9/17/2024 Bruce Adams
CS professor Jule Schatz is the principal investigator for the Illinois portion of the NSF-funded Break Through Tech AI Program , which equips undergraduates with the skills needed to thrive in the fast-evolving AI field.
Written by Bruce Adams
Cornell Tech, in collaboration with Hofstra University and the University of Illinois Urbana-Champaign, seeks to expand its proven Break Through Tech AI Program which is designed to equip underserved undergraduate students with the skills needed to thrive in the fast-evolving fields of artificial intelligence (AI) and machine learning (ML). The NSF has issued a continuing grant of $1.3 million for the Collaborative Research: CUE-T: Expanding the undergraduate AI talent pipeline by democratizing access to instructional capabilities across institutions of higher education (IHEs) project.
Grainger College of Engineering Siebel School of Computing and Data Science professor Jule Schatz is the principal investigator for the Illinois portion of the program. She explains, “My mentor, Colleen Lewis, introduced me to the organization back in early 2024 and asked if I would be interested in leading the Illinois portion. Having a lot of interest in this space, I quickly said yes.”
The AI Program is a virtual, one-year extracurricular experience for students, usually in their second undergraduate year, with required coursework in coding. Participants are equipped with the skills needed to secure a job in the fastest-growing areas of tech: data science, artificial intelligence (AI), and machine learning (ML). Cornell University presents them with a certificate upon completion.
Schatz says, “Illinois ran and will now continue to run the summer portion of the program for a cohort of around 60 students. In this portion, the students learn machine learning foundations through online material and a synchronous weekly 3-hour lab. At the end of that, they go onto working in groups on industry provided machine learning problems. During this whole process they receive mentorship and interview/job prep from industry professionals.”
This NSF project focuses on scaling up the summer "ML Foundations'' component of the Break Through Tech AI program. This nine-week, skills-based training course is delivered by faculty and graduate students from newly established Instructional Hubs at various institutions. The expansion will involve recruiting five new Instructional Hubs, training instructors through a "Train the Trainer" program, and delivering synchronous lab sessions to ensure students gain practical, industry-relevant skills. Schatz notes participating students “get their foot in the door early with the foundation over the summer. They also build valuable relationships and connections with each other and the instructors.” This past summer, 93% of participating students at the Illinois hub reported, “I feel like I belong in Data Science, Machine Learning, or AI,” and 98% reported, “I believe that my lab instructor (Schatz) has had a lasting effect on my development as a student.”
Schatz says, “One thing we focused on with the students was building confidence and communication skills. We did a lot of group work beyond the technical ML skills. I feel that a barrier for many students in computer science is not knowing the vocabulary of advanced topics. Once they know how to talk about the topics, they can start joining the conversations while continuing to learn more. We give them the tools and knowledge to start their ML journey.”
By the end of the three-year grant period, the program aims to serve 1,500 students annually, significantly enhancing the diversity and readiness of the STEM workforce. This project will contribute to the field by providing a scalable model for inclusive AI/ML education and generating valuable data on the effectiveness of distributed instructional hubs in democratizing access to cutting-edge AI education.