Sutharshan Rajasegarar

6.5k total citations · 2 hit papers
110 papers, 4.6k citations indexed

About

Sutharshan Rajasegarar is a scholar working on Artificial Intelligence, Computer Networks and Communications and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sutharshan Rajasegarar has authored 110 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Artificial Intelligence, 46 papers in Computer Networks and Communications and 27 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sutharshan Rajasegarar's work include Anomaly Detection Techniques and Applications (46 papers), Network Security and Intrusion Detection (30 papers) and Energy Efficient Wireless Sensor Networks (15 papers). Sutharshan Rajasegarar is often cited by papers focused on Anomaly Detection Techniques and Applications (46 papers), Network Security and Intrusion Detection (30 papers) and Energy Efficient Wireless Sensor Networks (15 papers). Sutharshan Rajasegarar collaborates with scholars based in Australia, United States and United Kingdom. Sutharshan Rajasegarar's co-authors include Christopher Leckie, Marimuthu Palaniswami, Shanika Karunasekera, Sarah Erfani, James C. Bezdek, Muhammad Ali Imran, Alexander Gluhak, Ahmed Zoha, Yanxu Zheng and John Yearwood and has published in prestigious journals such as PLoS ONE, IEEE Transactions on Geoscience and Remote Sensing and IEEE Communications Surveys & Tutorials.

In The Last Decade

Sutharshan Rajasegarar

107 papers receiving 4.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

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

2016 791 citations Sarah Erfani, Sutharshan Rajasegarar et al. Pattern Recognition profile →
Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey

2012 701 citations Alexander Gluhak, Muhammad Ali Imran et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Sutharshan Rajasegarar Australia	30	2.3k	1.8k	1.0k	665	625	110	4.6k
Milos Manic United States	33	1.4k 0.6×	938 0.5×	951 0.9×	1.1k 1.6×	366 0.6×	206	3.8k
Davide Anguita Italy	32	2.0k 0.9×	702 0.4×	794 0.8×	581 0.9×	223 0.4×	176	5.1k
Zhu Xiao China	39	1.2k 0.5×	1.8k 1.0×	1.4k 1.4×	319 0.5×	630 1.0×	302	5.4k
Qingqi Pei China	37	1.6k 0.7×	2.2k 1.3×	1.8k 1.7×	344 0.5×	356 0.6×	219	5.0k
Yanmin Zhu China	44	1.6k 0.7×	2.4k 1.3×	2.0k 2.0×	248 0.4×	759 1.2×	342	7.0k
Jianxin Li China	14	1.2k 0.5×	418 0.2×	847 0.8×	408 0.6×	507 0.8×	50	3.7k
Fu Xiao China	37	1.5k 0.6×	2.0k 1.2×	2.1k 2.0×	258 0.4×	237 0.4×	341	5.5k
Reza Malekian South Africa	39	519 0.2×	1.4k 0.8×	1.2k 1.1×	1.1k 1.7×	198 0.3×	198	5.3k
Tie Qiu China	51	2.0k 0.9×	5.0k 2.8×	3.0k 2.9×	812 1.2×	353 0.6×	261	9.1k
Kamin Whitehouse United States	34	586 0.3×	2.4k 1.4×	2.3k 2.3×	212 0.3×	800 1.3×	125	4.7k

Countries citing papers authored by Sutharshan Rajasegarar

Since Specialization

Citations

This map shows the geographic impact of Sutharshan Rajasegarar'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 Sutharshan Rajasegarar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sutharshan Rajasegarar more than expected).

Fields of papers citing papers by Sutharshan Rajasegarar

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sutharshan Rajasegarar. 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 Sutharshan Rajasegarar. The network helps show where Sutharshan Rajasegarar may publish in the future.

Co-authorship network of co-authors of Sutharshan Rajasegarar

This figure shows the co-authorship network connecting the top 25 collaborators of Sutharshan Rajasegarar. A scholar is included among the top collaborators of Sutharshan Rajasegarar based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Sutharshan Rajasegarar. Sutharshan Rajasegarar is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Shelyag, Sergiy, et al.. (2025). Time-Series Analysis of Ball Carrier Open-Space (BCOS) in Association Football. SN Computer Science. 6(4).

