activity
20242026
collaborators

6 papers

cs.AI2026

Safety Certification is Classification

Oliver Schön, Licio Romao, Sadegh Soudjani

The goal of this paper is certifying safety of dynamical systems subject to uncertainty. Existing approaches use trajectory data to estimate transition probabilities, and compute s…

eess.SY2026

Truthful Production Uncertainty in Electricity Markets: A Two-Stage Mechanism

Shobhit Singhal, Lesia Mitridati, Licio Romao

Renewable power sources have low marginal pro-duction costs, but may result in high balancing costs due to the inherent production uncertainty. Current day-ahead markets elicit onl…

eess.SY2025

Exact Recourse Functions for Aggregations of EVs Operating in Imbalance Markets

Karan Mukhi, Licio Romao, Alessandro Abate

We study optimal charging of large electric vehicle populations that are exposed to a single real-time imbalance price. The problem is naturally cast as a multistage stochastic lin…

cs.LG2025

Bridging conformal prediction and scenario optimization

Niall O'Sullivan, Licio Romao, Kostas Margellos

Conformal prediction and scenario optimization constitute two important classes of statistical learning frameworks to certify decisions made using data. They have found numerous ap…

cs.LG2024

Risk-Averse Certification of Bayesian Neural Networks

Xiyue Zhang, Zifan Wang, Yulong Gao +3

In light of the inherently complex and dynamic nature of real-world environments, incorporating risk measures is crucial for the robustness evaluation of deep learning models. In t…

eess.SY2024

A data-driven approach for safety quantification of non-linear stochastic systems with unknown additive noise distribution

Frederik Baymler Mathiesen, Licio Romao, Simeon C. Calvert +2

In this paper, we present a novel data-driven approach to quantify safety for non-linear, discrete-time stochastic systems with unknown noise distribution. We define safety as the…