UMA Home page for Andrea Simonetto
Phone +33 18 187 2117
I work at the intersection of optimization and learning for large-scale and streaming data, with a number of application domains as smart grids, intelligent transportation, personalized health, and quantum computing. Things that I am currently working on
- Online algorithms for time-varying optimization problems (prediction-correction, correction-only, feedback-based).
- Personalized optimization with Gaussian Processes.
- Online algorithms for dynamic ridesharing and shared mobility.
- Optimization algorithms on quantum computers.
- Applications: smart grids, intelligent transportation, personalized health, quantum computing.
- Convex and non-convex optimization: both from a theoretical perspective and algorithmic implementation. Recent works include prediction-correction algorithms to track the solution trajectory of time-varying convex programs. Older works include networked SDP convex relaxations of certain classes of non-convex programs.
- Distributed optimization, especially in connection with robotic and wireless sensor networks.
- Control theory in the context of distributed control design, model predictive control, embedded control systems.
- Signal processing: distributed estimation, sparse reconstructions, compressive sensing, wireless sensor network localization, sensor selection, graph signal processing.
- Parallel computing in the context of nonlinear estimation and specifically particle filtering.
Papers in peer-reviewed journals
- A Quantum Algorithm for the Sub-Graph Isomorphism Problem
ACM Transactions on Quantum Computing, ACM, 2022
- Best Approximate Quantum Compiling Problems
ACM Trans.Quant.Comput., vol. 3 (2), pp. 7, 2022
- Distributed Personalized Gradient Tracking with Convex Parametric Models
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IEEE Transactions on Automatic Control, pp. 1-1, Institute of Electrical and Electronics Engineers, 2022
- Time-Varying Optimization of Networked Systems With Human Preferences
IEEE Transactions on Control of Network Systems, pp. 1-12, IEEE, 2022
- Personalized optimization with user’s feedback
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Automatica, vol. 131, pp. 109767, Elsevier, sep, 2021
International conferences with proceedings
- Achievement and Fragility of Long-term Equitability
Artificial Intelligence, Ethics, and Society (AIES) (Oxford), jun, 2022
- Learning equilibria with personalized incentives in a class of nonmonotone games
European Control Conference (London), jun, 2022
- OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression
Learning for Dynamics & Control Conference (Stanford), may, 2022
- Optimizing through change for cyber-physical and social systems
Institut Polytechnique de Paris, sep, 2022