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 56 Citations 25,871 334 World Ranking 1992 National Ranking 52

Research.com Recognitions

Awards & Achievements

2012 - IEEE Fellow For contributions to computational intelligence, learning systems, and nonlinear modelling

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Statistics
  • Machine learning

His main research concerns Artificial intelligence, Artificial neural network, Wireless sensor network, Anomaly detection and Heart rate variability. Marimuthu Palaniswami has researched Artificial intelligence in several fields, including Computational complexity theory, Machine learning and Pattern recognition. His Artificial neural network study combines topics from a wide range of disciplines, such as Robustness, Control theory, Robust control and Adaptive control.

The various areas that Marimuthu Palaniswami examines in his Wireless sensor network study include Sensor node, Adaptation, Key and Base station. The concepts of his Key study are interwoven with issues in Smart environment, Reduction, Energy, Statistical parameter and Web of Things. His studies in Heart rate variability integrate themes in fields like Electrocardiography and Cardiology.

His most cited work include:

  • Internet of Things (IoT): A vision, architectural elements, and future directions (6583 citations)
  • An Information Framework for Creating a Smart City Through Internet of Things (777 citations)
  • Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability (703 citations)

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

His primary areas of study are Artificial intelligence, Pattern recognition, Wireless sensor network, Support vector machine and Internal medicine. His Artificial intelligence research incorporates elements of Machine learning, Computer vision and Signal processing. His work in Pattern recognition addresses subjects such as Speech recognition, which are connected to disciplines such as Independent component analysis.

His Wireless sensor network research is included under the broader classification of Computer network. His biological study spans a wide range of topics, including Fetus and Cardiology. His work carried out in the field of Heart rate variability brings together such families of science as Entropy and Statistics.

He most often published in these fields:

  • Artificial intelligence (29.90%)
  • Pattern recognition (16.94%)
  • Wireless sensor network (12.29%)

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

  • Artificial intelligence (29.90%)
  • Pattern recognition (16.94%)
  • Cluster analysis (7.81%)

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

The scientist’s investigation covers issues in Artificial intelligence, Pattern recognition, Cluster analysis, Entropy and Signal processing. His research integrates issues of Machine learning, Photoplethysmogram, Computer vision and Heart rate in his study of Artificial intelligence. His Cluster analysis research includes themes of Visualization, Anomaly detection, Data mining and Random projection.

His research investigates the link between Anomaly detection and topics such as Real-time computing that cross with problems in Wireless sensor network. His Wireless sensor network study is focused on Computer network in general. His research in Entropy intersects with topics in Heart rate variability and Nonlinear system.

Between 2016 and 2021, his most popular works were:

  • PPFA: Privacy Preserving Fog-Enabled Aggregation in Smart Grid (83 citations)
  • Ensemble Empirical Mode Decomposition With Principal Component Analysis: A Novel Approach for Extracting Respiratory Rate and Heart Rate From Photoplethysmographic Signal (47 citations)
  • Detection of epileptic seizure based on entropy analysis of short-term EEG. (34 citations)

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

  • Artificial intelligence
  • Statistics
  • Machine learning

Marimuthu Palaniswami mostly deals with Artificial intelligence, Cluster analysis, Pattern recognition, Data mining and Random projection. In his study, Hardware architecture, Variety and Load forecasting is inextricably linked to Machine learning, which falls within the broad field of Artificial intelligence. His Cluster analysis research is multidisciplinary, relying on both Anomaly detection, Computation, Partition, Minimum spanning tree and Big data.

In his research on the topic of Anomaly detection, Wireless sensor network is strongly related with Real-time computing. His Pattern recognition study combines topics in areas such as Hilbert–Huang transform, Photoplethysmogram, Noise and Respiratory rate. His study in Data mining is interdisciplinary in nature, drawing from both Smart meter, Scalability, Tree and Trajectory.

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

Internet of Things (IoT): A vision, architectural elements, and future directions

Jayavardhana Gubbi;Rajkumar Buyya;Slaven Marusic;Marimuthu Palaniswami.
Future Generation Computer Systems (2013)

9857 Citations

An Information Framework for Creating a Smart City Through Internet of Things

Jiong Jin;Jayavardhana Gubbi;Slaven Marusic;Marimuthu Palaniswami.
IEEE Internet of Things Journal (2014)

1224 Citations

Do existing measures of Poincare plot geometry reflect nonlinear features of heart rate variability

M. Brennan;M. Palaniswami;P. Kamen.
IEEE Transactions on Biomedical Engineering (2001)

1100 Citations

Support vector machines for automated gait classification

R.K. Begg;M. Palaniswami;B. Owen.
IEEE Transactions on Biomedical Engineering (2005)

414 Citations

Fuzzy c-Means Algorithms for Very Large Data

T. C. Havens;J. C. Bezdek;C. Leckie;L. O. Hall.
IEEE Transactions on Fuzzy Systems (2012)

410 Citations

Energy-efficient link-layer jamming attacks against wireless sensor network MAC protocols

Yee Wei Law;Marimuthu Palaniswami;Lodewijk Van Hoesel;Jeroen Doumen.
ACM Transactions on Sensor Networks (2009)

379 Citations

Support Vector Machines for Automated Recognition of Obstructive Sleep Apnea Syndrome From ECG Recordings

A.H. Khandoker;M. Palaniswami;C.K. Karmakar.
international conference of the ieee engineering in medicine and biology society (2009)

350 Citations

Distributed Anomaly Detection in Wireless Sensor Networks

Sutharshan Rajasegarar;Christopher Leckie;Marimuthu Palaniswami;James Bezdek.
international conference on conceptual structures (2006)

319 Citations

Intrusion Detection for Routing Attacks in Sensor Networks

Chong Eik Loo;Mun Yong Ng;Christopher Leckie;Marimuthu Palaniswami.
International Journal of Distributed Sensor Networks (2006)

316 Citations

Anomaly detection in wireless sensor networks

S. Rajasegarar;C. Leckie;M. Palaniswami.
IEEE Wireless Communications (2008)

308 Citations

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