I'm a Research Scientist at Google Research. Prior to this, I was a Machine Learning Scientist at Amazon from May 2021 to July 2024. I completed my PhD at the Australian National University where I was based at CSIRO Data61, advised by Richard Nock. Before this, I received a BSc (Adv) (Hons Class I and University Medal) from The University of Sydney. I am interested in both theoretical and practical aspects of machine learning with particular research interests in

News


Publications


  1. Distributionally Robust Bayesian Optimization with ϕ-divergences
    Hisham Husain, Vu Nguyen and Anton van den Hengel.
    NeurIPS2023

  2. Data Preprocessing to Mitigate Bias with Fair Boosted Mollifiers
    Alexander Soen, Hisham Husain and Richard Nock.
    ICML2023

  3. Semi-Supervised Semantic Segmentation under Label Noise via Diverse Learning Groups.
    Peixia Li, Pulak Purkait, Ajanthan Thalaiyasingam, Majid Abdolshah, Ravi Garg, Hisham Husain, Chenchen Xu, Stephen Gould, Wanli Ouyang and Anton van den Hengel
    ICCV2023 

  4. Adversarial Interpretation of Bayesian Inference.
    Hisham Husain and Jeremias Knoblauch
    ALT2022

  5. Regularized Policies are Reward Robust.
    Hisham Husain, Kamil Ciosek and Ryota Tomioka.
    AISTATS2021

  6. Distributional Robustness with IPMs and links to Regularization and GANs.
    Hisham Husain.
    NeurIPS2020

  7. Optimal Continual Learning has Perfect Memory and is NP-Hard.
    Jeremias Knoblauch, Hisham Husain and Tom Diethe.
    ICML2020

  8. Local Differential Privacy for Sampling.
    Hisham Husain, Borja Balle, Zac Cranko and Richard Nock.
    AISTATS2020

  9. A Primal-Dual Link between GANs and Autoencoders.
    Hisham Husain, Richard Nock and Robert C. Williamson.
    NeurIPS2019

Preprints



Contact


hisham dot husain at protonmail dot com