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SUSANTA DAS, PhD

   THEORY AND COMPUTATIONAL CHEMIST

Research Experiences :

• Developed an efficient workflow combining Quantum Mechanics (QM) and Machine Learning (ML) to calculate spectroscopic properties (Nuclear Magnetic Resonance/Collisional Cross Section) for the structure elucidation of metabolites, contributing to Precision medicine innovation.

• Developed a novel approach based on spectroscopic properties aimed at finding global minima from the conformational ensemble, significantly aiding in metabolite structure elucidation.

• Developed QM/MM docking code (EnzyDock) for studying enzyme catalysis.

• Conducted research on homology modeling of proteins, utilizing computational methods to predict protein structures based on evolutionary relationships with known structures.

• Performed QM/MM simulations of biomacromolecules to investigate their properties and behavior in complex physiological environments.

• Conducted studies on heterogeneous catalysis of Nano metal clusters employing Density Functional Theory (DFT) and ab initio Molecular Dynamics (MD) methods to investigate the structure, properties, and reaction mechanisms involved.

• Explored the activation of small molecules on nanoclusters, investigating the catalytic properties and mechanisms using DFT and ab initio MD methods.

• Utilized Coupled Cluster (CC) methods to study the structure and properties of molecular clusters, gaining insights into their behavior and interactions.

Academic Qualification

2010 - 2015 : Ph.D. (Computational Chemistry), Csir - National Chemical Laboratory (NCL), India

2007 - 2009 : M.Sc. (Chemistry), Visva Bharati Central University, India

2004 - 2007 : B.Sc. (Chemistry Hons.), University of Burdwan, India