I am a postdoc researcher at Center for Life Nano & Neuro Science (CLN2S) at Italian Institute of Technology (IIT), Rome Italy. My current research is focused on developing deep learning-based computer vision algorithms to analyze and study microfluidics experiments.
This link will take you to my Google Scholar profile.
Research center
CLN²S@Sapienza
About
Skills
Machine learning - Reinforcement learning, computer vision, deep learning
HPC computing - Fortran90, Python, PyTorch, TensorFlow
Statistical physics - Active matter systems, far from equilibrium system modelling
All Publications
2024
Durve M., Orsini S., Tiribocchi A., Montessori A., Tucny J.-M., Lauricella M., Camposeo A., Pisignano D., Succi S.
Measuring arrangement and size distributions of flowing droplets in microchannels through deep learning using DropTrack
Physics of Fluids, vol. 36, (no. 2)
2023
Durve M., Orsini S., Tiribocchi A., Montessori A., Tucny J-M., Lauricella M., Camposeo A., Pisignano D., Succi S.
Benchmarking YOLOv5 and YOLOv7 models with DeepSORT for droplet tracking applications
The European Physical Journal E, vol. 46, (no. 32)
2023
Succi S., Bonaccorso F., Durve M., Lauricella M., Montessori A., Tiribocchi A.
Density Functional Kinetic Theory for Soft Matter
Springer INdAM Series, vol. 51, pp. 249-260
2023
Tucny J-M., Durve M., Montessori A., Succi S.
Learning of viscosity functions in rarefied gas flows with physics-informed neural networks
Computers and Fluids, vol. 269, (no. 2024), pp. 106114
2023
Lauricella M., Chiodo L., Bonaccorso F., Durve M., Montessori A., Tiribocchi A., Loppini A., Filippi S., Succi S.
Multiscale Hybrid Modeling of Proteins in Solvent: SARS-CoV2 Spike Protein as Test Case for Lattice Boltzmann – All Atom Molecular Dynamics Coupling
Communications in Computational Physics, vol. 33, (no. 1), pp. 57-76
Colleagues of Multiscale and Quantum Simulations
