news
- May 2026 Started my summer research internship at Layer Health. I will work on training self-improving LLM agents with experts in the loop to provide clinical decision guidance.
- Apr 2026 Uncovering bias mechanisms in observational studies is accepted at ICML 2026.
- Mar 2026 New preprint. We use LLMs to streamline building powerful input representations in complex datasets to enable sample-efficient downstream learning.
- Dec 2025 Presenting two papers at NeurIPS. Zero-shot activity prediction with multimodal data using LLMs from my summer internship at Apple, and prediction-powered causal inferences with R. Cadei and P.D. Bartolomeis.
- Oct 2025 Presenting Prediction-powered generalization of causal inferences at IMES retreat. Slides are here.
- Jul 2025 I gave a hands-on practical workshop on causal inference at Paris AI4Health school. The material is here.
- Jun 2025 New preprint. We propose a method for detecting the source of bias in observational data by evaluating it against experimental data.
- May 2025 Started my summer research internship at Apple. I'll work on reasoning over multimodal data with LLMs.
- Feb 2025 Serving as the discussant for Maggie Makar's talk at the causal inference seminar organized by the Harvard Data Science Initiative.
- Jan 2025 T-cell representation learning work from my Microsoft internship is accepted at ICLR. We developed an approximate linear-time method for scalable learning of T-cell representations.
- Jul 2024 Presenting Prediction-powered generalization of causal inferences at ICML in Vienna.
- May 2024 Started my summer research internship at Microsoft. I'll work on developing better representations & models of the human immune system.
- Apr 2024 Presenting Benchmarking observational studies with experimental data under right-censoring at AISTATS in Valencia.