I’m a PhD Student in Machine Learning at EPFL in the MLO group, where I am supervised by Prof. Martin Jaggi. I am (like everyone?) intrigued by the power of large foundation models and their applications, in particular through open science and open-source. In my current research, I am therefore exploring:

  • Methods for scaling open language models & scaling behaviour
  • Training, optimization and efficient algorithms for large (and small!) models
  • Adaptive computing and new architectures for deep learning

and more :)

Prior to my PhD, I completed my Master and Bachelor in Computer Science at ETH Zürich working with the LAS group and Prof. Andreas Krause. I also was a visiting Student Researcher at the Apple MLR team in Paris, supervised by Prof. Marco Cuturi. See a list of my publications so far here.

During my studies, I had the chance to spend two semesters abroad: one at École Polytechnique in France, and one at the University of Toronto in Canada. Moreover, I was able to do an internship at Spacemaker AI, which is fun looking back at the interview I gave here.

Feel free to get in touch via mail:
alexander . hagele [AT] epfl.ch

News

  • October 2023: Starting my PhD at EPFL :)
  • April 2023: I’ve presented BaCaDI as an oral presentation at AISTATS 2023 (notable paper award, 32 / 1689 submissions) in Valencia (link to the conference). Slides are available here.
  • April 2023: I’m in Paris working with the Apple MLR team for the next months – please reach out if you’re around!
  • January 2023: For a course project on data visualization, I created a blog post on Visualizing folktables, a benchmark dataset for fairness in ML. The goal of the post is to provide an overview and exploration of the dataset, hopefully being of value for researchers working with folktables.
  • January 2023: Our paper on BaCaDI: Bayesian Causal Discovery with Unknown Interventions was accepted to AISTATS 2023!
  • September 2022: I’m in Paris at École Polytechnique (well, Palaiseau) for the next few months for a semester abroad before the end of my Master. Please send me a message if you’re around and want to chat! :)
  • July 2022: Presenting our work on Bayesian Causal Discovery to the Causality Discussion Group.
  • July 2022: BaCaDI was accepted to the CRL Workshop at UAI. See you August 5 in Eindhoven!
  • June 2022: Starting my internship at EPFL! Feel free to reach out if you’re around :)
  • June 2022: Our preprint for BaCaDI: Bayesian Causal Discovery with Unknown Interventions is out.