Simone Rossi

Simone Rossi is an Assistant Professor in the Data Science department at EURECOM. His research focuses on Bayesian methods, generative models, and deep learning, with particular emphasis on uncertainty quantification, diffusion processes, and scalable probabilistic models. He has contributed to foundational work on functional priors for Bayesian neural networks, conformal prediction for in-context learning, and optimization of diffusion models.

• Education: Not explicitly mentioned in the provided text.

His research interests span machine learning, probabilistic modeling, and theoretical computer science. He explores topics like score-based generative models, continuous-time diffusion processes, and efficient Bayesian inference techniques. Recent work includes analyzing scaling laws for uncertainty in deep learning and improving LLM reasoning capabilities for Text2SQL tasks.

His publications reflect contributions to top conferences like NeurIPS, ICML, and AABI, with a focus on both theoretical advancements and practical applications. Notable achievements include a Runner-up Best Paper Award at PAM 2024 for work on data augmentation in traffic classification.

• Scientific Awards: Runner-up Best Paper Award at PAM 2024

Dr. Rossi collaborates actively with industry and academia, contributing to open-source tools and foundational research in probabilistic deep learning. His work bridges theory and practice, addressing challenges in scalable Bayesian methods and generative model efficiency.