John Morrisett
Cornell University, NY·Education Research
Demand for people trained in artificial intelligence and machine learning is growing quickly. Access to high-quality, hands-on AI education is still uneven across colleges, and expanding it means finding scalable ways to teach practical skills.
- Fields
Education Research
Computer Science
- Topics
AI education
machine learning education
computer science education
- Grants
- 1 known grant, through Dec 2027
What they work on
- Recruit five new Instructional Hubs at partner institutions to deliver the nine-week ML Foundations course of the Break Through Tech AI Program.
- Train faculty and graduate student instructors through a "Train the Trainer" program and deliver live lab sessions that build practical machine learning skills.
- Evaluate how effectively a distributed network of instructional hubs widens participation in AI education, while scaling to 1,500 students per year.
More about the research
Working with Hofstra University and the University of Illinois, Cornell Tech aims to scale up the ML Foundations part of its Break Through Tech AI Program. This nine-week, skills-based course is taught by faculty and graduate students at Instructional Hubs based at various institutions. The project plans to recruit five new hubs, prepare their instructors through a "Train the Trainer" program, and run live lab sessions focused on industry-relevant skills. The goal is to double the number of students served and reach 1,500 students a year by the end of three years. The project will also collect data on how well a distributed network of teaching hubs works for widening participation in AI education.
Why it matters
A tested, scalable model for teaching machine learning through partner institutions could let more colleges offer practical AI training. That could prepare more undergraduates for AI and ML careers. The data on distributed instructional hubs could guide other programs trying to broaden access to technical education.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Jule Schatz
University of Illinois Urbana-Champaign, IL·Education Research
Scale up the nine-week ML Foundations course of the Break Through Tech AI Program by recruiting five new Instructional Hubs at partner institutions.
Sandra Clinton
University of North Carolina at Charlotte, NC·Education Research
Test whether the benefits of the PROGRESS mentoring program extend to undergraduate women from multiple underrepresented groups and to women with intersectional identities, using a longitudinal experimental design.
Fan Wu
Tuskegee University, AL·Computer Science
Develop Project ACE training that combines machine learning and cybersecurity within cyberinfrastructure, teaching secure design and ML defenses against modern cyber threats.
The school
Cornell University: 37 labs on PI Pages, $1.6B a year on research, 537 research doctorates a year.
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