[Access Lunch] Thursday 11/14: Hernisa Kacorri on " Teachable Machines in Accessibility"

[Cole Gleason]

Hi everyone!

Join us tomorrow for a talk from Dr. Hernisa Kacorri from University of
Maryland, College Park!

Date: Thursday, November 14, 2019
Time: 12:00PM- 1:00PM
Room: NSH 1109

*Also, Dr. Kacorri has time to meet tomorrow afternoon after the talk. If
you would like to meet with her, please let me know and I will schedule it!*

Title: Teachable Machines in Accessibility
Abstract: How can accessibility research leverage advances in machine
learning and artificial intelligence with limited data? We argue that
teachable machines can empower accessibility research.  By explicitly
providing a few pertinent training examples, we can enable individuals with
disabilities to attune machine learning systems to their idiosyncratic
characteristics and environment. We demonstrate this concept with a
concrete example: teachable object recognizers trained by and for blind
users. Further, we discuss open challenges in designing and building
teachable machines: perception of machine training by non-experts and
inaccessibility of the labeling process.

[image: image.png]

About the speaker: Hernisa Kacorri is an Assistant Professor in the College
of Information Studies and holds an affiliate appointment in the Computer
Science and the Human-Computer Interaction Lab at University of Maryland,
College Park. She received her Ph.D. in Computer Science in 2016 from The
Graduate Center at City University of New York, and has conducted research
at National and Kapodistrian University of Athens, IBM Research-Tokyo,
Lawrence Berkeley National Lab, and Carnegie Mellon University. Her
research focuses on data-driven technologies that address human challenges,
faced due to health or disability, with an emphasis on rigorous, user-based
experimental methodologies to assess impact. Hernisa is a recipient of a
Mina Rees Dissertation Fellowship in the Sciences, an ACM ASSETS best paper
finalist and a best paper award, and a CHI honorable mention. She has been
recognized by the Rising Stars in EECS program of CMU/MIT. Her work is
supported by NSF and NIDILRR.
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