Events
Past Event
Data Science Nights - June 2021 Meeting (Speaker: Juandalyn Burke)
Northwestern Institute on Complex Systems (NICO)
5:15 PM
Details
JUNE MEETING: Tuesday, June 29, 2021 at 5:30pm (US Central) via Zoom and Gather
DATA SCIENCE NIGHTS are monthly hack nights on popular data science topics, organized by Northwestern University graduate students and scholars. Aspiring, beginning, and advanced data scientists are welcome!
AGENDA:
5:15: Welcome to Data Science Nights via Zoom
* Zoom Link: https://northwestern.zoom.us/j/99588631168
5:30: Presentation by Juandalyn Burke, University of Washington
6:00: Hacking session via Gather
* Gather link: https://gather.town/app/UCTJAHOgQi2FLx4O/DSN
SPEAKER: Juandalyn Burke, Ph.D. Candidate, Biomedical Informatics and Medical Education Department, University of Washington
TOPIC: Using an Ecological Inference Software Tool to Detect Vote Dilution
The most basic characteristic of a democratic system is the right to vote. The Voting Rights Act (VRA) of 1965 was established to ensure fair voting practices were enacted and that elected officials were representative of the community they served. The VRA prohibits unfair and discriminatory voting practices, including racially polarized voting and vote dilution, based on the race or an individual’s association with minority language groups. However, in the United States, violations of the VRA are difficult to prove because information on race and ethnicity is not collected in the voting process. By definition, racially polarized voting occurs when distinct racial or ethnic groups vote divergently to elect their separate candidates of choice. Vote dilution occurs when the racial majority group votes to block the minority group from electing their preferred candidate. The eiCompare software package detects both racially polarized voting and vote dilution by inferring the race or ethnicity of the voters in a population using several methods of ecological inference. We improved and added features to the eiCompare package including: geocoding, more accurate procedures in detecting the race of voters, better visualization of ecological inference outcomes, parallel processing, and analysis of historical voting data. We think these new features will allow for better detection of racially polarized voting and vote dilution and will help to support evidence presented in voting rights litigation.
ADDITIONAL HACKING SESSION INFO
For anyone interested in building and analyzing networks, Jenny Liu will be at the "hack" sessions with code related to networks. The goal will be to go through some basic exercises from a book, then move onto reproducing the results of some papers.
For more info: data-science-nights.org
Supporting Groups:
This event is supported by the Northwestern Institute for Complex Systems and the Northwestern Data Science Initiative.
Time
Tuesday, June 29, 2021 at 5:15 PM - 7:30 PM
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
WED@NICO SEMINAR: Mayank Agrawal, Proof of Human "The Invisible Turing Test for the Internet"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
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Lower Level, Chambers Hall
Details
Speaker:
Mayank Agrawal, Co-founder and CEO, Proof of Human
Title:
Proof of Human: the Invisible Turing Test for the Internet
Abstract:
This presentation introduces the Process Turing Test, a new framework for distinguishing humans from AI that goes beyond linguistic output to analyze behavioral dynamics. As LLMs routinely pass text-based Turing Tests, we need methods that probe the underlying architecture of intelligence through perception, control, and decision-making patterns. Using process tracing data from canonical cognitive tasks, we demonstrate how behavioral embeddings capture computational signatures unique to human cognition. This provides robust proof-of-personhood that resists adversarial attacks while revealing fundamental principles about how humans and machines process information differently.
Speaker Bio:
Mayank Agrawal is the co-founder and CEO of Proof of Human, a research and deployment company building the proof-of-human layer in digital identity. The company develops high-impact research and translates that work into systems for bot detection, fraud prevention, and continuous authentication. Mayank’s work focuses on new approaches to distinguishing humans from AI through behavioral and cognitive signals. He earned his PhD in Psychology and Neuroscience from Princeton University, where he studied computational models of human decision-making with Jonathan Cohen, Tom Griffiths, and Nathaniel Daw. His research spans cognitive science, machine learning, and artificial intelligence, with work published in Science, PNAS, and Psychological Review. He previously studied Computer Science and Philosophy at Swarthmore College.
Location:
In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/96392420891
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, November 11, 2026 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)