CC
Chandra Chowdhury
Indian Institute of Technology Kharagpur, Indian Institute of Technology Madras, Indian Association for the Cultivation of Science, Visva-Bharati University, University of Milano-Bicocca
Research areas: Materials Science · Materials Chemistry · Machine Learning in Materials Science · 2D Materials and Applications · Advanced Chemical Physics Studies
0000-0001-9336-6041
Employment
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Indian Institute of Technology Kharagpur Assistant Professor2026 - Present
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Indian Institute of Technology Madras INSPIRE Faculty2025 - 2026
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UNIMIB Postdoctoral Fellow2024 - 2025
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CSIR-CLRI National Postdoctoral Fellow2022 - 2024
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Karlsruhe Institute of Technology Postdoctoral Fellow2019 - 2022
Education
- 2014 - 2019
- 2011 - 2013
- 2008 - 2011
Projects & Funding
Projects & funding information is unavailable.
Publications (16)
- Exploring Quantum Support Vector Regression for Predicting Hydrogen Storage Capacity of Nanoporous Materials Save
- Machine Learning and Bayesian Optimization in the Analysis of Van der Waals Bilayers Save
- Predicting the HER activity of SACs on MXenes with simple features and interpretable machine learning models Save
- Quantum computing for molecular vibrational energies: A comprehensive study Save
- Transition Metal Anchored Novel Holey Boron Nitride Analogues as Single‐Atom Catalysts for the Hydrogen Evolution Reaction Save
- Quantum support vector classifier for phase diagram prediction in quinary systems Save
- Unlocking Potential Catalysts: A Machine Learning Approach with Bayesian and Regression Models Save
- Quantum simulation of small molecules for multiple applications Save
- Prediction of hydrogen storage in metal-organic frameworks: A neural network based approach Save
- Execution of a quantum algorithm for calculating energies of some quantum mechanical systems Save
- Advancing 2D material predictions: superior work function estimation with atomistic line graph neural networks Save
- DFT and machine learning guided investigation into the design of new dual-atom catalysts based on α-2 graphyne Save
- Topological data analysis enhanced prediction of hydrogen storage in metal–organic frameworks (MOFs) Save
- Exploring Hydrogen Storage Capacity in Metal‐Organic Frameworks: A Bayesian Optimization Approach Save
- Structural and Electronic Properties of Two‐Dimensional Materials: A Machine‐Learning‐Guided Prediction Save
- Unravelling the Zn‐Cu Interaction during Activation of a Zn‐promoted Cu/MgO Model Methanol Catalyst Save