Jenny Han Lin

Jenny Han Lin is an Assistant Professor at the University of Utah's Kahlert School of Computing. Her research focuses on computational fabrication, particularly the intersection of computer science, textiles, and mathematics. She holds a PhD from Carnegie Mellon University (2024) and a B.E. from MIT, dual-degree in Computer Science and Molecular Biology. Prior to her current role, she was a postdoctoral scholar under Cem Yuksel at the University of Utah, and advised by James McCann during her PhD.

Her research interests include algorithmic textiles, robotic fabrication, and mathematical modeling of knitting/crochet processes. Notable work includes applying knot theory to formalize knit object equivalence and developing machine knitting compilers. She actively mentors students interested in graphics, textiles, and mathematical applications in fabrication.

Recent publications emphasize textile automation and fabrication planning, with applications in both robotics and computer graphics. Her work on Artin Braid Group representation for knitting machines received recognition as a finalist for the Best Conference Paper at ICRA '21.

Jenny has contributed to academic service through roles like organizing SIGBOVIK (a satirical conference fostering early academic writing) and running TechNights STEM outreach. She has co-chaired the SIGBOVIK organizing committee (2019-2022) and developed educational materials for algorithmic textiles through guest lectures at CMU and UW.