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Email

howard.bondell@unimelb.edu.au

Credentials


Position
Head, School of Mathematics and Statistics
School of Mathematics and Statistics
Education
PhD
Rutgers, The State University of New Jersey
ORCID

0000-0001-7743-0840

Prof Howard Bondell

Head, School of Mathematics and Statistics
School of Mathematics and Statistics

105 Scholarly works
7 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Mathematical modeling and optimization of athletic performance: Tapering and periodization
    DOI: 10.1515/jqas-2025-0077
  • 2026

    Journal article

    Bayesian Inference of Contextual Bandit Policies via Empirical Likelihood
  • 2026

    Journal article

    Augmenting Neural Networks With Time-Varying Weights
    DOI: 10.1002/for.70014
  • 2025

    Journal article

    Efficient sparse high-dimensional linear regression with a partitioned empirical Bayes ECM algorithm
    DOI: 10.1016/j.csda.2025.108146
  • 2024

    Research grants (ARC, NHMRC, MRFF)

    Causal Knowledge-Empowered Adaptive Federated Learning
  • 2020

    Research grants (ARC, NHMRC, MRFF)

    Statistical Modelling in the Era of Data Science: Theory and Practice
  • 2018

    Research Grant

    Towards Designing Complex Networks Resilient to Stealthy Attack and Cascading Failure
Howard Bondell

Latest Honours,
Awards and Fellowships


2017
Fellow of the American Statistical Association

RECENT SCHOLARLY WORKS

  • 2025

    Journal article

    Domain generalization via content factors isolation: a two-level latent variable modeling approach
    DOI: 10.1007/s10994-024-06717-6
  • 2025

    Journal article

    ComFe: An Interpretable Head for Vision Transformers
  • 2025

    Conference Proceedings

    MissScore: High-Order Score Estimation in the Presence of Missing Data
  • 2025

    Journal article

    A Mixture of Exemplars Approach for Efficient Out-of-Distribution Detection with Foundation Models
  • 2025

    Journal article

    Preserving Angles Improves Feature Distillation
  • 2025

    Conference Proceedings

    Density Ratio Estimation via Sampling along Generalized Geodesics on Statistical Manifolds

RECENT PROJECTS

  • 2021

    Research grants (ARC, NHMRC, MRFF)

    Return of Strategic Funding (Monash) - ARC Training Centre in Optimisation Technologies, Integrated Methodologies, and Applications (OPTIMA)
  • 2022

    Research grants (international)

    Deep Learning Theory

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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