uncertainty top 10%

Co-authors: Chris Giannella Ran Wolff Hillol Kargupta H. Kargupta Kamalika Das Bryan Matthews Souptik Datta Ashok N. Srivastava
Cited by: Artificial Intelligence Signal Processing Computer Networks and Communications
Journals: Statistical Analysis and Data Mining The ASA Data Science Journal (5 papers)IEEE Transactions on Knowledge and Data Engineering (2 papers)IEEE Internet Computing (1 paper)
Partner nations: United States Israel Belgium

In The Last Decade

Kanishka Bhaduri

29 papers receiving 546 citations

Peers

Countries citing papers authored by Kanishka Bhaduri

Since Specialization

Citations

This map shows the geographic impact of Kanishka Bhaduri's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kanishka Bhaduri with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanishka Bhaduri more than expected).

Fields of papers citing papers by Kanishka Bhaduri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kanishka Bhaduri. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kanishka Bhaduri. The network helps show where Kanishka Bhaduri may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Kanishka Bhaduri, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kanishka Bhaduri Line = papers co-authored together Kanishka Bhaduri links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

#	Work
1	Large scale support vector regression for aviation safety Kamalika Das,Kanishka Bhaduri,Bryan Matthews,Nikunj C. Oza	2015	2
2	Discovering Anomalous Aviation Safety Events Using Scalable Data Mining Algorithms Journal of Aerospace Information Systems ·Bryan Matthews,Santanu Das,Kanishka Bhaduri,Kamalika Das,Rodney Martin,Nikunj C. Oza	2013	47
3	Exploiting graph-theoretic tools for matching in carpooling applications Journal of Ambient Intelligence and Humanized Computing ·Luk Knapen,Ansar-Ul-Haque Yasar,Sung‐Jin Cho,Daniel Keren,Rajaee Abdolmehdi,Tom Bellemans,Davy Janssens,Geert Wets,Assaf Schuster,Izchak Sharfman,Kanishka Bhaduri	2013	21
4	Understanding large text corpora via sparse machine learning Statistical Analysis and Data Mining The ASA Data Science Journal ·Laurent El Ghaoui,Vu Pham,Guan‐Cheng Li,Deka Perdana Putra,Ashok N. Srivastava,Kanishka Bhaduri	2013	17
5	Algorithms for speeding up distance-based outlier detection Kanishka Bhaduri,Bryan Matthews,Chris Giannella	2011	61
6	Distributed anomaly detection using 1‐class SVM for vertically partitioned data Statistical Analysis and Data Mining The ASA Data Science Journal ·Kamalika Das,Kanishka Bhaduri,P. Votava	2011	13
7	Introduction to data mining for sustainability Data Mining and Knowledge Discovery ·Katharina Morik,Kanishka Bhaduri,Hillol Kargupta	2011	14
8	Scalable, asynchronous, distributed eigen monitoring of astronomy data streams Statistical Analysis and Data Mining The ASA Data Science Journal ·Kanishka Bhaduri,Kamalika Das,K. D. Borne,Chris Giannella,Nguyễn Phạm Duy Linh,Hillol Kargupta	2011	4
9	Distributed Anomaly Detection using Satellite Data From Multiple Modalitie. Kanishka Bhaduri,Kamalika Das,P. Votava	2010	8
10	Privacy-Preserving Outlier Detection Through Random Nonlinear Data Distortion IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics) ·Kanishka Bhaduri,Jay Kovach,Ashok N. Srivastava	2010	22
11	Multi-objective optimization based privacy preserving distributed data mining in Peer-to-Peer networks Peer-to-Peer Networking and Applications ·Kamalika Das,Kanishka Bhaduri,Hillol Kargupta	2010	4
12	Fast and Flexible Multivariate Time Series Subsequence Search NASA STI Repository (National Aeronautics and Space Administration) ·Kanishka Bhaduri,Qiang Zhu,Nikunj C. Oza,Ashok N. Srivastava	2010	6
13	A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks NASA STI Repository (National Aeronautics and Space Administration) ·Kanishka Bhaduri,Ashok N. Srivastava	2009	9
14	ν-Anomica: A Fast Support Vector Based Novelty Detection Technique Santanu Das,Kanishka Bhaduri,Nikunj C. Oza,Ashok N. Srivastava	2009	4
15	Distributed Decision‐Tree Induction in Peer‐to‐Peer Systems Statistical Analysis and Data Mining The ASA Data Science Journal ·Kanishka Bhaduri,Ran Wolff,Chris Giannella,Hillol Kargupta	2008	31
16	A Generic Local Algorithm for Mining Data Streams in Large Distributed Systems IEEE Transactions on Knowledge and Data Engineering ·Ran Wolff,Kanishka Bhaduri,H. Kargupta	2008	37
17	An efficient local Algorithm for Distributed Multivariate Regression in Peer-to-Peer Networks Kanishka Bhaduri,Hillol Kargupta	2008	12
18	A Scalable Local Algorithm for Distributed Multivariate Regression Statistical Analysis and Data Mining The ASA Data Science Journal ·Kanishka Bhaduri,Hillol Kargupta	2008	9
19	Local L2-Thresholding Based Data Mining in Peer-to-Peer Systems Ran Wolff,Kanishka Bhaduri,Hillol Kargupta	2006	26
20	Distributed Data Mining in Peer-to-Peer Networks IEEE Internet Computing ·Souptik Datta,Kanishka Bhaduri,Chris Giannella,Ran Wolff,H. Kargupta	2006	130

About Kanishka Bhaduri

Kanishka Bhaduri is a scholar working on Signal Processing, Artificial Intelligence, Computer Networks and Communications, Computer Science Applications and Statistics, Probability and Uncertainty, having authored 29 papers that have together received 594 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (10 papers), Anomaly Detection Techniques and Applications (9 papers), Data Management and Algorithms (6 papers), Time Series Analysis and Forecasting (5 papers), Data Mining Algorithms and Applications (5 papers), Peer-to-Peer Network Technologies (4 papers), Privacy-Preserving Technologies in Data (4 papers) and Network Security and Intrusion Detection (3 papers). The work is most often cited by research in Artificial Intelligence (364 citations), Signal Processing (120 citations), Computer Networks and Communications (220 citations), Information Systems (129 citations) and Statistics, Probability and Uncertainty (35 citations). Kanishka Bhaduri has collaborated with scholars based in United States, Israel and Belgium. Frequent co-authors include Chris Giannella, Ran Wolff, Hillol Kargupta, H. Kargupta, Kamalika Das, Bryan Matthews, Souptik Datta, Ashok N. Srivastava, Nikunj C. Oza and Santanu Das. Their work appears in journals such as Statistical Analysis and Data Mining The ASA Data Science Journal, IEEE Transactions on Knowledge and Data Engineering, IEEE Internet Computing, Data Mining and Knowledge Discovery and Journal of Ambient Intelligence and Humanized Computing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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