Photo of David Stork

David G. Stork

Title: Fellow
Research Areas: Computational Sensing and Imaging

Technical invention is like art, one of the great domains of creativity in the 21st century, and Silicon Valley is the modern equivalent of Florence in the Renaissance. Everyone in Silicon Valley—from gas station attendants to startup CEOs—admires and supports our unique and visionary culture of invention. If you have the drive and technical expertise, you are inevitably drawn to be part of this unique culture and change the world for the better.

At Rambus, I’ve helped my group invent electro-optic imaging systems, such as our binary pixel sensors and ultra-miniature computational imagers and sensors. This last is a new class of ultra-miniature sensors, which rely on special optical gratings affixed to photodetectors. The raw signals captured by the photodetectors do not resemble a traditional image in any way, but contain enough information that a final digital image can be computed. In short, the sensed signals are not an image for humans to see, but instead for computers to “see.” This overall approach is representative of the new paradigm of computational imaging.

I deeply enjoy the task of identifying technical problems or opportunities, solving hard theoretical problems and translating those results into practical devices and real-world services that make a difference in the world. Pondering interdisciplinary problems and the intersections of apparently disparate disciplines, e.g. optics and computing, hardware and software, computer vision and art, speech recognition and computer vision etc. I’m especially fascinated by artificial intelligence generally and the problems of vision (by humans and machines) specifically, including recognizing patterns—a general task of extraordinary complexity and depth but which humans take for granted.

Education

  • BS, Physics, Massachusetts Institute of Technology (MIT)
  • MS and PhD, Physics, University of Maryland, College Park

Books and research Papers

  • Pattern classification (2nd ed.) by R. O. Duda, P. E. Hart and D. G. Stork (Wiley), 2000
  • “Lensless Ultra-miniature Imagers Using Odd-symmetry Spiral Phase Gratings,” in Proceedings of the 2013 Computational Optical Sensing and Imaging (COSI): Patrick R. Gill and David G. Stork
  • “Lensless ultra-miniature CMOS imagers and sensors,” in Proceedings of SensorComm 2013: David G. Stork and Patrick R. Gill [best paper award]

Past Speaking Engagements

  • “Lensless Ultra-miniature Computational Sensors and Imagers,” Colloquium, University of Washington, Seattle, WA, November 2013
  • “Lensless Ultra-miniature Computational Sensors and Imagers,” Distinguished Lecture, Department of Computer Science, Northwestern University, Evanston, IL, October 2013
  • “Lensless Ultra-miniature CMOS Imagers and Sensors,” Plenary lecture, SensorComm 2013, Barcelona Spain, September 2013