Portrait image of Amina Mollaysa

Amina has been working on machine learning research and defended her Ph.D. thesis in 2021 February in the Department of Computer Science at the University of Geneva.  After the defense, she has continued working in the DMML research group in HES-SO as a postdoctoral researcher.

The main focus of her research are representation learning, generative models for discrete data, and optimization algorithms. Specifically, she has worked on how to incorporate meta-features (feature side-information) into learning to improve generalization performance, and how to enable the conditional generation and style transfer over discrete structured data such as molecules, trees, or graphs. These are typically hard to optimize, especially for a conditional generation. Methods developed for natural images often fail dues to the discrete nature of the space. She is interested in developing efficient algorithms that can deal with the discrete nature of the data.

AMLD EPFL 2022 / Speakers

Michael Bronstein

Oxford / Twitter / IDSIA

Max Welling

Distinguished Scientist, Microsoft Research

Samy Bengio

Senior Director, AI and Machine Learning Research, Apple

Regina Barzilay

Professor of Electrical Engineering and Computer Science, MIT

Melanie Mitchell

Davis Professor, Santa Fe Institute

Thomas Wolf

Co-founder and Chief Science Officer, Hugging Face

AMLD / Global partners