Events
Past Event
CANCELLED - WED@NICO SEMINAR: Hamsa Bastani, Wharton School, University of Pennsylvania "Challenges in Achieving Human-AI Collaboration"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
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Lower Level, Chambers Hall
Details
Hamsa Bastani is regrettably unable to join us this week and her talk is postponed. We will reschedule in the Fall 2026 term.
Speaker:
Hamsa Bastani, Associate Professor of Operations, Information, and Decisions, and Statistics and Data Science, Wharton School, University of Pennsylvania
Title:
Challenges in Achieving Human-AI Collaboration
Abstract:
TBA
Speaker Bio:
Hamsa Sridhar Bastani is an Associate Professor of Operations, Information, and Decisions (OID) and Statistics and Data Science at the Wharton School of the University of Pennsylvania, where she co-direct the Wharton Healthcare Analytics Lab. Her research sits at the intersection of machine learning, operations research, and economics. She studies how to design, deploy, and evaluate AI systems that empower human decision-makers and improve societal outcomes.
Professor Bastani aims to combine methodological depth with implementation in consequential environments. She has worked with national governments to deploy algorithms at the country scale for targeted border COVID-19 screening and essential medicine access, and has co-led one of the first large field studies of generative AI tutors in high school mathematics. She studies both the mathematical properties of algorithms and the way people respond to them.
Her research has been published in leading outlets including Nature, Management Science, Operations Research, and PNAS, and has garnered numerous recognitions, including the Wagner Prize for Excellence in Operations Research, the INFORMS Pierskalla Award for best healthcare paper, and the George Nicholson Prize. Previously, she graduated summa cum laude from Harvard in 2012 with an A.M. in physics and an A.B. in physics and mathematics, completed her PhD in Stanford's Electrical Engineering department under the supervision of Mohsen Bayati, and spent a year as a Herman Goldstine postdoctoral fellow at IBM Research.
Location:
Postponed until Fall 2026
About the Speaker Series:
Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems, networks, and artificial intelligence. It brings together attendees ranging from graduate students to senior faculty who span all of the schools across Northwestern, from applied math to sociology to biology and every discipline in-between. Please visit: https://bit.ly/WedatNICO for information on future speakers.
Time
Wednesday, May 13, 2026 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Data Science Nights - MAY 2026 - Speaker: Xudong Tang, Computer Science and NICO
Northwestern Institute on Complex Systems (NICO)
5:30 PM
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M416, Technological Institute
Details
MAY MEETING: Thursday, May 28, 2026 at 5:30pm (US Central)
LOCATION:
ESAM Conference Room, Tech M416
2145 Sheridan Road, Evanston, IL 60208
AGENDA:
5:30pm - Meet and greet with refreshments
6:00pm - Talk with Xudong Tang, PhD Student, Computer Science, NICO, and the Human-AI Collaboration Lab, Northwestern University
TALK TITLE:
Human and Machine Perception of Voice Similarity
ABSTRACT:
Modern voice cloning systems generate synthetic speech that listeners frequently cannot identify as being synthetic. But a voice can sound natural without sounding like the intended person, and what determines whether a clone is heard as a particular person is an open question. Here we report a large-scale preregistered experiment in which we collected 92,239 responses from 175 participants on their perception of pairs of real recordings, voice clones, and continuously morphed voices drawn from 100 contemporary celebrities across 20 speaker groups. We find that voice clones do not reliably preserve perceived speaker identity, reducing same-speaker judgments by 12.7 percentage points even though the clones are produced by a state-of-the-art text-to-speech model, while leaving different-speaker judgments unchanged. Using continuously morphed stimuli, we find that speakers vary substantially in how much variation their perceived identity tolerates, and that this variation is not predicted by speaker demographics. Speaker embeddings account for 58.9\% (95\% CI = [55.7, 61.9]) of variance in identity judgments, which is more than acoustic features, social attributes, and clone status combined. Once all these observed features are accounted for, clone status adds no additional predictive power. These results shows that the perceptual impact of voice cloning is positional rather than categorical: we can model how listeners judge a voice by how close it falls to the perceptual boundary that defines each speaker's recognizable voice, applying the same criterion to real and synthetic speech alike.
DATA SCIENCE NIGHTS are monthly meetings featuring presentations and discussions about data-driven science and complex systems, organized by Northwestern University graduate students and scholars. Students and researchers of all levels are welcome! For more information: http://bit.ly/nico-dsn
FUTURE DATES:
Data Science Nights will return in September!
Time
Thursday, May 28, 2026 at 5:30 PM - 7:00 PM
Location
M416, Technological Institute Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Spring 2026 Commencement
University Academic Calendar
All Day
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Spring 2026 Commencement
Time
Sunday, June 14, 2026
Contact
Calendar
University Academic Calendar
Juneteenth - University Closed
University Academic Calendar
All Day
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Juneteenth - University Closed
Time
Friday, June 19, 2026
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Calendar
University Academic Calendar
Independence Day (observed) - University Closed
University Academic Calendar
All Day
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Independence Day (observed) - University Closed
Time
Friday, July 3, 2026
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University Academic Calendar
Fall 2026 Classes Begin
University Academic Calendar
All Day
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Fall 2026 Classes Begin
Time
Wednesday, September 23, 2026
Contact
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University Academic Calendar