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UCSD Receives $3.4 Million for Graduate Training in Vision and Learning in Humans and Machines

San Diego, CA, Nov. 24, 2003 -- Researchers at the University of California , San Diego (UCSD) have been awarded a $3.4 million grant from the National Science Foundation (NSF) to establish an interdisciplinary program to train graduate students in the areas of human learning, human vision, computer vision, and machine learning. The grant, titled "Vision and Learning in Humans and Machines," is funded through the NSF's IGERT (Integrative Graduate Education and Research Training) program and will offer two-year fellowships to approximately 15 new students per year. The fellowships will be available to U.S. citizens, and will include a $27,500 annual stipend, as well as tuition and fees. This highly competitive "training" grant is unique at NSF, which primarily offers research-oriented funding.

This interdisciplinary program is intended to train a new generation of scientists and engineers who are as equally versed in the mathematical and physical foundations of computer vision as they are in the biological and psychological fields of natural vision and learning. "The intellectual merit of this proposal is its focus on creating novel interactions between the four areas of computer and human vision, and human and machine learning. We believe these areas are intimately intertwined, and that the synergy of their simultaneous study will lead to breakthroughs in all four domains," said Gary Cottrell, principal investigator and professor of computer science at UCSD's Jacobs School of Engineering.

According to Cottrell: "While there have been tremendous advances in computer vision and computational learning, current computer vision and learning systems for many applications (such as face recognition) are still inferior to the visual and learning capabilities of a toddler. Meanwhile, great strides in understanding visual recognition and learning in humans have been made with psychophysical and neurophysiological experiments. The time is ripe to apply our knowledge of human vision to the application of computer vision algorithms. Simultaneously we believe that the consideration of why vision is difficult for computers can give great insight to experimentalists examining the human and animal visual systems."

One of the grant's main criteria was that it had to be innovative. To answer this call, Cottrell and his UCSD co-principal investigators - Jacobs School computer science professor David Kriegman, Karen Dobkins (Psychology), Virginia de Sa (Cognitive Science) and Geoff Boynton (Salk Institute) - proposed an intensive two-week boot camp for new fellows beginning in September 2004 that will run Monday through Saturday from 9:00 a.m. to midnight . The workshops will allow the graduate students to learn from faculty and work on various topical projects.

In addition to the boot camp component, Cottrell and his colleagues have designed two new courses for the program's participants: one that combines human and computer vision, and another that combines human and machine learning. Modeled after the interdisciplinary cognitive science Ph.D. program led by Cottrell, the Vision and Learning in Humans and Machines program will require fellows to have a primary and secondary area from among the four areas of concentration (human learning, human vision, computer vision, and machine learning). Finally, as part of the grant, an international conference of these topics will be held at UCSD in the near future.

The application process for the IGERT-funded fellowships will run in parallel to the regular admissions process to UCSD. Students applying for admission to the departments that are participating in the grant (Psychology, Cognitive Science and CSE) who are interested in participating in the IGERT will be required to write a separate statement of purpose.

Troy Anderson, tdanderson@ucsd.edu, 858-822-3075