Skip to content
View adigasuhas's full-sized avatar
🎯
Focusing
🎯
Focusing
12 followers · 55 following

Achievements

Achievement: Quickdraw

Achievements

Achievement: Quickdraw

Block or report adigasuhas

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
adigasuhas/README.md

Hi, I'm Suhas Adiga!

Twitter LinkedIn YouTube GitHub

I am a final-year MS student at the Theoretical Sciences Unit, JNCASR, working with Prof. Umesh V. Waghmare. My research focuses on applying machine learning and data-driven approaches to accelerate the discovery and design of functional materials for energy applications. I work at the intersection of first-principles methods and machine learning, with current projects spanning superconductors, thermoelectrics, and geomaterials.

I am actively exploring Universal Machine Learning Interatomic Potentials (UMLIPs) for large-scale atomistic modeling, and developing NLP-based pipelines for literature mining and automated materials dataset construction.

My Current Interests

  • Data-Driven Material Design using AI and Experiments
  • Foundational Models for Materials
  • Interpretable ML for Materials Science (ML4MS)

Languages and Tools

HTML5 Python Bash Arduino Linux pytorch GitLab Blender LaTeX TensorFlow Figma

Profile views counter

Pinned Loading

  1. Toy_Model---Superconductivity Toy_Model---Superconductivity Public

    This repository contains Python code for running a GUI to visualize Cooper pair formation in a 2D unit cell.

    Python

  2. Python-for-Materials-Science Python-for-Materials-Science Public

    This repository contains notebooks demonstrating the usage of Python libraries for Materials Science. It will be updated weekly, and expect to finish this in a span of 10 weeks.

    Jupyter Notebook

  3. Accelerating-Search-for-Superconductors-using-Machine-Learning Accelerating-Search-for-Superconductors-using-Machine-Learning Public

    This repository contains the data files and python code used for our project 'Accelerating-Search-for-Superconductors-using-Machine-Learning'

    Python