Projects

Ongoing Projects:

• Machine Learning for Complex Systems

• Learning Control and Reinforcement Learning for Behavioral Epidemic Models

• Chaotic Dynamical Systems

• Scientific Machine Learning

• Modeling Vector-Borne Diseases

• Theoretical Systems Biology

• Stochastic Evolutionary Game Theory 

• Mathematical Oncology

• Machine Learning Applied to Health Data Analytics

• Statistical Physics Applied to Systems Biology

• Theretical Physics and Statistics applied to Ecology

• Non-markoviolkan Modeling

• Nonlocal Spatiotemporal Models

Published Projects

• Non-markovian Extensions of Lorenz Model

• Stochastic Evolutionary Games as irrationality model in Behavioral Epidemiology

• Evolutionary Game Theory Applied to Behavioral Epidemiology: role of homophily (CA: Chris Bauch, Waterloo University, Canada)

• Reinforcement Learning for Behavioral Epidemic Models (CA: Giulio Pisaneschi, Pisa University)

• Classical Game Theory Applied to Pandemic PH Decisions (CA: Alessio Carrozzo-Magli, Bologna University)

• Spatiotemporal Quasiperiodicity In Behavioral Epidemics

• Phase Transitions in Behavioral Epidemiology

• Statistical Physics applied to Theoretical Machine Learning (preprint) (CA: Fabio Anselmi, UniTS)

• Spatiotemporal Chaos In Behavioral Epidemiology

• COVID-19 and Behavior Modeling: a Systematic Review

• Bounded Noise-induced 'phase transitions' in Bistable Biochemical Systems

• Machine Learning for Health Data Analytics applied to COVID-induced Penumonia 

• Deep Learning and Bayesian Learning in Behavioral Epidemiology of Diseases Super Spreading 

• Singular Perturbation Theory applied to Behavioral Epidemiology 

• Geometric Semantic Genetic Programming (CA Muaro Castelli, Nova Universidade, Lisboa)

• Hybrid Stochastic Modeling in Behavioral Epidemiology

• Machine Learning applied to Quantum Mechanics (CA Fabio Anselmi, Trieste University)

• Adversarial Attacks interplay with Implicit Bias (CA Fabio Anselmi, Trieste University)

• Fairness for Machbne Learning apllied to Health Data (CA Chiara Gallese, then at Turin University)

• Stochastic Behavioral Multi-Agents Systems (CA Julia Klein, Konstanz University, Germany)

• Forced Chaotic Models in Epidemiology

• Classical Optimal Control and Subharmonic Resonances

• Pandemic Modeling (CA Mimmo Iannelli, Trento University)

• Classical Optimal Control for Behavioral Epoidemiology (Paper 1)

• Classical Optimal Control for Behavioral Epoidemiology (Paper 2, CA Mimmo Iannelli, Teento University)

• Membrane Computing applied to Multi-Agent Systems in Population Biology (CA Claudio Zandron, Milano Bicocca University)

• Generative Adversarial Networks for Stochastic Population Models (CA Francesca Cairoli, Trieste University)

• Data symmetries and Learning in fully connected neural networks (CA Fabio Anselimi, Trieste University)

• Julia Language for inferences in Computational Oncology (CA Fabrizio Angaroni, then at Milan Bicocca University)

• Computational Tumor Genomics (CA Giulio Caravagna, Trieste University)

• Bayesian Learning algorithms in Oncogenomics (CA Giulio Caravagna, Trieste University)