📍 Hyderabad, India | ✉️ anish.saheb41@email.com
I'm a quantum chemist with a Ph.D. from IIT Bombay and global postdoctoral research experience (USA, Germany), now pivoting into data science and machine learning. I bring 8+ years of experience solving complex scientific problems using Python, C++, SQL, and GPU programming. Now, I'm passionate about leveraging data analytics and AI/ML to drive innovation, decision-making, and scientific discovery across industries.
- Programming: Python, SQL, C++, Fortran, Bash, R
- ML & Data: Pandas, NumPy, Scikit-learn, RDKit, Matplotlib, Power BI
- Computational Methods: Coupled Cluster, Density Functional Theory, Quantum Monte Carlo, Molecular Dynamics
- Simulation & Tools: Gaussian, ORCA, Q-CHEM, Gromacs, VMD, Autodock
- Cloud/Systems: Conda, HPC clusters, CUDA (GPU), Jupyter
- Responsible for the development of an automated Python-based CADD pipeline for virtual screening, molecular docking, and cheminformatics scoring to accelerate structure-based drug discovery (SBDD)
- Leading the development of scalable algorithms for predictive modeling of molecular interactions, improving early-stage drug screening efficiency.
- Built a simulation pipeline towards the accurate quantification of Protein-ligand interaction via the usage of hybrid QM/MM methodologies
- Led the development of methodologies for accurate excited-state computations and associated properties
- Wrote scientific workflows in Python and C++, optimized on GPU nodes
- Developed QM-based methodology towards the efficient implementation of Phaseless Auxiliary Field Quantum Monte Carlo (ph-AFQMC)
- Worked on data generation pipelines for high-performance quantum models
- Ph.D., Chemical Physics | Indian Institute of Technology Bombay (August 2023)
- M.Sc., Chemistry | National Institute of Technology Rourkela (May 2018)
- B.Sc., Chemistry | Jadavpur University Kolkata (May 2016)
- 🥇 Humboldt Fellowship for Postdocs – 2024
- 🏅 Best Poster – QSCP, Poland (2022)
- 🏅 Best Poster – TCS, IISER Kolkata (2021)
- Tribedi S., Chakraborty A., Maitra R., Formulation of a dressed coupled-cluster method with implicit triple excitations and benchmark application to hydrogen-bonded systems. J. Chem. Theory Comput. 2020, 16, 6317. DOI: 10.1021/acs.jctc.0c00736
- Agarawal V., Roy S., Chakraborty A., Maitra R., Accelerating coupled cluster calculations with nonlinear dynamics and supervised machine learning. J. Chem. Phys. 2021, 154, 044110. DOI: 10.1063/5.0037090
- Chakraborty A., Tribedi S., Maitra R., A double exponential coupled cluster theory in the fragment molecular orbital framework. J. Chem. Phys. 2022, 156, 244117. DOI: 10.1063/5.0090115
- Chakraborty A., Maitra R., Fixing the catastrophic breakdown of single reference coupled cluster theory for strongly correlated systems: Two paradigms toward the implicit inclusion of high-rank correlation with low-spin channels. J. Chem. Phys. 2023, 159, 024106. DOI: 10.1063/5.0146765
- Chakraborty A., Samanta P., Maitra R., Accurate determination of excitation energy: An equation-of-motion approach over a bi-exponential Coupled Cluster theory. J. Chem. Phys. 2024, 161, 114109. DOI:10.1063/5.0221202.
- Poster: Structures and Dynamics of Molecules and Clusters (SDMC), Himachal Pradesh, India, 2019
- Poster: Mumbai Workshop on Quantum Chemistry (MWQC), IIT Bombay, India, 2019
- Talk: Diamond Jubilee Chemistry Symposium, IIT Bombay, India, 2019
- Poster: In-house Symposia, Department of Chemistry, IIT Bombay, India, 2021
- Poster: Theoretical Chemistry Symposium (TCS), IISER Kolkata, India, 2021
- Poster: 25th International Workshop on Quantum Systems in Chemistry, Physics and Biology (QSCP), Torun, Poland, 2022
- Talk: Mini-Symposium on Theoretical Physical Chemistry and Chemical Physics (MS-TPCCP), IIT Bombay, India, 2023