Computational Modeling and Artificial Intelligence for Material Design

Artificial intelligence to predict porous materials behavior.

Seeking undergraduate researcher to work on an NSF-funded project on computational imaging and artificial intelligence supporting the design of advanced material. Experience in Python programming is required. 

Project is Not Currently Available

This project has reached full capacity for the current term. Please check back next semester for updates.

Project description

This project aims to develop computational models supporting the optimal design of material using advanced imaging and data science tools.

Students will work on:

  • Implementing novel neural networks for generating materials microstructure;
  • Integrating the network with physics-based modeling of material behavior;
  • Collaboration with PhD students to co-author scientific papers. 

Project outcome

The specific outcomes of this project will be identified by the faculty mentor at the beginning of your collaboration. 

Project details

Timing, eligibility and other details
Length of commitment 0-2 months
Start time Summer (May/June)
In-person, remote, or hybrid? Hybrid Project
Level of collaboration Individual Student Project
Benefits Stipend
Who is eligible All undergraduate students 

Project mentor

Danial Faghihi


Mechanical and Aerospace Engineering

Phone: 716) 645-1450


Start the project

  1. 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.)
  2. 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. Please reference this when you get to Step 2 of the Preparation Phase. 

Experience with at least one program language is necessary; No prior preparation is needed. 

Prerequisite skill: Python language.


mechanical and aerospace engineering, python, computational modeling, programming, artificial intelligence