About me

I am a Postdoctoral Researcher at the Department of Electrical Engineering and Computer Science (EECS) at the University of California at Berkeley, working with Michael Jordan. My research is supported by the Swiss National Science Foundation.

Prior to my current position, I was Postdoctoral Research Scientist at the Machine Learning and Optimization (MLO) lab at EPFL, working with Martin Jaggi. While at EPFL, I organized the Smooth Games reading group . In part of my time, I participated in the intelligent Global Health (iGH) sub-group of MLO led by Mary-Anne Hartley, by advising on the machine learning aspect of the ongoing projects.

I obtained my Ph.D. from EPFL, and Idiap, supervised by François Fleuret. During my Ph.D. studies I did two internships at: (i) Mila where I was supervised by Yoshua Bengio and Simon Lacoste-Julien, as well as at (ii) DeepMind supervised by Irina Higgins.

Research interests

My main interests lie at the intersection of game theory and machine learning. I would like to understand the training dynamics of multi-player games and saddle point optimization. In addition, my interests include unsupervised learning, generative modeling, generalization, and robustness.

Selected Publications & Preprints

* Equal contributions.

Google Scholar

Past Talks

Former Supervision & Teaching Assistance

  • Gilberto Manunza (MSc thesis), On the Connection between Adversarial Training and Uncertainty Estimation
    seven months MSc project, 2021, EPFL.
  • Apostolov Alexander (CS-498 Semester Project), On the Effect of Variance Reduced Gradient and Momentum for Optimizing Deep Neural Networks
    autumn semester, 2020, EPFL.
  • Co-superivison with Sebastian U. Stich:
    • Oğuz Kaan Yüksel, Normalizing Flows for Generalization and Robustness
      (CS-498 Semester Project) autumn semester, 2020, EPFL.
    • Yehao Liu, On the Drawbacks of Popular Deep Learning Uncertainty Estimation Methods
      spring semester & summer internship, 2021, EPFL.
  • Co-superivison with Mary-Anne Hartley:
    • Deeksha M. Shama, Deep Learning Approaches for Covid-19 Diagnosis via Digital Lung Auscultation
      autumn semester, 2020.
    • Pablo Cañas, On Uncertainty Estimation of Global COVID Policy Simulator
      autumn semester, 2020.
  • Teaching Assistant, Deep Learning Course (EE-559)
    for MSc students, EPFL, 2018 & 2020.
  • Teaching Assistant, An Introduction to Deep Learning
    for MSc students, African Master's in Machine Intelligence, Kigali, Rwanda, 2018.





Reading Group




Feel free to reach out at: tatjana.chavdarova[at]berkeley[dot]edu