Industry Affiliates Meeting

November 30, 2018

1:30 – 5:30 pm

Click here to view poster abstracts

Click here to view photos from poster session

Background Each year the Stanford Center for Image Systems Engineering (SCIEN) holds an annual meeting for its’ Industry Affiliate Member companies. The talks introduce new Stanford faculty who are advancing imaging science and technology.  The poster presentations introduce postdoctoral researchers and graduate students who are working in computational imaging with expertise in image systems engineering, including optics, sensors, processing, machine learning, displays and human perception (Information about previous meetings can be found on our website:  20152016 and 2017).

Registration: Each member company receives two complimentary seats for the meeting. Please contact your company’s SCIEN coordinator for details. Otherwise, registration for SCIEN Industry Affiliate Members begins now.  Non-SCIEN member companies will be able to register beginning November 20. Academic members (Stanford faculty/students) may begin registering on November 24. Seating is limited an hence registration will be closed once we meet the maximum capacity of our venue.

Program

TimeTitleSpeaker
1:45 - 2:15 pmDesigning efficient hardware accelerators for imaging, vision and machine learning
(Abstract)
Professor Priyanka Raina
Department of Electrical Engineering
1:30 - 1:45 pmIntroductionProfessor Bernd Girod, Faculty Co-Director
Professor Gordon Wetzstein, Faculty Co-Director
Dr. Joyce E. Farrell, Executive Director
2:15 - 2:45 pmBroadening and Deepening the Role of Artificial Intelligence in Computational Neuroscience
Abstract
Professor Dan Yamins
Department of Psychology and Computer Science (courtesy)
2:45 - 3:15 pmInside Out: In-situ visualization of chemical and biological processes with nanometer-scale resolution
(Abstract)
Professor Jennifer Dionne
Department of Materials Science and Engineering
3:15 - 5:30 pmPoster Presentations
(snacks and food provided)
ostdoctoral scholars and graduate students