Research Summary
Computational scientist specializing in nucleation kinetics, structural ordering in clathrate hydrates, and the development of machine learning tools for molecular simulations. My research integrates microsecond-scale molecular dynamics with deep learning (Variational Autoencoders, PointNet) and enhanced sampling methods (metadynamics, adaptive sampling) to decode rare-event kinetics in condensed matter. I also develop open-source tools for reaction pathway generation and ADMET property prediction.
Education
S.N. Bose National Centre for Basic Sciences, Kolkata
- Supervisor: Dr. Suman Chakrabarty
- Thesis: Nucleation Kinetics and Structural Ordering in Clathrate Hydrates
2021 — Present
S.N. Bose National Centre for Basic Sciences, Kolkata
2019 — 2021
Publications
Total citations: 24 • h-index: 3 • Google Scholar Profile
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Maity, D., Shahid, S. & Chakrabarty, S. "PathGennie: Rapid Generation of Rare Event Pathways via Direction-Guided Adaptive Sampling Using Ultrashort Monitored Trajectories." J. Chem. Theory Comput., 2025. [DOI]
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Maity, D. & Chakrabarty, S. "IceCoder: Identification of Ice Phases in Molecular Simulation Using Variational Autoencoder." J. Chem. Theory Comput., 2025. (4 citations) [DOI]
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Shahid, S., Maity, D. & Chakrabarty, S. "MTAN-ADMET: A Multi-Task Adaptive Neural Network for Efficient and Accurate Prediction of ADMET Properties." ChemRxiv, 2025. (1 citation) [DOI]
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Maity, D. & Chakrabarty, S. "Challenges in Transferable Prediction of Solvation Free Energy: A Comparative Analysis of Molecular Representations and Machine Learning Methods." Research Square, 2025. [PDF]
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Bhaumik, S.K., Maity, D., Basu, I., Chakrabarty, S. & Banerjee, S. "Efficient Light Harvesting in Self-Assembled Organic Luminescent Nanotubes." Chemical Science, 2023. (16 citations) [DOI]
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Sahoo, R., Maity, D., Shankar Rao, D.S., Chakrabarty, S., Yelamaggad, C.V. & Prasad, S.K. "Dimer-Parity-Dependent Odd-Even Effects in Photoinduced Transitions to Cholesteric and TGB Smectic-C* Mesophases." Physical Review E, 2022. (3 citations) [DOI]
Technical Expertise
Simulation
GROMACS, OpenMM, PLUMED (Advanced Metadynamics, Well-Tempered Metadynamics)
Machine Learning
PyTorch, Variational Autoencoders, PointNet, Graph Neural Networks, scikit-learn
Methods
Free Energy (FEP, TI, MBAR), Enhanced Sampling, Adaptive Path Sampling, Rare-event Kinetics
Programming
Python (NumPy, SciPy, MDAnalysis, pyscal), C/C++, Bash, SLURM / HPC
Research Experience
S.N. Bose National Centre for Basic Sciences
- Developed IceCoder, a VAE-based framework for automated ice polymorph identification from MD trajectories (JCTC, 2025).
- Created PathGennie, a direction-guided adaptive sampling tool for rare-event pathway generation (JCTC, 2025).
- Investigated solvation free energy prediction using comparative ML approaches across molecular representations.
- Co-developed MTAN-ADMET, a multi-task neural network for drug-like molecule property prediction.
- Studied nucleation kinetics and structural ordering of methane hydrates with alcohols and osmolytes.
2021 — Present
Honors & Awards
Senior Research Fellowship (SRF), Govt. of India
2023 — Present
Junior Research Fellowship (JRF), Govt. of India
2021 — 2023
References
Dr. Suman Chakrabarty
Associate Professor, S.N.B.N.C.B.S.
suman.chakrabarty@snbncbs.res.in
Reference 2
Available upon request