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Mathematics & Statistics

The R. Kent Nagle Lecture Series

March 12, 2020

Danielle Bassett discusses the topic of “Network Architectures Supporting Learnability”

Audience The talk is directed at a general audience and is open to the public. There is no entrance fee.
Date March 12, 2020
Time Thursday evening, 7:30pm
Place CWY 206, at USF-Tampa (For a map of the campus,
click here.)
Parking Free parking in Lots 37 and 37T.
NOTE This lecture has been CANCELLED.

Danielle Bassett

Danielle S. Bassett

Danielle Bassett

Description of the Talk

Human learners acquire not only disconnected bits of information, but complex interconnected networks of relational knowledge. The capacity for such learning naturally depends on the architecture of the knowledge network itself. I will describe recent work assessing network constraints on the learnability of relational knowledge, and theories from statistical physics that offer an explanatory model for such constraints. I will then broaden the discussion to the generic manner in which humans communicate using systems of interconnected stimuli or concepts, from language and music, to literature and science. I will describe an analytical framework to study the information generated by a system as perceived by a biased human observer, and provide experimental evidence that this perceived information depends critically on a system's network topology. Applying the framework to several real networks, we find that they communicate a large amount of information (having high entropy) and do so efficiently (maintaining low divergence from human expectations). Moreover, we also find that such efficient communication arises in networks that are simultaneously heterogeneous, with high-degree hubs, and clustered, with tightly-connected modules — the two defining features of hierarchical organization. Together, these results suggest that many real networks are constrained by the pressures of information transmission to biased human observers, and that these pressures select for specific structural features.

Description of the Speaker

Danielle S. Bassett is the J. Peter Skirkanich Professor at the University of Pennsylvania, with affiliations in the Departments of Bioengineering, Physics & Astronomy, Electrical & Systems Engineering, Neurology, and Psychiatry. She is also an External Professor at the Santa Fe Institute. She is most well known for her work blending neural and systems engineering to identify fundamental mechanisms of cognition and disease in human brain networks. She received a B.S. in physics from Penn State University and a Ph.D. in physics from the University of Cambridge, UK as a Churchill Scholar, and as an NIH Health Sciences Scholar. Following a postdoctoral position at UC Santa Barbara, she was a Junior Research Fellow at the Sage Center for the Study of the Mind. She has received multiple prestigious awards, including American Psychological Association's ‘Rising Star’ (2012), Alfred P. Sloan Research Fellow (2014), MacArthur Fellow Genius Grant (2014), Early Academic Achievement Award from the IEEE Engineering in Medicine and Biology Society (2015), Harvard Higher Education Leader (2015), Office of Naval Research Young Investigator (2015), National Science Foundation CAREER (2016), Popular Science Brilliant 10 (2016), Lagrange Prize in Complex Systems Science (2017), Erdos-Renyi Prize in Network Science (2018). She is the author of more than 240 peer-reviewed publications, which have garnered over 19000 citations, as well as numerous book chapters and teaching materials. She is the founding director of the Penn Network Visualization Program, a combined undergraduate art internship and K-12 outreach program bridging network science and the visual arts. Her work has been supported by the National Science Foundation, the National Institutes of Health, the Army Research Office, the Army Research Laboratory, the Office of Naval Research, the Department of Defense, the Alfred P Sloan Foundation, the John D. and Catherine T. MacArthur Foundation, the Paul Allen Foundation, the ISI Foundation, and the University of Pennsylvania.

The Organizing Committee of the Nagle Lecture Series thanks the USF Department of Mathematics and Statistics and the College of Arts and Sciences for sponsoring this event.