Alessandro Abate
Professor of Control Engineering
Combines control theory and formal verification to provide formal guarantees for increasingly complex AI agents, drawing on decision theory, logic and probability.
Alessandro Abate's lab at Cambridge works on learning theory & optimization, reasoning & neuro-symbolic AI and compilers & programming languages. 92 papers since 2023, 35 at top venues, mostly AAAI and CDC. Applications close .
At a glance
- papers, 2023–2026
- 24/ year
- at T1 venues
- 38%
- PhD students
- —
- MS students
- —
- alumni listed
- —
Papers by yearfrom DBLP, 2023–2026
- 19 papers2026 · T1 9 · collecting
- 27 papers2025 · T1 8
- 21 papers2024 · T1 9
- 25 papers2023 · T1 9
T1 venuesOtherVenues: AAAI, CDC, L4DC, AAMAS, Artificial Intelligence
Research focuspaper titles that use each topic's words
- Learning theory & optimization27 papers
- formal9 papers
- Reasoning & neuro-symbolic AI5 papers
- Compilers & programming languages0 papers
- probability0 papers
Paper list
From DBLP.
202619 papers
- AAAI (T1)Best-Effort Policies for Robust Markov Decision Processes (opens in a new tab)
- IEEE Control. Syst. Lett.Categorical Characterization of Template-Dependent Ordering of Graph-Based Lyapunov Stability Certificates (opens in a new tab)
- SAIVCertified Neural Approximations of Nonlinear Dynamics (opens in a new tab)
- LICSComplete ω-Regular Supermartingale Certificates (opens in a new tab)
- Autom.Data-driven certificate synthesis (opens in a new tab)
- ICCAD (T1)Efficient and Scalable Multi-Agent Traffic Signal Control via Mean-Field Approximation in Reinforcement Learning (opens in a new tab)
- AAAI (T1)Efficient Solution and Learning of Robust Factored MDPs (opens in a new tab)
- IEEE Trans. Smart GridExact Characterization of Aggregate Flexibility via Generalized Polymatroids (opens in a new tab)
- AAMAS (T1)Fair Coordination in Strategic Scheduling (opens in a new tab)
- Sci. Comput. Program.Fossil 2.0: Design, usage and impact of a software tool for verification and control of dynamical models (opens in a new tab)
- AAAI (T1)Incremental Data-Driven Policy Synthesis via Game Abstractions (opens in a new tab)
- AAMAS (T1)Networked Communication for Mean-Field Games with Function Approximation and Empirical Mean-Field Estimation (opens in a new tab)
202527 papers
- Annu. Rev. Control.A general framework for verification and control of dynamical models via certificate synthesis (opens in a new tab)
- Real Time and SuchAdaptive Task Planning and Formal Control Synthesis Using Temporal Logic Trees (opens in a new tab)
- CAVBranching Bisimulation Learning (opens in a new tab)
- TACASCertifiably Robust Policies for Uncertain Parametric Environments (opens in a new tab)
- CDCCertified Approximate Reachability (CARe): Formal Error Bounds on Deep Learning of Reachable Sets (opens in a new tab)
- CDCContinuous-time Data-driven Barrier Certificate Synthesis (opens in a new tab)
- CDCData-Driven Abstraction and Synthesis for Stochastic Systems with Unknown Dynamics (opens in a new tab)
- TAC (T1)Data-Driven Memory-Dependent Abstractions of Dynamical Systems via a Cantor-Kantorovich Metric (opens in a new tab)
- L4DCData-Driven Yet Formal Policy Synthesis for Stochastic Nonlinear Dynamical Systems (opens in a new tab)
- ICLR (T1)DeepLTL: Learning to Efficiently Satisfy Complex LTL Specifications for Multi-Task RL (opens in a new tab)
- ACM Trans. Auton. Adapt. Syst.Efficient Model Verification at Runtime through Adaptive Dynamic Approximation (opens in a new tab)
- AAMAS (T1)Equilibrium Selection via Communication Partition (opens in a new tab)
202421 papers
- ECCA Stability-Based Abstraction Framework for Reach-Avoid Control of Stochastic Dynamical Systems with Unknown Noise Distributions (opens in a new tab)
- CAVBisimulation Learning (opens in a new tab)
- L4DCBounded robustness in reinforcement learning via lexicographic objectives (opens in a new tab)
- HSCCCTL Model Checking of MDPs over Distribution Spaces: Algorithms and Sampling-based Computations (opens in a new tab)
- NeurIPS (T1)Deep Bayesian Active Learning for Preference Modeling in Large Language Models (opens in a new tab)
- TAC (T1)Distributional Reachability for Markov Decision Processes: Theory and Applications (opens in a new tab)
- IEEE Control. Syst. Lett.Enhancing Data-Driven Stochastic Control via Bundled Interval MDP (opens in a new tab)
- HSCCFossil 2.0: Formal Certificate Synthesis for the Verification and Control of Dynamical Models (opens in a new tab)
- L4DCLearning robust policies for uncertain parametric Markov decision processes (opens in a new tab)
- L4DCLearning-based rigid tube model predictive control (opens in a new tab)
- Principles of VerificationModel Checking and Strategy Synthesis with Abstractions and Certificates (opens in a new tab)
- Artificial Intelligence (T1)Probabilistic reach-avoid for Bayesian neural networks (opens in a new tab)
202325 papers
- CDCAbstracting Linear Stochastic Systems via Knowledge Filtering (opens in a new tab)
- CDCAn Exact Characterisation of Flexibility in Populations of Electric Vehicles (opens in a new tab)
- ARCHARCH-COMP23 Category Report: Stochastic Models (opens in a new tab)
- Artificial Intelligence (T1)Certified reinforcement learning with logic guidance (opens in a new tab)
- FMAS@iFMCorrect-by-Construction Control for Stochastic and Uncertain Dynamical Models via Formal Abstractions (opens in a new tab)
- CDCData-driven Abstractions via Adaptive Refinements and a Kantorovich Metric (opens in a new tab)
- L4DCData-driven memory-dependent abstractions of dynamical systems (opens in a new tab)
- CDCDistributionally Robust Optimal and Safe Control of Stochastic Systems via Kernel Conditional Mean Embedding (opens in a new tab)
- QESTFormal Controller Synthesis for Markov Jump Linear Systems with Uncertain Dynamics (opens in a new tab)
- TAC (T1)Grid-Free Computation of Probabilistic Safety With Malliavin Calculus (opens in a new tab)
- CDCInner Approximations of Stochastic Programs for Data-Driven Stochastic Barrier Function Design (opens in a new tab)
- ACM Trans. Model. Comput. Simul.Introduction to the Special Issue on QEST 2021 (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to CambridgeMichaelmas 2027
PhD in Computer Science
- Round
- Funding round (8 Dec 2026)
- Opens
- GRE
- See program page
- English
- See program page
- Fee
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Confirmed on the program page.
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