Mihir Durve is a researcher at the Center for Life Nano & Neuro Science (CLN2S), IIT Rome, specialising in deep learning-based computer vision for microfluidic analysis. He is currently involved in the EIC Pathfinder-funded iNSIGHT project, automating in-air capsule production for precision nutrition.
Research center
CLN²S@Sapienza
About
Education
Title: Ph.D. (Physics)
Institute: University of Trieste and ICTP
Location: Trieste
Country: Italy
From: 2016 To: 2020
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
2025
Tiribocchi A., Durve M., Lauricella M., Montessori A., Tucny J.-M., Succi S.
Lattice Boltzmann simulations for soft flowing matter
Physics Reports, vol. 1105, pp. 1-52
2024
Bogdan M., Pineda J., Durve M., Jurkiewicz L., Succi S., Volpe G., Guzowski J.
Crystallization and topology-induced dynamical heterogeneities in soft granular clusters
Physical Review Research, vol. 6, (no. 3)
Article
Journal
2024
Durve M., Tucny JM., Bhamre D., Tiribocchi A., Lauricella M., Montessori A., Succi S.
Droplet shape representation using fourier series and autoencoders
AIAA Journal, vol. 0, (no. 0), pp. 1-5
2024
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
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)
Colleagues of Multiscale and Quantum Simulations
