Postdoctoral Researcher and Lecturer @ 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 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. Find my full CV here.
TOAST: Transformer Optimization using Adaptive and Simple Transformations has been accepted AS-IS in Transactions on Machine Learning Research (TMLR)!
Structure is Supervision: Multiview Masked Autoencoders for Radiology and You Only Train Once: Differentiable Subset Selection for Omics Data has been accepted in Transactions on Machine Learning Research (TMLR).
From Leads to Latents (GRaM), Beyond Independent Frames (FM4Science), and Rethinking Machine Unlearning (TTU, Oral).
Co-organized and moderated the panel session of UniReps at NeurIPS2025 with Sara Hooker, Ahmad Beirami, and Meenakshi Khosla.
Proud to announce my membership in the ELLIS Society, joining a community of leading European AI researchers!