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heyitsdipu/README.md

Hi, I'm Diptesh Gayen

Postdoctoral Researcher | PhD in Physics | Computational Chemistry

Profile views


About Me

I am a computational materials scientist with a PhD in Physics, working at the interface of atomistic simulation, machine learning, and materials modeling.

My current research focuses on machine-learning interatomic potentials for polymer and soft-matter systems. I am especially interested in graph neural networks, equivariant models, generative models, and data-driven approaches for next-generation materials discovery.

class DipteshGayen:
    def __init__(self):
        self.pronouns = "He/Him"
        self.background = ["Physics", "Materials Science", "Computational Modeling"]
        self.interests = [
            "Enhanced Samplng",
            "Free energy calculation",
            "Machine-Learning Interatomic Potentials",
            "Atomistic Simulations",
            "Polymer and Soft-Matter Systems",
            "Graph Neural Networks",
            "Generative Models for Materials",
            "Next-Generation Materials"
        ]
        self.motto = "Play fearlessly. Play bold."

Current Focus

  • Applying machine-learning interatomic potentials for polymer and biosystems.
  • Deepening my understanding of graph neural networks, equivariant architectures, and generative models
  • Exploring data-driven workflows for atomistic modeling and materials discovery
  • Building research code for simulations, analysis, and machine-learning workflows

Research Interests

  • Free energy perturbation method
  • Machine-learning interatomic potentials
  • Force-field development
  • Polymer and soft-matter modeling
  • Graph neural networks for materials
  • Generative models for molecular and materials systems

Collaboration

I am open to collaborations in:

  • MLIP development
  • Atomistic machine learning
  • Polymer and soft-matter simulations
  • Data-driven materials modeling
  • Computational chemistry and force-field development

Tech Stack

Programming

Scientific Computing and Data Analysis

Machine Learning

Atomistic Simulation and Electronic Structure

Machine-Learning Interatomic Potentials

Tools


Selected Links


Beyond Research

Outside research, I enjoy karate, badminton, hiking, reading, and listening to philosophical discussions.

I am interested in spirituality in the sense of understanding the relationship between the self and the universe. I follow Advait Vedanta, or non-duality, which points toward the absence of separation between the individual self and the whole.

For a serious introduction to this perspective, I recommend the works of Acharya Prashant.


GitHub Activity

GitHub Streak


Play fearlessly. Play bold.

Pinned Loading

  1. from-smiles-to-ml from-smiles-to-ml Public

    In this series of notebooks, I have explored the concepts of smiles, descriptors, fingerprints, and SMILE Tokenizer

    Jupyter Notebook

  2. polymer-informatics polymer-informatics Public

    Jupyter Notebook

  3. machine-learning-force-field-dialanine machine-learning-force-field-dialanine Public

    Development of machine learning force field for Dialanine

    Jupyter Notebook