Collegiate Assistant Professor · Department of Computer Science · Virginia Tech
I study how people and intelligent systems learn to work well together, in classrooms, in interfaces, and across cultures.
About
For twenty years I have taught, researched, and served in higher education, first in Pakistan at the University of Sindh and the University of Mirpurkhas, and since 2023 as a Collegiate Assistant Professor of Computer Science at Virginia Tech.
My work asks how people and intelligent systems learn to work together. In computing education, that means redesigning courses so students learn how large language models work, use them with care, and reflect on what they gain and lose. In human–computer interaction, it means asking whether AI can help evaluate interfaces, and how culture shapes the interfaces we build.
I also build things students use, including DBWorkout, a gamified SQL platform, and classroom analytics that give instructors feedback without keeping video. I mentor undergraduate and graduate researchers, and I am helping develop CS 2104 as a foundation for Virginia Tech’s AI minor.
Research themes
Usability, user experience, and the evaluation of interactive systems, from university websites to classroom tools.
Explore Human–computer interactionHow people and AI systems work together: language models as simulated stakeholders, human–AI collaboration, and AI that supports human judgment.
Explore Human-centered AITesting whether large language models can find usability and accessibility problems in code and designs, and how they compare with human experts.
Explore LLM-assisted usability evaluationTeaching students to use large language models responsibly: course redesign, assessment, and evidence about how students actually use these tools.
Explore AI in computing educationHow culture, language, and accessibility shape what good design means, from culture-oriented heuristics to cross-border privacy and security literacy.
Explore Cultural and inclusive designLearning tools built and tested in real courses, including a gamified SQL platform and privacy-preserving classroom analytics.
Explore Educational technologyFeatured research
Can a language model spot what an expert would?
ActiveComparing LLM and human heuristic evaluations of code, designs, and websites, and testing how persona diversity and simulated stakeholders change the results.
Not banned, and not left to chance.
ActiveRedesigning CS 2104 so students learn how LLMs work, use them with guidance, reflect on that use, and are assessed with AI access in mind, alongside studies of how students actually use these tools.
SQL practice that pushes back.
ActiveAn open-access, gamified SQL learning platform with real-time automated feedback, a shared leaderboard, and an instructor-controlled AI hint toggle, used in CS 4604 and CS 2304.
Feedback for instructors, privacy for students.
ActiveAn AI-assisted system that combines pose estimation, gaze estimation, and LLM-based summaries to describe classroom engagement without ever retaining video. Supported by a 4-VA collaborative research grant.
Selected publications
FutureHCI ’26: Future of Human–Computer Interaction Workshop, Virginia Tech
Proceedings of the 57th ACM Technical Symposium on Computer Science Education (SIGCSE TS 2026), Vol. 2, poster paper, pp. 1299–1300
2026 ASEE Annual Conference & Exposition, Charlotte, NC
2025 IEEE Symposium on Visual Languages and Human-Centric Computing (VL/HCC), pp. 152–158
Universal Access in the Information Society, 24(4), pp. 3465–3481
* Student co-author.
Teaching
I teach through hands-on, project-based work, and I design each course so every student can take part. My courses range from data structures and databases to human–computer interaction and the senior capstone.
Fall 2023 to Fall 2026
Spring 2024 to Spring 2026
Spring 2025
Spring 2024, Fall 2025
Mentorship
71 undergraduate researchers supervised across 13 projects since 2024
News and highlights
Presented four papers at FIE 2026: how students use LLMs across computer science subfields, a study of virtual global collaboration in data analytics and machine learning education, and two work-in-progress papers on DBWorkout and on automated analysis of student engagement that preserves privacy.
A student-led paper on how well LLMs detect and fix WCAG accessibility violations in web dashboards won Best Paper at the Future of HCI workshop at Virginia Tech.
Co-led a workshop on intentional AI integration in course design, and presented lightning talks on DBWorkout, AI literacy across the disciplines, and student LLM behavior in individual and team work.
Presented our paper on teaching responsible LLM use and security awareness in a CS problem-solving course at the 2026 ASEE Annual Conference & Exposition.
Read the paperNolan Platt was one of five students chosen to represent Virginia Tech at the ACC Meeting of the Minds at Florida State University, presenting work on LLM reasoning about classroom attention.
“From Code to Collaboration: Reimagining Computing Education with Generative AI,” at the International Conference on Computing and Emerging Technologies, Quaid-e-Awam University of Engineering, Science and Technology.
Research group
Human–AI Interaction and Computing Education Lab. My research group at Virginia Tech, where undergraduate and graduate students work on human–computer interaction, AI, and computing education.