I design and develop interactions and technologies that embrace digital and physical experiences. I am specifically interested in tools, techniques and devices that enable new interaction concepts for the augmentation and empowerment of human abilities. This includes 3D user interfaces, interaction techniques, augmented reality, mixed reality, virtual reality, ubiquitous computing, mobile devices, novel interfaces for medical imaging, multimodal systems, touch-screen interaction, and software/hardware prototyping.

The research projects are from exciting times and inspiring collaborations at different research labs and institutions, including MIT, Columbia University, University of California, KTH (Royal Institute of Technology), and Microsoft Research.I teach at Stanford University and have previously taught at Rhode Island School of Design and KTH.

Research Projects » Publications » Google Scholar »
Alex Olwal, Ph.D.
Sr Research Scientist, Google
olwal [at] acm.org
Alex Olwal

Bio-impedance sensing
Zensei is an implicit sensing system that leverages bio-sensing, signal processing and machine learning to classify uninstrumented users by their body's electrical properties.
Zensei: Embedded, Multi-electrode Bioimpedance Sensing for Implicit, Ubiquitous User Recognition
Sato, M., Puri, R., Olwal, A., Ushigome, Y., Franciszkiewicz, L., Chandra, D., Poupyrev, I., and Raskar, R.
Proceedings of CHI 2017 (SIGCHI Conference on Human Factors in Computing Systems), Denver, CO, May 6-11, 2017, pp. 3972-3985.

CHI 2017
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Zensei: Augmenting Objects with Effortless User Recognition Capabilities through Bioimpedance Sensing
Sato, M., Puri, R., Olwal, A., Chandra, D., Poupyrev, I., and Raskar, R.
UIST 2015 Adjunct Proceedings (ACM Symposium on User Interface Software and Technology), Charlotte, NC, Nov 8-11, 2015, pp. 41-42.

UIST 2015 Adjunct Proceedings
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