Fan Wu
Tuskegee University, AL·Computer Science
Cyberinfrastructure (CI), the computing systems, networks and data resources behind modern science, needs people skilled in both cybersecurity and machine learning (ML). Few professionals combine these skills.
- Fields
Computer Science
Education Research
- Topics
cybersecurity education
machine learning
cyberinfrastructure
- Grants
- 2 known grants, through Jun 2028
What they work on
- Develop Project ACE training that combines machine learning and cybersecurity within cyberinfrastructure, teaching secure design and ML defenses against modern cyber threats.
- Incorporate large language models and experiential learning into a scalable, adaptable cyberinfrastructure curriculum that links theory with hands-on practice.
- Build ten portable Google Colaboratory lab modules that teach machine learning on public datasets of denial-of-service, CAPTCHA-bypass and SQL injection attacks.
- Evaluate whether the hands-on labs improve students' knowledge, grades, motivation, self-efficacy and career interest, using mixed methods with surveys, focus groups and administrative data.
More about the research
Underrepresented groups have limited access to training, and teaching lags behind fast-moving tools such as large language models (LLMs). Both of the PI's projects build hands-on teaching materials for ML and cybersecurity. Both also study whether these materials help students, especially at Historically Black Colleges and Universities (HBCUs) such as Tuskegee.
Why it matters
Organizations that depend on computing systems need more workers who can defend them using machine learning. Free, browser-based labs and adaptable training could widen access to these skills, especially for students at HBCUs and other underrepresented groups. A larger, better-trained workforce could strengthen defenses against cyberattacks across science and industry.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Collaborative Research: CyberTraining: Implementation: Medium: AI and Cybersecurity Education for Cyberinfrastructure: A Hands-on Approach
NSF · Jul 2024 – Jun 2028
Collaborative Research: SaTC: EDU: Authentic Learning of Machine Learning in Cybersecurity with Portable Hands-on Labware
NSF · Sep 2021 – Aug 2027
Closest labs
Emily Lovell
University of California-Santa Cruz, CA·Education Research
Expose HBCU computer science students who have completed foundational coursework to open source career pathways through paid summer contributions to real-world open source software projects matched to their interests.
Sheikh Rabiul Islam
University at Albany, NY·Computer Science
Develop seven AI4SecureCI learning modules that teach fair and explainable AI for securing cloud cyberinfrastructure, covering topics from malware detection to adversarial attacks, and integrate them into undergraduate and graduate courses.
John Morrisett
Cornell University, NY·Education Research
Recruit five new Instructional Hubs at partner institutions to deliver the nine-week ML Foundations course of the Break Through Tech AI Program.
The school
Tuskegee University: 4 labs on PI Pages, $30M a year on research, 6 research doctorates a year.
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