About Gierad

Gierad is a Ph.D. candidate at the School of Computer Science at Carnegie Mellon University, where he specializes in HCI and interactive sensing. He is a Google PhD Fellow, a Swartz Innovation Fellow for Entrepreneurship, a Qualcomm Innovation Fellow, an Adobe Research Fellow, and a Disney Research Fellow. He is also a recipient of the Fast Company Innovation by Design Award, along with 6 Best Paper Awards and Nominations at premier venues in human-computer interaction.

I'm currently on the job market, pursuing a broad search for academic and industry positions. View travel schedule.

Statements: Research × Teaching × Diversity


My research in HCI lies at the intersection of interactive systems, sensing, and applied machine learning. I design, build, and evaluate sensing technologies that greatly enhance input expressivity for users and contextual awareness for devices.

My research has spanned areas in novel sensing for mobile and wearable computing, smart environments, and the Internet of Things. I approach this work from two equally rigorous angles: 1) exploiting sensing opportunities that don't require special-purpose hardware or invasive instrumentation, and 2) inventing novel hardware to unlock unexplored sensing capabilities. Most recently, I've complemented this work with deep learning techniques, unlocking even more novel applications. I am advised by Chris Harrison at the Future Interfaces Group.

I am also Editor-in-Chief of XRDS, ACM's premiere magazine for students. I work alongside my amazing co-Editor-in-Chief Diane Golay. I am also the originator of Zensors, Inc., and Mites.io, two startups spun-off from my research.

Most people pronounce my name as "Girard" (which is fine). If you're curious, it's like "Girard" but drop the second "r". More of a "gi-rah-d". Its not a typical Filipino name.


I publish my research at premiere venues in Human-Computer Interaction. Click on each project to download papers, access supporting materials and read project-specific FAQs.

T1. Imbuing Devices with Rich Contextual Awareness

T2. Increasing Explicit Input Expressivity for Users

T3. Specific HCI Application Areas