Latest News

Jun 2024: Gave an invited talk at Künstliche Intelligenz in und für Wissenschaften Symposium

Jan 2024: 1 journal accepted to Information Sciences!

July 2023: 1 paper accepted to ICCV2023!
April 2023: 1 paper accepted to ICLR2023!

July 2022: I have been selected as one of the Outstanding Reviewers (Top 10%) at ICML2022!
Jun 2022: I have joined Meta as an AI research Scientist!
Jun 2022: 1 paper accepted to Interspeech2022!
May 2022: 3 papers accepted to CoLLAs2022!
May 2022: 1 paper accepted to ICML2022!
April 2022: I have been selected as Highlighted Reviewer at ICLR2022!
April 2022: Listen to my interview with the Austrian Ai Podcast! ( part 2)

Dec 2021: I have joined the Institute for Machine Learning!
Sep 2021: 1 paper accepted to NeurIPS 2021!
Sep 2021: 1 new talk on Contextual Reinforcement Learning is available online!
Sep 2021: 1 new talk on the Foundations of Data Augmentation is available online!
July 2021: 1 journal paper published!
May 2021: My research proposal has been accepted to Graphcore Academic Programme!
March 2021: I have been selected to join the inaugural cohort of Google Cloud Research Innovators (see the news item)!
March 2021: I received a grant from Google Cloud Credit Research Program for my research project CaRL.

Dec 2020: New blog post is out!
Nov 2020: Giving a public lecture at CP Lecture series, at the Johannes Kepler University.
Nov 2020: Received a grant from Google Cloud Credit Research Program for my research project DEVs.
Sep 2020: Giving an invited talk at the Cyber-Physical Systems Group, TU Wien.

Nov 2019: Giving an invited talk at the Intelligent Autonomous Systems Group of the Computer Science Department of the Technische Universitaet Darmstadt.
Oct 2019: Awarded the travel grant for the DL/RL summer school in Edmonton, Alberta, Canada by Amii (Alberta Machine Intelligence Institute).
Jun 2019: Successfully defended (Passed with Distinction) my PhD dissertation entitled "Representation Learning and Inference from Signals and Sequences".
July 2019: Attending the CIFAR's DL/RL Summer School in Edmonton, Alberta, Canada.
Jun 2019: 1 paper accepted to CVPR 2019!


Introduction

I am an AI research scientist at Meta. I was previousely a Postdoc at the Institute for Machine Learning, at the Johannes Kepler University of Linz. In my research, I am interested in generalisation and robustness in deep learning and reinforcement learning.



Selected publications

Here is a list of my selected publications.

  • Hamid Eghbal-zadeh, Werner Zellinger, Maura Pintor, Kathrin Grosse, Khaled Koutini, Bernhard A. Moser, Battista Biggio, Gerhard Widmer Rethinking Data Augmentation for Adversarial Robustness, In Proceedings of Information Sciences 654 (2024): 119838., 2024.
  • Talks



    2021


    Title of the talk: How Much Is An Augmented Sample Worth?
    Description: Teaser at the Pre-register workshop at NeurIPS2021.

    Title of the talk: Learning Context Variables in Contextual Reinforcement Learning
    Description: Talk at the 5th IPM Advanced School On Computing & Artificial Intelligence (2021).



    Title of the talk: Foundations of Data Augmentation
    Description: Talk at the Amirkabir Artificial Intelligence Summer Summit (AAISS) 2021.



    2020


    Title of the talk: Context-Adaptive Reinforcement Learning using Unsupervised Learning of Context Variables
    Description: Teaser at the Pre-register workshop at NeurIPS2020.

    Title of the talk: CP lecture serries
    Description: Public lecture at the CP lecture serries.




    Title of the talk: On the Inductive Biases in Data Augmentation and Adversarial Robustness.
    Description: Talk at the Amirkabir Artificial Intelligence Summer Summit (AAISS) 2020.



    Title of the talk: Adversarial Robustness in Data Augmentation.
    Description: Talk at the Towards Trustworthy ML: Rethinking Security and Privacy for ML, ICLR 2020 Workshop.



    2019


    Title of the talk: Representation Learning under Incomplete and Imprecise Information Conditions.
    Description: Talk at the Intelligent Autonomous Systems Group of the Computer Science Department of the Technische Universitaet Darmstadt.



    2018


    Title of the talk: Deep Within-Class Covariance Analysis for Robust Deep Audio Representation Learning.
    Description: Talk at the Interpretability and Robustness in Audio, Speech and Language, NeurIPS 2018 Workshop.

    Mentoring

    If you are from an under represented group, and need help with ML research or similar topics, you can book a mentoring session with me.