Prof. Simone Fiori, M.E. (Hons), Ph.D.

Mailing address:
DII – Dipartimento di Ingegneria dell'Informazione
uPM – Università Politecnica delle Marche
Via Brecce Bianche, Ancona I-60131 (Italy, EU)

Room: Q165_173

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I was born in Rimini (Italy). I received the Italian Laurea (with honors) from the University of Ancona (Italy), and the Ph.D. degree from the University of Bologna (Italy).

Positions held:

I'm currently an Associate Professor at the School of Information and Automation Engineering of the Università Politecnica delle Marche (Italy), where I've been teaching electrical engineering, numerical calculus and mathematical methods in automation.
I'm also currently holding a Visiting Professor position at Peng's Lab at the Keio University (Japan) for the academic year 2023-2024.

Current scientific research interests:

Modeling and simulation of complex aircrafts. Modeling of unmanned quadcopter drones and helicopters, and simulating numerically their behavior by manifold calculus. Animation by A. Tarsi: Simulation of a helicopter take-off.
Modeling, simulation and control of complex underwater vehicles. Modeling of unmanned underwater vehicles, designing appropriate controllers for trajectory following, and simulating numerically their behavior by manifold calculus.
Modeling, simulation and control of complex spacecrafts. Modeling of unmanned spacececraft, designing appropriate controllers for reorientation and rendezvous maneuvers, and simulating numerically their behavior by manifold calculus. Animation by E. Sampaolesi: Simulation of a spacecraft effecting a rendezvous to a space station.
Simulation and control of DC2DC power converters. Modeling of DC-to-DC electrical power converters, designing appropriate controllers to achieve conversion, and simulating numerically their behavior by manifold calculus.
Optimization on manifolds and Lie groups. Geometrical (pseudo-) Riemannian-gradient optimization methods and numerical calculus techniques. Dynamical systems on manifolds to optimize smooth criteria. Symplex (Amoeba) methods on manifolds to optimize non-smooth criteria.
Statistics on smooth manifolds: Generation of pseudo-random clouds and pseudo-random processes on differentiable manifolds and Lie groups. ARMA-type models on differentiable manifolds and Lie groups. Cross- and auto-correlation functions on differentiable manifolds and Lie groups.
Non-linear oscillators on Lie groups and smooth manifolds. Continuous-time, second-order dynamical systems on Lie groups and manifolds exhibiting periodic oscillatory behavior as well as continuous-time, second-order chaotic systems.
Non-linear control on smooth manifolds and related numerical calculus techniques. Extension of PID-like control theories. Minimum effort control theories. Consensus and virtual-potential control. Numerical techniques to implement non-linear control theories on manifolds. Synchronization of dynamical systems on manifolds. Animation by A. Saccuti: Synchronization of two satellites when one of them gets hit repeatedly.
Statistical data modeling and regression. Statistical isotonic modeling and data regression. Non-linear transformations to extend isotonic modeling to non-monotonic data.
MATLAB-based implementation.

Past scientific research interests:

Application of numerical calculus on manifolds to machine learning and signal/data processing. Foundations of machine learning and signal/data processing on smooth manifolds.
Artificial neural systems and algorithms for signal/data processing. (Here is a scanned version of a stamp with a portrait issued by the USSR in 1983 to commemorate the 1200th anniversary of Muhammad al-Khowarizmi, after whom algorithms are named).
Unsupervised learning theory (principal/independent component/subspace analysis, information-theoretic learning) and neural units with adaptive activation functions.
Linear and non-linear adaptive discrete-time filtering. Blind deconvolution of non-minimum phase systems, blind image deblurring.
Non-linear and non-stationary continuous-time circuits with stochastic excitations. Statistical isotonic modeling and data regression.

(Statistics since January 26, 2006)

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