AI-Guided Material Discovery: Unsupervised Learning and Data Science for Safer, High Performance Material Discovery
Join us to learn about how to use cutting edge GPU infrastructure to solve real world material discovery problems with AI and unsupervised machine learning.
Project description
Our lab in the Department of Materials Design & Innovation (MDI) is building an AI-driven pipeline to discover safer, high-performance materials for biomedical applications. This project is part of our effort on AI-driven Discovery of Safe, High-Performant Monomers for Biomedical Applications and supports an ongoing collaboration with UB’s School of Dental Medicine. We already have a PhD student developing advanced reactive machine learning molecular dynamics (AI-driven simulations) and a co-design workflow that will be used to screen thousands of candidate monomers. Your role as an ELN undergraduate researcher will be to help “make sense” of the data feeding this pipeline and drive automated decision making using modern unsupervised machine learning and AI tools.
Project outcome
By the end of the project, the student will produce (i) a set of well-documented, reproducible Jupyter notebooks and Python workflows for unsupervised learning and data visualization, (ii) contributions to an open-source GitHub repository that implements these tools on our in-house materials dataset, and (iii) a succinct written report and/or ELN poster summarizing methods, results, and key insights for a non-specialist audience.
Project details
| Length of commitment | About a semester |
| Start time | Anytime |
| In-person, remote, or hybrid? | Hybrid |
| Level of collaboration | Small group project (2-3 students) |
| Benefits | Research experience |
| Who is eligible | Juniors and Seniors with experience in calculus, linear algebra, and Python programming |
Core partners
- Dr. Sivaraman's lab at UB
- UB School of Dental Medicine
- National lab and industry partners such as NVIDIA
Project mentor
Ganesh Sivaraman
Assistant Professor
Materials Design and Innovation
Phone: 716-645-5405
Email: ganeshsi@buffalo.edu
Start the project
- Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
- After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.)
Preparation activities
Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. After you’re approved to begin the project, your mentor will send the relevant materials. Please reference this when you get to Step 2 of the Preparation Phase.
Review these two courses
Keywords
artificial intelligence, machine learning, material discovery, python, github