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Directorate for Computer and Information Science and EngineeringNSF · NSFNSF

Collaborative Research: CUE-T: Expanding the undergraduate AI talent pipeline by democratizing access to instructional capabilities across institutions of higher education (IHEs)

Krishnan Pillaipakkamnatt·Hofstra University, NY·2025–2027·ACTIVE
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INSTITUTION

Hofstra University, NY

PRINCIPAL INVESTIGATOR

Krishnan Pillaipakkamnatt

FUNDING

$273K

YEAR

2025

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Abstract

Cornell Tech, in collaboration with Hofstra University and the University of Illinois, seeks to expand its proven Break Through Tech AI Program designed to equip all undergraduate students with the skills needed to thrive in the fast-evolving fields of artificial intelligence (AI) and machine learning (ML). By expanding participation in high-quality AI education through a network of Instructional Hubs, this project aims to double the number of students served annually. This new generation of AI leaders will help ensure advances in responsible AI and promote US competitiveness in this exploding technical field. This project focuses on scaling up the 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. By the end of the three-year grant period, the program aims to serve 1,500 students annually, significantly enhancing the readiness of the STEM workforce. This project will contribute to the field by providing a scalable model for AI/ML education and generating valuable data on the effectiveness of distributed instructional hubs in expanding participation in cutting-edge AI education. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Directorate for Computer and Information Science and EngineeringImprov Undergrad STEM Ed(IUSE)EducateAINAIRR-Nat AI Research Resourcethrougheducationtrainintelligenceuniversitycomponentensurebreakworkforceannuallyworthyreflectsmeritnewlyfieldsdistributedevolvingmachineeffectiveness

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