In front of the famous Dresden Semperoper
Skills & Expertise:
Molecular Simulations, Electronic Structure, DFT-to-MD coupling, Python, Bash Scripting, Git, Integration of physics-based simulations with ML (GNN, scikit-learn, PyTorch, Tensorflow), Scientific Writing and presentations
Research Interests:
Intersection between Machine learning and chemistry
Machine learning for materials
Graph neural networks
Molecule generation and optimisation
Diptesh Gayen, PhD
Computational Material Scientist
Welcome to Diptesh's webpage!
I completed my PhD in Applied Theoretical Physics at the University of Freiburg. My work focused on understanding how conjugated organosulfur polymer cathodes interact with realistic electrolytes in lithium-sulfur batteries under different environemnts, combining molecular dyanmics and density functional theory. The broader motivation has always been energy material; not only describing them, but understanding why they behave the way they do.
My academic journey began at Calcutta University, Kolkata, followed by a master's in Physics at Indian Institute of Technology, Gandhinagar (IITGN). During my master, I moved to Japan Advanced Institute of Science and Technology for an research internship, where I worked on DFT simulations on 2D materials and metal intefaces. Later, I continued that topic for my master thesis at IITGN.
Beyond the bench, I am particularly interested in the application of artificial intelligence in the field of material science and chemistry, especially in developing a machine learning interatomic potential (MLIP). The idea is to calculate fast and accurate chemical properties without solving the tedious first-principle calculations.
In "me time" I like to do sports: Karate (dojo), Badminton, and Volleyball. I like to read philosophy and sprituality.
