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Email

tom.drummond@unimelb.edu.au

Credentials


Position
Professor at Melbourne Connect
Faculty of Engineering and Information Technology – Admin
Education
PhD
Curtin University
Bachelors Degree (Honours)
University of Cambridge
Masters
University of Cambridge
ORCID

0000-0001-8204-5904

Prof Tom Drummond

Professor at Melbourne Connect
Faculty of Engineering and Information Technology

191 Scholarly works
1 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Raising the bar: Deep learning on comprehensive database sets new benchmark for automated fission-track detection
    DOI: 10.1016/j.cageo.2025.106096
  • 2026

    Journal article

    Admitting Ignorance Helps the Video Question Answering Models to Answer
    DOI: 10.1109/TMM.2026.3651115
  • 2025

    Journal article

    Few-Shot Multilingual Open-Domain QA from Five Examples
    DOI: 10.1162/tacl_a_00750
  • 2025

    Journal article

    Improved level set method for particle reconstruction from X-ray computed tomography images
    DOI: 10.1016/j.powtec.2025.120743
  • 2025

    Journal article

    TCAM-Diff: Triplane-Aware Cross-Attention Medical Diffusion Model
    DOI: 10.1609/aaai.v39i21.34433
  • 2025

    Journal article

    Robots Have Been Seen and Not Heard: Effects of Consequential Sounds on Human-Perception of Robots
    DOI: 10.1109/LRA.2025.3546097
  • 2023

    Research grants (ARC, NHMRC, MRFF)

    Small Scalable Natural Language Models Using Explicit Memory
Tom Drummond

RECENT SCHOLARLY WORKS

  • 2025

    Conference Proceedings

    Sound Judgment: Properties of Consequential Sounds Affecting Human-Perception of Robots
    DOI: 10.1109/HRI61500.2025.10974245
  • 2025

    Conference Proceedings

    Deep Learning based Computer-vision for Enhanced Beamforming
    DOI: 10.1109/ICCWorkshops67674.2025.11162224
  • 2024

    Journal article

    MotionPerceiver: Real-Time Occupancy Forecasting for Embedded Systems
    DOI: 10.1109/LRA.2024.3360811
  • 2024

    Conference Proceedings

    Pre-training Cross-lingual Open Domain Question Answering with Large-scale Synthetic Supervision
    DOI: 10.18653/v1/2024.emnlp-main.770

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