Muru Raj Odiathevar
PhD Student School of Engineering and Computer Science
Thesis Info
Research Interests: Probabilistic Machine Learning, Edge AI, Network Anomaly Detection
Thesis Title: Anomaly Detection in Dynamic and Distributed Scenarios
Supervisor: Prof Winston Seah, A/Prof Marcus Frean
Thesis Title: Anomaly Detection in Dynamic and Distributed Scenarios
Supervisor: Prof Winston Seah, A/Prof Marcus Frean
Research Interests
My current research is on anomaly detection in networked systems using various methods such as probabilistic machine learning, deep learning and statistical modelling. I am also researching on expanding existing methods for different scenarios such as in Edge AI. I also have a wider interest in AIOps, automation, engineering and technology. More details on LinkedIn: https://www.linkedin.com/in/muru-raj-76a231105/ Publications-
Murugaraj Odiathevar, Winston KG Seah, and Marcus Frean. "A hybrid online offline system for network anomaly detection." 2019 28th International Conference on Computer Communication and Networks (ICCCN). IEEE, 2019.
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Murugaraj Odiathevar, Winston KG Seah, Marcus Frean and Alvin Valera. "An Online Offline Framework for Anomaly Scoring and Detecting New Traffic in Network Streams." IEEE Transactions on Knowledge & Data Engineering 01 (2021): 1-1.
- Murugaraj Odiathevar, Duncan Cameron, Winston KG Seah, Marcus Frean and Alvin Valera. "Humans learning from Machines: Data Science meets Network Management." 2021 International Conference on COMmunication Systems & NETworkS (COMSNETS). IEEE, 2021.
- Hybrid Machine Learning System and Method : AU 2019900788