Stefanie Mueller is the TIBCO Career Development Associate Professor in the MIT EECS department and a member of the Computer Science and Artificial Intelligence Laboratory. In her research, she develops novel hardware and software systems that advance personal fabrication technologies. Stefanie publishes her work at the most selective HCI venues CHI and UIST and has received several best paper and honorable mention awards. Stefanie was named a Forbes 30 under 30, an MIT Technology Review Innovator under 35 (TR35), and has received a Sloan Fellowship, Microsoft Research Fellowship and NSF CAREER Award. Stefanie has served as both an ACM CHI 2023 paper chair as well as an ACM UIST 2020 paper chair. Stefanie has been an invited speaker at universities and research labs, such as Harvard, Stanford, UC Berkeley, CMU, Microsoft Research, Disney Research, and Adobe Research.
Stefanie directs the HCI Engineering group at CSAIL and is actively recruiting Postdocs, PhD students, and interns interested in helping to kickstart this new lab. Interested Postdocs can email her directly. For a PhD position please apply through MIT's PhD admission page.
G-ID is a method that utilizes the subtle patterns left by the 3D printing process to distinguish and identify objects that otherwise look similar to the naked eye.
The focus of the HCI CoR is inventing new systems and technology that lie at the interface between people and computation, and understanding their design, implementation, and societal impact.
MIT CSAIL team creates a special program at the MIT Museum, featuring talks and new holographic sculptures. It links CSAIL’s color-changing research to MIT’s holographic history.
The FabObscura system helps users design and print barrier-grid animations without electronics, and can help produce dynamic household, workplace, and artistic objects.
MIT CSAIL researchers developed SustainaPrint, a system that reinforces only the weakest zones of eco-friendly 3D prints, achieving strong results with less plastic.
“InteRecon” enables users to capture items in a mobile app and reconstruct their interactive features in mixed reality. The tool could assist in education, medical environments, museums, and more.
