Irene Cannistraci, PhD

Postdoctoral Researcher, ETH Zurich

Postdoctoral Researcher and Lecturer at ETH Zurich in the Institute of Machine Learning, working on representation learning, multimodal machine learning, foundation models, efficiency and post-training. I received my PhD with honors from Sapienza University in 2025, and one of my works has been recognized with an ICLR 2024 Spotlight (top 5%).

I am also an ELLIS member, co-organizer of the UniReps workshop series at NeurIPS and the ELLISxUniReps speaker series, and the co-leader of CSNOW, Computer Science Network of Women at ETH.

Feel free to reach out at irene.cannistraci[at]inf.ethz.ch

Latest News & Updates

Mar 2026

publication

New paper on multimodal representation learning accepted to TMLR!

Structure is Supervision: Multiview Masked Autoencoders for Radiology has been accepted as is for publication in Transactions on Machine Learning Research (TMLR).

Mar 2026

publication

3 papers accepted at ICLR 2026 Workshops with an oral contribution!

From Leads to Latents (GRaM), Beyond Independent Frames (FM4Science), and Rethinking Machine Unlearning (TTU, Oral).

Dec 2025

publication

New preprint online!

You Only Train Once: Differentiable Subset Selection for Omics Data.

Dec 2025

organization

UniReps 2025 Workshop Co-Organizer and Panel Moderator

Co-organized and moderated the panel session of UniReps at NeurIPS2025 with Sara Hooker, Ahmad Beirami, and Meenakshi Khosla.

Nov 2025

award

ELLIS Member

Proud to announce my membership in the ELLIS Society, joining a community of leading European AI researchers!

Selected Publications

View all publications

TOAST: Transformer Optimization using Adaptive and Simple Transformations

Irene Cannistraci, Simone Antonelli, Emanuele Palumbo, Thomas Sutter, Emanuele Rodolà, Bastian Rieck, Julia Vogt

Under Review 2025

View paper

From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication

Irene Cannistraci, Luca Moschella, Marco Fumero, Valentino Maiorca, Emanuele Rodolà

ICLR 2024 2024 Spotlight · Top 5%

View paper