Dana Ballard Memorial Symposium

On Monday May 20th a memorial symposium for Dana Ballard will be held at the University of Texas at Austin. This event will serve as a remembrance and celebration of the life and scientific work of Dr Dana Ballard (1946–2022).

Dana Ballard was a pioneer in the study of computer vision, neural computation, human vision and motor coordination, and robotics. As part of the IEEE International Conference on Development and Learning (ICDL) 2024, we will host a morning seminar session celebrating Ballard’s research with presentations by speakers who collaborated with Ballard or were inspired by his work.

Invited Speakers: Rajesh Rao, Jochen Triesch, Chen Yu, Virginia de Sa, Constantin Rothkopf, Janneke Jehee, Ruohan Zhang, Jeff Pelz

ICDL registration is not required for attendance, but we ask that all attendees RSVP via the google form link below by March 1, 2024

Live stream link is available below for those unable to attend. For any questions please contact chen.yu@austin.utexas.edu, brian.sullivan@bristol.ac.uk, and saraschroer@utexas.edu


Biography

Born in Holyoke, MA in 1946, Dana Ballard grew up in the Bahamas and had a colourful childhood before traveling to the United States to study at the Massachusetts Institute of Technology for a BSc in Aeronautics & Astronautics in 1967. This was followed by an MSc in Information & Control Engineering from the University of Michigan in 1970. He received a Ph.D. in Information Engineering at the University of California at Irvine (1974). Ballard joined the faculty in Computer Science at the University of Rochester in 1975 and subsequently at the University of Texas at Austin (2006-2022). As a teacher and supervisor Dana was famous for his sense of humour, wide ranging knowledge, creativity, and desire to give students both theoretical and applied experience.

Ballard made significant contributions to computer vision, particularly in the development of algorithms and models for visual recognition and tracking. Together with Christopher Brown in 1982, he authored the influential textbook "Computer Vision", the first of its kind. Ballard went on to make further contributions in computer vision and cognitive science, including developing theories around "predictive coding" (with Rajesh Rao) and "just-in-time visual computation" (with Mary Hayhoe). These ideas have played a crucial role in understanding how the brain processes complex information within the constraints provided by real world tasks. Dana Ballard also worked on computational models of motion control initially in robotic and computer vision and later applied to human movement. Ballard wrote two texts detailing principles of computation and information processing in human sensation and cognition entitled ‘An Introduction to Natural Computation’ (1999) and ‘Brain Computation as Hierarchical Abstraction’ (2015).

Schedule & Live stream

The memorial symposium will start at 8:45am on May 20th, 2024. You may find the full schedule below. If you are not able to attend in-person, you may attend virtually through this live stream link.

Time

    Events

Speakers

08:45 - 09:00         Opening Remarks Peter Stone
09:00 - 09:20         From Active Vision to Active Predictive Coding or: How Rajesh Rao
        I learned from Dana to stop worrying and love the brain
09:20 - 09:40         Embodied Statistical Learning Chen Yu
09:40 - 10:00         Embodied Intelligence and Learning Ruohan Zhang
10:00 - 10:20         Vision and Learning in Humans and Machines Virginia de Sa
10:20 - 10:50

Break

10:50 - 11:10         Uncertainty in Visual Decision-making Janneke Jehee
11:10 - 11:30         Learning to See without Supervision Jochen Triesch
11:30 - 11:50         Open Questions in Animate Vision Constantin Rothkopf
11:50 - 12:00         A Photographic Remembrance of Dana Jeff Pelz

Speakers

Rajesh Rao | University of Washington, USA | From Active Vision to Active Predictive Coding or: How I learned from Dana to stop worrying and love the brain
Chen Yu | The University of Texas at Austin, USA | Embodied Statistical Learning
Ruohan Zhang | Stanford University, USA | Embodied Intelligence and Learning
Virginia de Sa | University of California, San Diego, USA | Vision and Learning in Humans and Machines
Janneke Jehee | Radboud University, Nijmegen, Netherlands | Uncertainty in visual decision-making
Jochen Triesch | Frankfurt Institute for Advanced Studies, Germany | Learning to See without Supervision
Constantin Rothkopf | Technical University of Darmstadt, Germany | Open questions in animate vision
Jeff Pelz | Rochester Institute of Technology, USA | A photographic remembrance of Dana

ICDL 2024

This event is part of the IEEE International Conference on Development and Learning (ICDL) 2024. If you are intersted in attending the main conference, you may register here