Data science in Physics and Material science
Machine Learning
- Symbolic Regression techniques
- Properties prediction
- Active learning
- Connect ML to simulations
- Advanced regression techniques
- Neural networks
Time series analysis
- Physical data prediction
- Spatiotemporal analysis
- Correlations and causalities
- Clustering analysis
- Event Detection
- Econo-physics
Complex System Dynamics
- System dynamics
- Chaotic behavior
- Recurrence and cross-recurrence analysis
- Fuzzy clustering
- Support decision systems
Complex Network Analysis
- Community structure
- Topological properties
- Graph theory application
Applications
- Experimental time series analysis
- Spatiotemporal rain analysis from radar images
- Spatiotemporal analysis of field measurments
- Event detection from highway sensor data analysis
Fluid flows at the nanoscale
Computational methods
- Molecular Dynamics
- Dissipative Particle Dynamics
- Smoothed-Particle Thermodynamics
- Computational Fluid Dynamics
- Multiscale modeling
Applications
- Water desalination
- Magnetic driving of particles for water cleaning and drug delivery
- Crack propagation
- Electric/Magnetic-driven flows
- Transport properties of fluids
- Hydrophobic/Hydrophilic surfaces
- Turbulent flows
Material properties
Physical properties (electrical, dielectric, optical) of technological materials
- nano-composite polymeric materials
- multifunctional polymeric materials
- composite polymeric materials
- materials of micro-nanoelectronics
- semiconductor materials and devices
- ceramic materials
- insulating materials
- polymer electrolytes
- cement morta
Applications
- Investigation of the relationship between structure and properties of materials
- Energy harvesting and storage in polymeric nanosystems and nanostructured systems
- Study of the conductivity of polymeric systems
- Development of complex polymeric systems for electromagnetic shielding
- Study of Weyl and Dirac particles interaction with electromagnetic fields