2026 Sutharshan Rajasegarar: Computer Science Researcher – H-Index, Publications & Awards

Discipline name	D-Index	World Ranking	Current World Ranking	National Ranking	Current National Ranking	Publications	Citations
Computer Science	36	11081	10768	335	334	146	7326

Sutharshan Rajasegarar publication distribution in Computer Science in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Computer Science in 2026. The highlighted bar marks where Sutharshan Rajasegarar sits on this spectrum.

32 publications 991+

This scientist: 146 publications — 25th percentile

25% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 991 publications or more.

Sutharshan Rajasegarar D-index placement in Computer Science in 2026

The chart shows the D-index (discipline H-index) distribution of Computer Science scientists ranked by Research.com in 2026. The highlighted bar marks where Sutharshan Rajasegarar sits on this spectrum.

30 D-Index 131+

This scientist: 36 D-Index — 23rd percentile

23% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 131 D-Index or more.

Overview

Sutharshan Rajasegarar is affiliated with Deakin University in Australia and has contributed extensively to research spanning multiple areas within computer science and engineering. Their work prominently intersects artificial intelligence, plant science, computer vision and pattern recognition, computer networks and communications, and electrical and electronic engineering.

The primary research topics covered in their publications include:

Anomaly Detection Techniques and Applications
Network Security and Intrusion Detection
Smart Agriculture and AI
Advanced Malware Detection Techniques
Plant Disease Management Techniques
Emotion and Mood Recognition
Face and Expression Recognition

Key recent papers authored or coauthored by Rajasegarar include:

"Deep Metric Learning Based Citrus Disease Classification With Sparse Data," 2020, IEEE Access
"LGAttNet: Automatic micro-expression detection using dual-stream local and global attentions," 2020, Knowledge-Based Systems
"Quantum deep learning-based anomaly detection for enhanced network security," 2024, Quantum Machine Intelligence
"Multi-attention graph neural networks for city-wide bus travel time estimation using limited data," 2022, Expert Systems with Applications
"Deep Continual Learning for Emerging Emotion Recognition," 2021, IEEE Transactions on Multimedia

Frequent collaborators in Rajasegarar's work include John Yearwood, Selvarajah Thuseethan, Lei Pan, Maia Angelova, and Sivasubramaniam Janarthan.

Rajasegarar's publications have appeared in several venues, notably:

IEEE Access
arXiv (Cornell University)
Expert Systems with Applications
PLoS ONE
IEEE Transactions on AgriFood Electronics

Their research output indicates contributions to areas where advanced machine learning techniques are applied to practical domains such as disease classification in plants, micro-expression detection, network security enhancement, travel time estimation using graph neural networks, and emotion recognition through continual learning frameworks.

Best Publications

High-dimensional and large-scale anomaly detection using a linear one-class SVM with deep learning

Sarah M. Erfani;Sutharshan Rajasegarar;Shanika Karunasekera;Christopher Leckie

1266
Citations
Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey

Ahmed Zoha;Alexander Gluhak;Muhammad Ali Imran;Sutharshan Rajasegarar

1171
Citations
Anomaly detection in wireless sensor networks

S. Rajasegarar;C. Leckie;M. Palaniswami

387
Citations
Distributed Anomaly Detection in Wireless Sensor Networks

S. Rajasegarar;C. Leckie;M. Palaniswami;J.C. Bezdek

354
Citations
Parking availability prediction for sensor-enabled car parks in smart cities

Yanxu Zheng;Sutharshan Rajasegarar;Christopher Leckie

293
Citations
Quarter Sphere Based Distributed Anomaly Detection in Wireless Sensor Networks

S. Rajasegarar;C. Leckie;M. Palaniswami;J.C. Bezdek

246
Citations
Centered Hyperspherical and Hyperellipsoidal One-Class Support Vector Machines for Anomaly Detection in Sensor Networks

S Rajasegarar;C Leckie;J C Bezdek;M Palaniswami

190
Citations
Labelled data collection for anomaly detection in wireless sensor networks

Shan Suthaharan;Mohammed Alzahrani;Sutharshan Rajasegarar;Christopher Leckie

164
Citations
Anomaly detection in wireless sensor networks in a non-stationary environment

Colin O'Reilly;Alexander Gluhak;Muhammad Ali Imran;Sutharshan Rajasegarar

146
Citations
A Hybrid Approach to Clustering in Big Data

Dheeraj Kumar;James C. Bezdek;Marimuthu Palaniswami;Sutharshan Rajasegarar

126
Citations
Fog-Empowered Anomaly Detection in IoT Using Hyperellipsoidal Clustering

Lingjuan Lyu;Jiong Jin;Sutharshan Rajasegarar;Xuanli He

119
Citations
Hyperspherical cluster based distributed anomaly detection in wireless sensor networks

Sutharshan Rajasegarar;Christopher Leckie;Marimuthu Palaniswami

116
Citations
Clustering ellipses for anomaly detection

Masud Moshtaghi;Timothy C. Havens;James C. Bezdek;Laurence Park

106
Citations
Bus travel time prediction with real-time traffic information

Jiaman Ma;Jeffrey Chan;Goce Ristanoski;Sutharshan Rajasegarar

104
Citations
Elliptical anomalies in wireless sensor networks

Sutharshan Rajasegarar;James C. Bezdek;Christopher Leckie;Marimuthu Palaniswami

87
Citations
Deep metric learning based citrus disease classification with sparse data

Sivasubramaniam Janarthan;Selvarajah Thuseethan;Sutharshan Rajasegarar;Qiang Lyu

85
Citations
Improving load forecasting based on deep learning and K-shape clustering

Fateme Fahiman;Sarah M. Erfani;Sutharshan Rajasegarar;Marimuthu Palaniswami

81
Citations
Anomaly detection by clustering ellipsoids in wireless sensor networks

Masud Moshtaghi;Sutharshan Rajasegarar;Christopher Leckie;Shanika Karunasekera

67
Citations
Efficient Unsupervised Parameter Estimation for One-Class Support Vector Machines

Zahra Ghafoori;Sarah M. Erfani;Sutharshan Rajasegarar;James C. Bezdek

66
Citations
A Rapid Hybrid Clustering Algorithm for Large Volumes of High Dimensional Data

Punit Rathore;Dheeraj Kumar;James C. Bezdek;Sutharshan Rajasegarar

65
Citations
Real-Time Urban Microclimate Analysis Using Internet of Things

Punit Rathore;Aravinda S. Rao;Sutharshan Rajasegarar;Elena Vanz

61
Citations
A Scalable Framework for Trajectory Prediction

Punit Rathore;Dheeraj Kumar;Sutharshan Rajasegarar;Marimuthu Palaniswami

56
Citations

Frequent Co-Authors

Christopher Leckie University of Melbourne

Marimuthu Palaniswami University of Melbourne

James C. Bezdek University of Melbourne

Shanika Karunasekera University of Melbourne

John Yearwood Deakin University

Jemal H. Abawajy Deakin University

James Bailey University of Melbourne

Kotagiri Ramamohanarao University of Melbourne

James M. Keller University of Missouri

Xi Zheng Macquarie University

External Links

Personal website of Sutharshan Rajasegarar

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