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: Lightning Talks w/ Northwestern Scholars!
Northwestern Institute on Complex Systems (NICO)
12:00 PM
//
Lower Level, Chambers Hall
Details
Speakers:
Yessica Herrera, Visiting Scholar, Northwestern Institute on Complex Systems
Talk Title: The Body Speaks: Visual Patterns of Psychological Stress
Aakriti Kumar, Post-Doctoral Fellow, Northwestern Institute on Complex Systems
Talk Title: Evaluating Elements of Empathic Communication with Experts, Crowds, and Large Language Models
Tingyu "Mark" Zhao, PhD Student, Industrial Engineering and Management Sciences
Talk Title: Noise Filtering in Complex Networks
Sign Up:
Sign up to present at a future Lightning Talk session. NICO Lightning Talks are open to graduate students, postdoctoral fellows, and visiting scholars.
Location:
In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/95387714084
Passcode: NICO25
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, May 14, 2025 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
WED@NICO SEMINAR: Rosemary Braun, Northwestern University "The Scale of Life"
Northwestern Institute on Complex Systems (NICO)
12:00 PM
//
Lower Level, Chambers Hall
Details
Speaker:
Rosemary Braun, Associate Professor, Department of Molecular Biosciences, Northwestern University
Title:
The Scale of Life
Abstract:
Living systems exhibit surprising and beautiful self-organization at all scales. At the atomic level, proteins self-assemble into macromolecular complexes. The function of these machines is orchestrated within the cell by regulatory networks, whose activity is in turn dictated by, and coordinated with, the cells environment. This coordination takes place across large spans of space and time: the size and lifetime of organisms as large as the blue whale. Populations and ecosystems of many organisms in turn exhibit remarkable emergent dynamics. Today, advances in single-cell assays enable us to probe the molecular state of every cell in a sample in high-dimensional detail. But is this the correct scale at which to probe living systems? What can we learn from this data, and how can we abstract from the microscopic details to macroscopic phenotypes? In this talk, I will discuss some of our recent work bridging the cell and tissue/organism scales, and discuss some challenges and opportunities for the future.
Speaker Bio:
Rosemary Braun is an Associate Professor of Molecular Biosciences, Applied Mathematics [ESAM], and Physics at Northwestern University. A theoretical physicist by training, she earned her PhD in Physics from the University of Illinois, followed by a Masters in Biostatistics from Johns Hopkins University. She completed her postdoctoral training at the National Cancer Institute (NIH) before joining Northwestern as a faculty member. Today, she works at the intersection of statistics, mathematics, and biology to develop computational tools for analyzing high-dimensional data. In addition to her Northwestern affiliations, she is also Associate Director of the National Institute for Theory and Mathematics in Biology, as well as external faculty of the Santa Fe Institute.
Location:
In person: Chambers Hall, 600 Foster Street, Lower Level
Remote option: https://northwestern.zoom.us/j/97015976754
Passcode: NICO25
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, May 21, 2025 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)