Team

Meet the researchers advancing AI-driven materials discovery and design

Principal Investigator

Kamal Choudhary, PhD

Assistant Professor

Joint appointments in Materials Science & Engineering, Electrical & Computer Engineering, and Data Science & AI Institute

Research Associate, National Institute of Standards and Technology (NIST)

🏆 Fellow, American Physical Society (2025)

📝 Associate Editor, Nature: npj Computational Materials

📝 Editorial Board, Scientific Data, Materials Today Communications, PRX Energy, Machine Learning: Science and Technology

📧  drkamal@jhu.edu or kchoudh2@jhu.edu
📄 Download CV
🔗 LinkedIn | Twitter/X | YouTube | Google Scholar | Spotify

PhD Students

Jaehyung Lee

Jae is a PhD student interested in the application of computational tools & methods on the atomic scale to discover novel energy materials. He has been working on developing agentic AI and generative models for materials design.

Hometown: Seoul, South Korea

Fun fact: I served 2 years of military service prior to joining Johns Hopkins!

LinkedIn: https://www.linkedin.com/in/leejaehyung/

Google Scholar: https://scholar.google.com/citations?user=6hNv7BAAAAAJ&hl=en

Charles Rhys Campbell

Status: Incoming PhD student (Starting 2026)

LinkedIn: https://www.linkedin.com/in/crhysc

Undergraduate Researchers

 

Justin Ely

Kent Zhang

Akshaya Ajith

 

Shrijani Buruganahalli

 

Join Our Team

We’re actively recruiting passionate researchers at all levels. Ideal candidates have backgrounds in:

    • Materials Science, Physics, Chemistry, or related fields

    • Computer Science, Data Science, or Machine Learning

    • Computational modeling or scientific programming

    • Strong interest in interdisciplinary research combining physics and AI

How to Apply:

    1. 📧 Email your CV/Resume to drkamal@jhu.edu
      Subject line: “Postdoc/PhD/Undergrad research application”
    2. 📺 Watch our introductory YouTube videos (Learn about JARVIS, materials informatics, and our research approach)
    3. 💻 Try these Google Colab notebooks (Get hands-on experience with our tools and datasets)
    4. Go through introductory books in materials/data science, review articles such as this one.
  1.  

The videos and notebooks ensure all applicants start with the same foundational knowledge and demonstrate your genuine interest in our research.

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