The Materials Modeling and Scientific Computing Group at GeM Laboratory pioneers cutting-edge research in computational mathematics and machine learning to decode complex phenomena in soft matter and advanced materials. Led by Prof. Zecheng Gan, the group focuses on developing scalable numerical algorithms, data-driven methodologies, and multiscale modeling frameworks for simulating electrostatics, hydrodynamics, and charged systems at mesoscopic scales. Their mission is to bridge theoretical insights with engineering applications, advancing innovations in energy materials, dielectric colloids, and biomolecular systems. By synergizing high-performance computing, AI-enhanced simulations, and cross-disciplinary collaborations, the team aims to establish predictive computational paradigms for next-generation material design and smart manufacturing.
- Fast algorithms for materials simulations
- Data-driven and machine learning approaches for materials sciences
- Applied math and scientific computing
- Computational electromagnetism and hydrodynamics
- Computational materials science