Machine learning for meteorological time series
We are investigating machine learning methods for time series analysis in the contexts of meteorology and finance.
Our group blends physics, machine learning and biological behavior to ask how organisms acquire and process complex sensory information from their fluid environment to guide behavior. We deploy state-of-the-art simulations and asymptotic models to portray the fluid flows surrounding living organisms. These data feed machine learning algorithms that model behaviors ranging from sensory predictions and navigation to spore dispersal to the formation of complex bacterial colonies. We are interested in model organisms like mice and bacteria as well as less studied organisms like higher fungi, octopus and jellyfish and real weirdos, like piranhas and sea robins (a fish with legs!)
We are investigating machine learning methods for time series analysis in the contexts of meteorology and finance.
We aim at elucidating the algorithms used by organisms to sense and navigate turbulent environments.
Our research is motivated and inspired by biology and is nurtured by longstanding experimental collaborations in Europe and the US.
We have a longstanding interest in the fundamental properties of turbulent transport of both particles and scalar fields.
Alessandro
Verri
Agnese
Seminara
Giovanni
Minuto
Francesco
Marcolli
Martin
James
Yujia
Qi
Francesco
Boccardo
Luca
Gagliardi
Anna
Khristodulo
Arnaud Ruymaekers | 2023 → 2024 | Research Scholar | Reinforcement Learning
Arnaud Ruymaekers | 2023 | Student | Reinforcement Learning
Daniele Lagomarsino Oneto | 2023 | Post-doctoral fellow
Francesco Marcolli | 2022 → 2023 | Research Scholar | Multiagent RL
Nicola Rigolli | 2022 → 2023 | Post-doctoral fellow
Gianvito Losapio | 2022 | Research Scholar
Andrea Guarnore | 2022 | Student
Matteo Ferrari | 2022 | Student
Title | Year | Author | Venue |
---|---|---|---|
Reconstitution of ORP-mediated lipid exchange coupled to PI4P metabolism | 2024 | Fuggetta Nicolas; Rigolli Nicola; Magdeleine Maud; Hamaï Amazigh; Seminara Agnese; Guillaume Drin And | PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA |
Alessandro De Gloria, a Pioneer in Electronic Engineering Applications | 2024 | Bellotti F.; Bricco E.; Bruzzone A.; Caviglia D.; Di Zitti E.; Gastaldo P.; Grosso D.; Magnani L.; Olivieri M.; Raggio M.; Valle M.; Verri , et al. | International Conference on Applications in Electronics Pervading Industry, Environment and Society, APPLEPIES 2023 |
Physics informed machine learning for wind speed prediction | 2023 | Lagomarsino-Oneto Daniele; Meanti Giacomo; Pagliana Nicolò; Verri Alessandro; Mazzino Andrea; Rosasco Lorenzo; Seminara Agnese | ENERGY |
Molecular tuning of sea anemone stinging | 2023 | S He Lily; Qi Yujia; AH Allard Corey; A Valencia-Montoya Wendy; P Krueger Stephanie; Weir Keiko; Seminara Agnese; W Bellono Nicholas | ELIFE |
An Automatic Tool Performing Functional Analysis in MR Urography in Children | 2023 | Vincenzi Elena; Fantazzini Alice; Gulino Martina; Manini Simone; Verri Alessandro; Odone Francesca; Basso Luca; Damasio MARIA BEATRICE; Basso Curzio | 2023 IEEE 36TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS 2023 IEEE 36TH INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS, CBMS |