Seminar: Enhancing Collective Programming: Real-time Analysis of Human Behavior in Computing Tasks at Scale
Yan Chen
Assistant Professor, Computer Science
Programming with Intelligent Machines & Environments Lab (PRIME)
Virginia Tech
Friday, November 15, 2024
2:30 - 3:45PM
3100 Torgersen Hall
Abstract
Programming and data science tasks are increasingly collaborative endeavors, yet barriers in communication and coordination continue to challenge effective learning and development. In this talk, I will present three innovative systems that address these challenges by leveraging the interplay between computing tasks and human cognition: 1) VizProg, a visualization system that helps instructors identify student misconceptions in real-time by mapping coding trajectories in 2D space (CHI 2023 Best Paper Honorable Mention), 2) VizGroup, an AI-assisted event-driven system that guides instructors' attention to critical issues by analyzing group discussions and coding activities in real-time (UIST 2024), and 3) SemanticOn, a no-code automation development system that bridges the gap between user intent and computational tasks through intuitive interactions (UIST 2022 Best Paper Honorable Mention). These systems demonstrate how intelligent visualization and interaction techniques can transform programming from an often frustrating experience into a fluid, collaborative endeavor. Looking ahead, I envision a future where human-AI collaboration in programming naturally emerges through adaptive systems that maintain users in their optimal flow state while fostering genuine fulfillment in collective problem-solving.
Biography
Yan Chen is an Assistant Professor of Computer Science at Virginia Tech where he directs the Programming with Intelligent Machines & Environments Lab (PRIME) PRIME Logo. Yan is active in the Human-Computer Interaction (HCI) research community. His research spans programming support tools, learning at scale, real-time data analysis, and CS education. His work has been published at top HCI conferences, including ACM CHI, UIST, and CSCW. He received the Best Short Paper award at VL/HCC 2020, the Best Paper at L@S 2024, and the Best Paper Honorable Mention Award at CHI 2023, and UIST 2022. Yan was a Postdoctoral Fellow at the University of Toronto. He received his Ph.D. degree from the University of Michigan, and BS and MS degrees in Applied Math and Electrical & Computer Engineering from the University of Colorado, Boulder.