<Kalyan Kumar Dhar, Ph.D.

Computational Scientist | Catalysis | Scientific Machine Learning | Data-Driven Materials Discovery

Google Scholar • ORCID • ResearchGate • LinkedIn • Academia • Website

About Me

I am a computational scientist working at the intersection of:

• Computational Chemistry
• Heterogeneous Catalysis
• Scientific Machine Learning
• Data-Driven Materials Design
• Environmental & Water Systems

My work focuses on developing physically interpretable computational models that connect quantum simulations, reaction energetics, and machine learning for accelerated catalyst and materials discovery.

Research Vision

Quantum Simulations ↓ Reaction Energetics ↓ Descriptor Engineering ↓ Machine Learning ↓ Mechanistic Understanding ↓ Materials Discovery

Research Themes

Catalysis & Reaction Engineering

• Heterogeneous catalysis
• Surface reaction mechanisms
• Adsorption energetics
• Transition-state modeling
• Reaction network analysis

Scientific Machine Learning

• Physics-informed ML
• Descriptor-based modeling
• Explainable AI for chemistry
• Surrogate models
• Feature engineering for atomistic systems

Computational Chemistry

• Density Functional Theory (DFT)
• Electronic structure analysis
• Catalyst screening
• Charge-transfer mechanisms
• High-throughput workflows

Environmental Applications

• Sustainable catalysis
• Textile wastewater treatment
• Natural coagulants
• Water treatment technologies

Technical Skills

Programming & Data Science

• Python
• NumPy
• Pandas
• Scikit-Learn
• RDKit

Computational Chemistry

• VASP
• ASE
• LAMMPS

Visualization

• Matplotlib
• Plotly
• Seaborn

Research Workflow

DFT → Feature Engineering → Machine Learning → Prediction → Interpretation → Publication

Featured Projects

Reaction Energy Modeling Pipeline

Physics-informed ML framework for catalytic reaction pathway analysis using DFT data.

Descriptor-Based Catalyst Discovery

Machine-learning-driven catalyst screening using structural and electronic descriptors.

Textile Wastewater Treatment Analytics

Data-driven optimization of environmental treatment processes.

Charge Transfer Mechanisms

Electronic structure and charge redistribution studies in catalytic systems.

Scientific Visualization Toolkit

Publication-quality tools for:

• Heatmaps
• Volcano plots
• Reaction energy diagrams
• Correlation matrices
• Mechanistic schematics

GitHub Analytics

Contribution Activity

Research Profiles

• Google Scholar: https://scholar.google.com/citations?user=0BbshI8AAAAJ&hl=en
• ORCID: https://orcid.org/0000-0003-4265-3600
• ResearchGate: https://www.researchgate.net/profile/Kalyan_Dhar
• Academia: https://polimi.academia.edu/KaLyanDhar
• LinkedIn: https://www.linkedin.com/in/onekalyan
• Website: https://stectww.wordpress.com/kalyan-kumar-dhar-phd/

Open Science Commitment

• Reproducible computational workflows
• FAIR data principles
• Open-source scientific tools
• Transparent ML models for chemistry

Contact

📧 kalyankumar.dhar@polimi.it

Support

If my work is useful:

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Advancing catalyst discovery through interpretable scientific machine learning.