Scholar
Javier Abad
Google Scholar ID: gGHkUhkAAAAJ
ETH Zurich
Citations & Impact
Citations
70
H-index
6
i10-index
4
Publications
8
Co-authors
12
list available
Publications
Resume (English only)
Academic Achievements
- Recent paper: 'Efficient Randomized Experiments Using Foundation Models', which explores integrating predictions from multiple foundation models with experimental data while preserving valid statistical inference.
Research Experience
- Previously led a project on conformal prediction under the guidance of Adrian Weller MBE; researched interpretability methods for causal inference with Prof. Mihaela van der Schaar; worked as a Research Scientist at Featurespace, researching and implementing ML models to fight financial crime.
Education
- PhD student at ETH AI Center, advised by Prof. Fanny Yang and Prof. Julia Vogt.
Background
- Research interests include developing machine learning models that can be trusted for high-stakes decision-making, particularly in the areas of AI safety, privacy, and causal inference. Currently looking into copyright protection for language models, privacy preservation in sensitive datasets, and the detection and estimation of hidden confounding bias.
