Dr. Desney S. TanThe MIT Technology Review article Human-Aided Computing: Microsoft researchers are trying to harness untapped brain power said:
Despite all the power of computers, they are still lousy at certain simple tasks, such as recognizing faces and knowing the difference between a table and a cow. Now researchers at Microsoft are trying to tap into some of the specialized and often subconscious computing power in the human brain, and use it to solve problems that have so far been intractable for machines.
Desney Tan, a researcher at Microsoft Research, and Pradeep Shenoy, a graduate student at the University of Washington, have devised a scheme that uses electro-encephalograph (EEG) caps to collect the brain activity of people looking at pictures of faces and nonfaces, such as horses, cars, and landscapes. The pair found that even when the subjects’ objective wasn’t to distinguish the faces from the nonfaces, their brain activity indicated that they subconsciously identified the difference. The researchers wrote software that churns through the EEG data and classifies faces and nonfaces based on the subjects’ response. When a single person viewed an image once, the system was able to identify faces with up to 72.5 percent accuracy. Results were even better using data from eight people who had viewed a particular image twice: accuracy jumped to 98 percent.
Desney S. Tan, Ph.D. is
Researcher in the Visualization and Interaction Group at Microsoft
Research. He also holds an affiliate faculty appointment in the
Department of Computer Science and Engineering at the University of
His research interests include Human-Computer Interaction and Brain-Computer Interfaces. Specifically, he spends most of his time understanding and building applications for large displays, multiple device systems, as well as wearable brain imaging devices. However, he is a somewhat schizophrenic researcher and has worked on projects in many other domains.
Desney coauthored Using Job-Shop Scheduling Tasks for Evaluating Collocated Communication, FacetMap: A Scalable Search and Browse Visualization, An Exploration of User Interface Designs for Real-time Panoramic Photography, Large Displays Enhance Optical Flow Cues and Narrow the Gender Gap in 3D Virtual Navigation, Physically Large Displays Improve Performance on Spatial Tasks, An Evaluation of Extended Validation and Picture-in-Picture Phishing Attacks, and Using a Low-Cost Electroencephalograph for Task Classification in HCI Research. Read his full list of publications!
Desney earned his Bachelor of Science in Computer Engineering from the University of Notre Dame in 1996, after which he spent a couple of years building bridges and blowing things up in the Singapore Armed Forces. He later returned to Carnegie Mellon University, where he worked with Randy Pausch in his Stage 3 Research Group and earned his PhD in Computer Science in 2004. His thesis was Exploiting the Cognitive and Social Benefits of Physically Large Displays.
Read Teaching computers to read minds.