About me

Hi! My name is Tatjana (pronounced /tatiana/) and 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.

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.

I am very grateful to the Swiss National Science Foundation for supporting my research, through the Early.Postdoc.Mobility (in 2021) and the Postdoc.Mobility (in 2023) fellowships.

News:

mid-October, 2023: I'll join CISPA as a tenure-track Professor, and will give a course on Games in Machine Learning (winter semester) at Saarland University in Germany -- stay tuned for course materials! I have open positions for research assistants, PhD students, and Postdocs, use this form to apply!
August, 2023: I'll be at the EUROPT workshop in Budapest; let me know if you'll be there!
mid June, 2023: I will be at Jordan Symposium in France, let me know if you're there!
May 31 - June 3, 2023: I will be at SIAM OP23 in Seattle, and talk about solving VIs with constraints: slides
May 1 - May 5, 2023: I will attend ICLR in person and talk about how to solve games with constraints

Hiring

I have open positions for research assistants, PhD students, and Postdocs at CISPA and Saarland University!
Use this form to apply, and drop me an email after (follow the instructions therein).
Earliest starting time is October 2023.

Research interests

My main interests are at the intersection of game theory and machine learning. My research aims to better understand the training dynamics of multi-player games and develop improved methods for their optimization. In addition, my broader interests include unsupervised learning, generative modeling, generalization, and robustness.

Other

I am very passionate about cultivating a diverse and inclusive ML community, and I actively participate in various activities, most prominently as part of the board of directors and Vice President of the Events committee of WiML. Outside work, I enjoy hiking, (acro)yoga, biking, and playing games. I love traveling to places with distinct nature (and taking photos of such landscapes :) ).

Selected Research Projects

* Equal contributions.

Google Scholar

Talks

Supervision & Teaching Assistance

  • Tong Yang, On Interior Point Approach for Solving Variational Inequalities
    2022, UC Berkeley.
  • 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.

Activities

Reviewing

Workshops

Socials

Reading Group

Misc

Panel

Contact

If you'd like to discuss my work or broadly on doing research in CS, DEI activities, etc., please don't hesitate to reach out at: tatjana.chavdarova[at]berkeley[dot]edu