Visiting Scientist at SLAC through Sep 2026
Ivan Brillo
AI researcher · Visiting Scientist at SLAC, Stanford University
I build machine learning methods for science and healthcare. Right now I’m a Visiting Scientist at SLAC National Accelerator Laboratory (Stanford University) in the Vernieri Group, developing an agentic AI system that automates the optimization and design of particle detectors for the Future Circular Collider (FCC-ee).
I recently graduated, 110 cum laude, from the MSc in Artificial Intelligence & Data Engineering at the University of Pisa. I’m also pursuing the Advanced MSc in Robotics at the Sant’Anna School of Advanced Studies on a full merit scholarship. Before SLAC, I was a Mitacs Globalink visiting researcher at Mila, developing CNN surrogates that replace expensive Gaussian Process updates.
My work spans surrogate modelling and Bayesian optimization, deep learning for physiological signals (ECG, EEG), explainable AI for clinical applications, and embedded systems. I’m always happy to talk about research collaborations.
Menlo Park, CA · Pisa, Italy
News
All news- Presented AI-driven optimization of detector design for the FCC-ee at the 4th US FCC Meeting at SLAC.
- Graduated from the MSc in Artificial Intelligence & Data Engineering at the University of Pisa with 110 cum laude.
- Submitted ResCTrans, an explainable Transformer-based amyloidosis classifier from ECG signals, to the IEEE Journal of Biomedical and Health Informatics.
- Joined SLAC National Accelerator Laboratory (Stanford University) as a Visiting Scientist in the Vernieri Group, building agentic AI for FCC detector design.
- Awarded the Zegna Scholarship for academic excellence and merit.
Experience
Full CV- Jul 2026 – Sep 2026
SLAC National Accelerator Laboratory (Stanford University)
Developing an agentic AI system to automate the optimization and design of Future Circular Collider (FCC) particle detectors. Supervisor C. Vernieri.
- Mar 2026 – Jun 2026
Mila — Quebec Artificial Intelligence Institute
Developed CNN surrogates to replace computationally expensive online Gaussian Process updates. Funded by a Mitacs Globalink Research Scholarship. Supervisor M. Bonizzato.
- Oct 2025 – Jul 2026
Research Center "E. Piaggio"
Framing R-peak prediction from EEG as a segmentation problem via distance-to-peak estimation, evaluating multi-scale CNNs and autoregressive models with a focus on domain generalization. Supervisor M. Cimino.
- Sep 2025 – Jan 2026
Monasterio Foundation
Cardiac amyloidosis classification from ECGs using Transformers, with interpretability via Grad-CAM and Attention Rollout. Supervisor C.A. Avizzano.
- Feb 2025 – Oct 2025
Sant'Anna School of Advanced Studies
- Explainable classification of tumor-mimicking materials from force/position data. Supervisor C.M. Oddo.
- Efficient federated learning via dynamic training-precision adjustment. Supervisor E. Paolini.