Thuseethan, Selvarajah, et al.. (2024). LiRAN: A Lightweight Residual Attention Network for In-Field Plant Pest Recognition. 3(1). 167–178. 2 indexed citations

Gholami, Khalil, et al.. (2024). Risk-constrained community battery utilisation optimisation for electric vehicle charging with photovoltaic resources. Journal of Energy Storage. 97. 112646–112646. 4 indexed citations

Shelyag, Sergiy, et al.. (2024). Predicting goal probabilities with improved xG models using event sequences in association football. PLoS ONE. 19(10). e0312278–e0312278. 3 indexed citations

Pokhrel, Shiva Raj, Lu‐Xing Yang, Sutharshan Rajasegarar, & Gang Li. (2024). Robust Zero Trust Architecture: Joint Blockchain based Federated learning and Anomaly Detection based Framework. 7–12. 8 indexed citations

Shelyag, Sergiy, et al.. (2024). Winning With Chaos in Association Football: Spatiotemporal Event Distribution Randomness Metric for Team Performance Evaluation. IEEE Access. 12. 83363–83376. 2 indexed citations

Rajasegarar, Sutharshan, et al.. (2024). LabelGen: An Anomaly Label Generative Framework for Enhanced Graph Anomaly Detection. IEEE Access. 12. 121971–121982. 1 indexed citations

Yang, Meng, et al.. (2023). Evolving graph-based video crowd anomaly detection. The Visual Computer. 40(1). 303–318. 10 indexed citations

Mak‐Hau, Vicky, et al.. (2022). DμDT: the Deakin University Microgrid Digital Twin. 1–6. 2 indexed citations

10.

Natgunanathan, Iynkaran, Adnan Anwar, Sutharshan Rajasegarar, & Vicky Mak‐Hau. (2022). Error Spectrum Analysis of Solar Power Prediction for Deakin Microgrid Digital Twin. 1–6. 2 indexed citations

11.

Rajasegarar, Sutharshan, et al.. (2022). Machine Learning Aided Minimal Sensor based Hand Gesture Character Recognition. 22. 1–9. 1 indexed citations

12.

Natgunanathan, Iynkaran, et al.. (2020). Robust Patient Information Embedding and Retrieval Mechanism for ECG Signals. IEEE Access. 8. 181233–181245. 10 indexed citations

13.

Shilton, Alistair, Sutharshan Rajasegarar, & Marimuthu Palaniswami. (2020). Multiclass Anomaly Detector: the CS++ Support Vector Machine. Journal of Machine Learning Research. 21(213). 1–39. 2 indexed citations

14.

Thuseethan, Selvarajah, Sutharshan Rajasegarar, & John Yearwood. (2019). Emotion Intensity Estimation from Video Frames using Deep Hybrid Convolutional Neural Networks. 1–10. 9 indexed citations

15.

Abawajy, Jemal, et al.. (2017). Meta Learning Ensemble Technique for Diagnosis of Cardiac Autonomic Neuropathy Based on Heart Rate Variability Features. Own your potential (DEAKIN). 169–175. 1 indexed citations

16.

Abawajy, Jemal, et al.. (2017). Breast cancer risk assessment prediction using an ensemble classifier. Own your potential (DEAKIN). 177–183. 5 indexed citations

17.

Rajasegarar, Sutharshan, Christopher Leckie, & Marimuthu Palaniswami. (2015). Pattern based anomalous user detection in cognitive radio networks. 5605–5609. 8 indexed citations

18.

Rajasegarar, Sutharshan, Alexander Gluhak, Muhammad Ali Imran, et al.. (2014). Ellipsoidal neighbourhood outlier factor for distributed anomaly detection in resource constrained networks. Pattern Recognition. 47(9). 2867–2879. 29 indexed citations

19.

Suthaharan, Shan, et al.. (2010). Labelled data collection for anomaly detection in wireless sensor networks. 269–274. 106 indexed citations

20.

Rajasegarar, Sutharshan, et al.. (2007). Analysis of Anomalies in IBRL Data from a Wireless Sensor Network Deployment. 158–163. 10 indexed citations

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.

Explore authors with similar magnitude of impact