Hey, welcome to my page!
I do my phd in the university of Geneva under the supervision of prof. Bart Vandereycken. My interests lie in the areas of optimization, differential geometry and machine learning. Recently, I'm interested in seeking for convexity-like structures in important data science problems, focusing now on eigenvalue problems. In the past, I have worked on distributed optimization supervised by prof. Dan Alistarh in IST Austria and on accelerated optimization on manifolds supervised by prof. Aurelien Lucchi in ETH Zurich. From August to October 2022, I visited the group of prof. P-A Absil in UC Louvain.
Currently, I am visiting TU Munich working with prof. Suvrit Sra!
You can find out about my research in google scholar and connect with me via linkedin.
*New preprints on algorithmic perspectives of the symmetric eigenvalue problem:
F. Alimisis, B. Vandereycken: Geodesic Convexity of the Symmetric Eigenvalue Problem and Convergence of Riemannian Steepest Descent
F. Alimisis, Y. Saad and B. Vandereycken: Gradient-type subspace iteration methods for the symmetric eigenvalue problem
Below you can see my résumé:
CV.pdf