Pubudu Pathirana

Professor

Deakin University

Australia

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Professor Pubudu Pathirana is a faculty member at Deakin University, Australia. His research focuses on machine learning, cyber-physical systems, and privacy preservation in IoT. Recent publications include studies on federated learning, traffic state estimation, and deep reinforcement learning applications in blockchain technology.

Articles (17)

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2025

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2025

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2025

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2024

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2023

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2023

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2022

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2022

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2022

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2022

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2021

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2021

Collaborators (5)

Dinh Nguyen

Assistant Professor

University of Alabama in Huntsville

UNITED STATES

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Cyrus Shahabi

University of Southern California

UNITED STATES

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Ian H. Harding

AUSTRALIA

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Aruna Seneviratne

Professor

University of New South Wales

AUSTRALIA

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Seyyedali Hosseinalipour

Assistant Professor

University at Buffalo

UNITED STATES

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Pubudu Pathirana

Research Interests

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About

Articles (17)

Privacy and Fairness in Machine Learning: A Survey

Federated Learning for Cyber Physical Systems: A Comprehensive Survey

Traffic State Estimation With Spatio-Temporal Autoencoding Transformer (STAT Model)

Toward Privacy-Preserving Waste Classification in the Internet of Things

FedXPro: Bayesian Inference for Mitigating Poisoning Attacks in IoT Federated Learning

Unification of probabilistic graph model and deep reinforcement learning (UPGMDRL) for multi-intersection traffic signal control

Cooperative Task Offloading and Block Mining in Blockchain-Based Edge Computing With Multi-Agent Deep Reinforcement Learning

Technological Evolution in the Instrumentation of Ataxia Severity Measurement

Machine Learning-Based Scoring System to Predict the Risk and Severity of Ataxic Speech Using Different Speech Tasks

Latency Optimization for Blockchain-Empowered Federated Learning in Multi-Server Edge Computing

Federated Learning for COVID-19 Detection With Generative Adversarial Networks in Edge Cloud Computing

6G Internet of Things: A Comprehensive Survey

A survey on blockchain for big data: Approaches, opportunities, and future directions

Blockchain for Edge of Things: Applications, Opportunities, and Challenges

Federated Deep Learning for the Diagnosis of Cerebellar Ataxia: Privacy Preservation and Auto-Crafted Feature Extractor

Secure Computation Offloading in Blockchain Based IoT Networks With Deep Reinforcement Learning

Swarm intelligence for next-generation networks: Recent advances and applications

Collaborators (5)

Dinh Nguyen

Cyrus Shahabi

Ian H. Harding

Aruna Seneviratne

Seyyedali Hosseinalipour

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