Leonardo Bardi

Biography

Leonardo Bardi is an academic researcher at TU Chemnitz. His research focuses on Statistical learning, Generalized Bayesian learning, Weak dependence, Stochastic Partial Differential Equations and Ambit Stochastics.

Research Interests

Statistical learning
Generalized Bayesian learning
Weak dependence
Stochastic Partial Differential Equations
Ambit Stochastics

Publications

Probabilistic forecast for raster datasets: a theory-guided machine learning methodology based on spatio-temporal Ornstein-Uhlenbeck processes

L. Bardi, I.V. Curato, L. Proietti

Forthcoming, 2026

Spatio-temporal probabilistic forecast using MMAF-guided learning

L. Bardi, I.V. Curato, L. Proietti

Arxiv preprint, 2026

An Exploration of the Effects of Periodic Top Predator Interference and Hunting on a Predator-Prey System

L. Bardi

Trends in Biomathematics: Exploring Epidemics, Eco-Epidemiological Systems, and Optimal Control Strategies — Book chapter, 2024

Conferences

GSPD 2025 (Attendee)
NordStat 2026 (Contributed Talk)

Workshops

DYNSTOCH 2026 (Contributed Talk)

Summer Schools

43rd Finnish Summer School on Probability and Statistics (Attendee)
ProbAI 2025 (Poster Presentation)
Lake Como School on Stochastic Dynamics: Foundations and Applications 2026 (Attendee)
2nd Summer School on PDEs and Randomness 2026 (Attendee)

Teaching

Statistics in Data Science

Contact

Email: leonardo.bardi at mathematik.tu-chemnitz.de
Office: Reichenhainer Str. 41, Room C47.615
Phone: +49 (0371) 531-33788
ORCID: 0009-0004-3204-2886