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Email

aravinda.rao@unimelb.edu.au

Credentials


Position
University Guest (Academic)
Department of Electrical and Electronic Engineering
Education
PhD
University of Melbourne
Masters (Coursework)
Deakin University
Bachelors Degree
Visvesvaraya Technological University
ORCID

0000-0003-2319-6539

Dr Aravinda S. Rao

University Guest (Academic)
Department of Electrical and Electronic Engineering

61 Scholarly works
2 Projects

HIGHLIGHTS

  • 2026

    Journal article

    CONSENSUS: Consensus-based Systematic Evidence Synthesis for Forensic Risk Profiling of Cryptocurrency Mixers
    DOI: 10.1145/3800585
  • 2026

    Journal article

    QERA: A QUANTUM ECONOMIC RISK ASSESSMENT FRAMEWORK FOR BLOCKCHAIN CRYPTOGRAPHIC INFRASTRUCTURE
    DOI: 10.1142/S0218348X26400645
  • 2026

    Book Chapter

    Anomaly Detection in Cross-Chain Bridges: A Data Analytics Study
    DOI: 10.1007/978-981-95-9230-2_3
  • 2026

    Conference Proceedings

    Towards Optimised Detection of Smart Contract Vulnerabilities using Large Language Models
    DOI: 10.1109/ICBC67748.2026.11575545
  • 2026

    Book Chapter

    Towards Interoperable Digital Product Passports: A Dual-Ledger Blockchain Approach
    DOI: 10.1007/978-981-95-9230-2_15
  • 2026

    Journal article

    Minimum Foot Clearance Prediction in Stroke Survivors: A Transformer-Based Approach
    DOI: 10.1109/TNSRE.2026.3694895
  • 2021

    Research Contracts

    Field Data Collation to Support Real-Time Operational Management – Scoping Study
Aravinda S. Rao

Latest Honours,
Awards and Fellowships


2010
Network Ten Allan Williamson Information and Communication Technology (ICT) Skills Award Network Ten

RECENT SCHOLARLY WORKS

  • 2026

    Conference Proceedings

    TOPOS: Topological Profiling of On chain Subgraphs for Cross Chain Forensics
    DOI: 10.1109/ICBC67748.2026.11575551
  • 2025

    Journal article

    Detecting Atrial Fibrillation by Artificial Intelligence-Enabled Neuroimaging Examination
    DOI: 10.1159/000543042
  • 2025

    Conference Proceedings

    Zero-shot Stroke Lesion Segmentation via CAM-guided Prompting of MedSAM2
    DOI: 10.1145/3746252.3760872
  • 2025

    Journal article

    Early adherence to biofeedback training predicts long-term improvement in stroke patients: A machine learning approach
    DOI: 10.1371/journal.pone.0336503

RECENT PROJECTS

  • 2021

    Research Contracts

    Automated Tracking of Construction Materials for Improved Supply Chain Logistics and Provenance - Phase 1 Scoping Study

Acknowledgement of Country

We acknowledge Aboriginal and Torres Strait Islander people as the Traditional Owners of the unceded lands on which we work, learn and live. We pay respect to Elders past, present and future, and acknowledge the importance of Indigenous knowledge in the Academy.

Read about our Indigenous priorities

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