I am a theoretical and computational materials scientist with interdisciplinary expertise spanning chemical and materials science, chemistry, physics, and biophysics. My research combines first-principles quantum mechanical simulations, molecular dynamics, atomistic modeling, and machine learning to understand and design materials at the atomic and molecular scale. 

My long-term vision is to establish a research program that advances computational materials and chemical science through rigorous theory, simulation, and data-driven discovery. My work aims to accelerate the design of functional materials and nanoscale devices for applications in health, energy, catalysis, electronics, and quantum technologies.

The research in my future group will involve theoretical and computational approaches applied to problems in materials chemistry, chemical science, physics, dynamics, optics, and biophysics. We will develop and apply cutting-edge methods — including electronic structure theory, molecular dynamics (AIMD and classical MD), and machine learning — to discover, engineer, and control materials. By gaining insight into molecular behavior and electronic structure, we aim to develop novel strategies for tuning material properties at the atomic scale.

Specific research interests include:

• Computational Materials Science and Engineering (CMSE)

• Electronic Structure Theory

• Molecular Dynamics Simulations (AIMD, MD)

• Quantum Electron Transport (e.g., nanojunctions, FET's)

• Nanoscale Device Modelling (gas/biosensing)

• Nanoplasmonics (LSPR, Tight-Binding Parameter Development for mono- and bimetallic nanoclusters)

• Computational Bioengineering and Biophysics (Ion and DNA transport)

• Quantum Chemistry and Biochemistry (non-covalent interactions, benchmarking)

• Machine Learning and Transfer Learning for modeling intermolecular interactions and materials discovery 

I envision a future where materials can be synthesized virtually and explored computationally with the same ease that digital platforms recommend content — combining physical rigor with data-driven tools to transform materials discovery.

ramgt88@gmail.com