A data-driven approach for safety quantification of non-linear stochastic systems with unknown additive noise distribution
arXiv, 2024.
Data-driven memory-dependent abstractions of dynamical systems via a Cantor-Kantorovich metric
arXiv, 2024.
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers
arXiv, 2024.
Enhancing Data-Driven Stochastic Control via Bundled Interval MDP
IEEE Control Systems Letters, 2024.
On the exact feasibility of convex programs with discarded constraints
IEEE Transactions on Automatic Control, 2023.
Probabilistic feasibility guarantees for convex scenario programs with an arbitrary number of discarded constraints
Automatica, 2023.
Robust Control for Dynamical Systems with Non-Gaussian Noise via Formal Abstractions
Journal of Artificial Intelligence Research 2023. Distinguished Paper Award. AAAI 2022.
Distributed Actuator Selection: Achieving Optimality via a Primal-Dual Algorithm
IEEE Control Systems Letters, 2018.
Bounded Robustness in Reinforcement Learning via Lexicographic Objectives
6th Annual Learning for Decision and Control 2024. Oral presentation. Top 6 percent.
A Stability-Based Abstraction Framework for Reach-Avoid Control of Stochastic Dynamical Systems with Unknown Noise Distributions
2024 European Control Conference (ECC), 2024.
Probabilities Are Not Enough: Formal Controller Synthesis for Stochastic Dynamical Models with Epistemic Uncertainty
AAAI Conference on Artificial Intelligence, 2023.
Inner Approximations of Stochastic Programs for Data-Driven Stochastic Barrier Function Design
62nd IEEE Conference on Decision and Control (CDC), 2023.
Data-driven Abstractions via Adaptive Refinements and a Kantorovich Metric
62nd IEEE Conference on Decision and Control (CDC), 2023.
Abstracting Linear Stochastic Systems via Knowledge Filtering
62nd IEEE Conference on Decision and Control (CDC), 2023.
Formal Controller Synthesis for Markov Jump Linear Systems with Uncertain Dynamics
International Conference on Quantitative Evaluation of Systems, 2023.
Data-driven memory-dependent abstractions of dynamical systems
5th Conference on Learning for Dynamics & Control, 2023.
Distributionally Robust Optimal and Safe Control of Stochastic Systems via Kernel Conditional Mean Embedding
62nd IEEE Conference on Decision and Control (CDC), 2023.
Tight sampling and discarding bounds for scenario programs with an arbitrary number of removed samples
3rd Conference on Learning for Decision and Control, 2021.
Tight generalization guarantees for the sampling and discarding approach to scenario optimization
59th Conference on Decision and Control, 2020.
Convergence rate analysis of a subgradient averaging algorithm for distributed optimisation with different constraint sets
58th Conference on Decision and Control (CDC), 2019.
H-inf filter design with low- and middle-frequency specifications for continuous-time linear systems: LMI conditions derived from two different extensions of the KYP lemma
2018 Annual American Control Conference (ACC), 2018.
Non-minimal order low-frequency H-inf filtering for uncertain discrete-time systems
IFAC-PapersOnLine, 2017.
Projeto de Filtros para Sistemas a Tempo Discreto com Criterio H-infinito em Faixa de Frequencias
Simposio Brasileiro de Automacao Inteligente (SBAI), 2017.
State-feedback and filtering problems using the generalized KYP lemma
Conference on Computer Aided Control System Design (CACSD), 2016.
H-infinity Robust Filter Design for Continuous-Time Linear Systems Using LMIs with a Scalar Parameter
XXI Congresso Brasileiro de Automatica, 2016.
Projeto de Filtros Robustos H-2 usando LMIs com Escalares
Simposio Brasileiro de Automacao Inteligente (SBAI), 2015.
Scalable and data-driven approaches to convex programming
University of Oxford 2021. IET Control and Automation dissertation prize.
Projeto de Filtros para Sistemas Lineares com Critérios H-2, H-infinito e H-infinito em Faixas de Frequência por meio de Desigualdades Matriciais
University of Campinas (UNICAMP), 2017.