Second-year PhD Student in the Data Analytics Lab at ETH Zürich under the supervision of prof. Thomas Hofmann and Dr. Aurelien Lucchi.

I’m interested in design and the analysis of new adaptive stochastic optimization methods for non-convex machine learning problems.

Also, I am involved in several computational systems biology projects, such as SignalX.

For more details, you can check my curriculum vitae.

Practical Accelerated Optimization on Riemannian Manifolds, arvix, 2020.
F. Alimisis, A. Orvieto, G. Becigneul, A. Lucchi

Continuous-time Acceleration in Riemannian Optimization, AISTATS, 2020.
F. Alimisis, A. Orvieto, G. Becigneul, A. Lucchi

Shadowing Properties of Optimization Algorithms, NeurIPS, 2019.
A. Orvieto, A. Lucchi

Continuous-time Models for Stochastic Optimization Algorithms, NeurIPS, 2019.
A. Orvieto, A. Lucchi

The Role of Memory in Stochastic Optimization, UAI, 2019.
A. Orvieto, J. Kohler, A. Lucchi


While the heart beats, bruise it–it is your only opportunity; while the eye can still turn towards you with moist, timid entreaty, freeze it with an icy unanswering gaze; while the ear, that delicate messenger to the inmost sanctuary of the soul, can still take in the tones of kindness, put it off with hard civility, or sneering compliment, or envious affectation of indifference; while the creative brain can still throb with the sense of injustice, with the yearning for brotherly recognition–make haste–oppress it with your ill-considered judgements, your trivial comparisons, your careless misrepresentations. The heart will by and by be still–“ubi saeva indignatio ulterius cor lacerare nequit“; the eye will cease to entreat; the ear will be deaf; the brain will have ceased from all wants as well as from all work. Then your charitable speeches may find vent; then you may remember and pity the toil and the struggle and the failure; then you may give due honour to the work achieved; then you may find extenuation for errors, and may consent to bury them.

George Eliot, The Lifted Veil