Events
Past Event
Data Science Nights - January 2021 Meeting (Speaker: Bryan Pardo)
Northwestern Institute on Complex Systems (NICO)
5:15 PM
Details
JANUARY MEETING: Wednesday, January 27, 2021 at 5:15pm (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/96207323991
* Passcode: DSN2021
5:30: Presentation by Bryan Pardo, Northwestern University
6:00: Hacking session via Gather
* Gather link: https://gather.town/app/UCTJAHOgQi2FLx4O/DSN
SPEAKER: Bryan Pardo, Associate Professor, McCormick School of Engineering, Northwestern University
TOPIC: New directions in deep audio source separation: training without ground truth and automatic model selection
Audio source separation is the task of separating an audio scene containing multiple concurrent sound sources into individual streams/tracks, each containing a source (or group of sources) of interest to the user. Source separation is an enabling technology for a variety of tasks, including speech recognition, music transcription, sound object ID, and hearing assistance. Deep learning models are the state-of-the-art in source separation, but they are typically trained on synthetic audio mixtures made from isolated sound source recordings so that ground-truth for the separation is known. However, the vast majority of available audio is not isolated, limiting the range of scenes where deep models trained on isolated data are effective. Furthermore, a deep model is typically only successful in separating audio mixtures similar to the mixtures it was trained on. This requires the end user to know enough about each model’s training to select the correct model for a given audio mixture. In this talk, Prof. Pardo will outline proposed solutions to both problems. First, he will present a method to train a deep source separation model in an unsupervised way by bootstrapping using multiple primitive cues, without the need for ground truth isolated sources or artificial training mixtures. He will then outline a proposed confidence measure that can be broadly applied to any clustering-based source separation model. The proposed confidence measure does not require ground truth to estimate the quality of a separated source. This allows automatic selection of the appropriate deep clustering model for an audio mixture.
SPEAKER BIO: Bryan Pardo is head of Northwestern University’s Interactive Audio Lab and co-director of the Northwestern University HCI+Design institute. Prof. Pardo has appointments in in the Department of Computer Science and Department of Radio, Television and Film. He received a M. Mus. in Jazz Studies in 2001 and a Ph.D. in Computer Science in 2005, both from the University of Michigan. He has authored over 100 peer-reviewed publications. He has developed speech analysis software for the Speech and Hearing department of the Ohio State University, statistical software for SPSS and worked as a machine learning researcher for General Dynamics. He has collaborated on and developed technologies acquired and patented by companies like Bose, Adobe and Ear Machine. While finishing his doctorate, he taught in the Music Department of Madonna University. When he is not teaching or researching, he performs on saxophone and clarinet with the bands Son Monarcas and The East Loop.
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
Monday, January 25, 2021 at 5:15 PM - 7:30 PM
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
WED@NICO SEMINAR: Steven Franconeri, Northwestern University "Point Taken: A gamified Intervention that Creates Enlightened Disagreements"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
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Lower Level, Chambers Hall
Details
Speaker:
Steven Franconeri, Professor of Psychology, Weinberg College of Arts & Sciences; Professor of Management and Organizations, Kellogg School of Management, Northwestern University
Title:
Point Taken: A gamified Intervention that Creates Enlightened Disagreements
Abstract:
Should we drop standardized testing for college or Ph.D. admissions? Allow athletes to join teams based on gender identity? When organizational and public policies bind behavior, human coexistence requires a way to determine that collective policy. Because individuals and like-minded groups have incomplete information, constrained strategies, and biased perspectives, thoughtful debate on those policies is critical. Unfortunately, those debates too often degrade into chaotic fights.
Point Taken provides a scalable solution by translating best practices in conflict resolution and critical thinking into a structured dialogue that can be learned and played in 30 minutes. In this interactive session, you'll play a short game to feel its effects.
Players replace persuasion with a common goal of discovering why they disagree. Dialogue then unfolds thoughtfully and calmly, through chains of short written reasons and responses. We've tested the game extensively in schools and organizations, and conducted a formal pilot study. All show powerful improvements in the tone and quality of debate, across longstanding and strongly-held disagreements. I’ll give background on best practices for enlightened disagreement, show how they translate to the game, ask you to play a game, and then ask for your advice on next steps.
Speaker Bio:
Steven Franconeri is leading scientist, teacher, and speaker on visual thinking, visual communication, and the psychology of data visualization. He is a Professor of Psychology in the Weinberg College of Arts & Sciences at Northwestern, Director of the Northwestern Cognitive Science Program, as well as a Kellogg Professor of Management and Organizations by Courtesy. He is the director of the Visual Thinking Laboratory, where a team of researchers explore how leveraging the visual system - the largest single system in your brain - can help people think, remember, and communicate more efficiently.
His undergraduate training was in computer science and cognitive science at Rutgers University, followed by a Ph.D. in Experimental Psychology from Harvard University, and postdoctoral research at the University of British Columbia. His work on both Cognitive Science and Data Visualization has been funded by the National Science Foundation, as well as the Department of Education, and the Department of Defense. He has received a prestigious National Science Foundation CAREER award, given to researchers who combine excellent research with outstanding teaching, and he has received a Psychonomic Society Early Career award for his research on visual thinking.
Location:
In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/97198523514
PW: NICO26
About the Speaker Series:
Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems, data science and network science. 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, March 11, 2026 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)