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News
- 🗓 July 2025: Organizing the Reliable ML with Unreliable Data workshop at NeurIPS 2025 with Andrew Ilyas, Anay Mehrotra, and Manolis Zampetakis
- 🗓 June 2025: Our paper on causal inference got the Best Paper Award at COLT 2025
- 🗓 April 2025: Our paper on diffusion models and distribution learning got the Short Best Paper Award at the ICLR 2025 DeLTa workshop
- 🗓 April 2025: Completed my course on Stability in Machine Learning for Spring 2025. The lecture notes can be found here
I am an FDS Postdoctoral Fellow at Yale University. Before that, I was a PhD student in the Computer Science Department of the National Technical University of Athens (NTUA) working with Dimitris Fotakis and Christos Tzamos. I completed my undergraduate studies in the School of Electrical and Computer Engineering Department of the NTUA.
I work on statistical and computational learning theory. My research focuses on the design of algorithms with rigorous guarantees for Machine Learning problems. I am particularly interested in:
- Learning from imperfect data: designing efficient algorithms that are robust to imperfect data for problems arising in Machine Learning and Econometrics with applications to Causal Inference.
- Generalization and stability: understanding the generalization properties of algorithms and their stability to changes in the training data (replicability, privacy, memorization, learning curves).
- Generative modeling: proving rigorous guarantees for generative models, but also designing practical methods for diffusion and language models.
I am on the 2025/26 job market.
Feel free to contact me at: alkis.kalavasis[at]yale.edu