Events
Past Event
WED@NICO SEMINAR: Lightning Talks with Northwestern Fellows and Scholars!
Northwestern Institute on Complex Systems (NICO)
12:00 PM
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Lower Level, Chambers Hall
Details
NICO is hosting a lightning talk seminar each term as a part of our Wednesdays@NICO seminar series. Northwestern graduate students and postdoctoral fellows are invited to participate. To sign up for future lightning talks, please visit: https://bit.ly/2lRqSXK
FALL 2019 SPEAKERS
Diego Gómez-Zará - Ph.D. Candidate, Technology and Social Behavior
Title: A Network Approach to the Formation of Self-assembled Teams
Abstract: Which individuals in a network make the most appealing teammates? Which invitations are most likely to be accepted? And which are most likely to be rejected? This study explores the factors that are most likely to explain the selection, acceptance, and rejection of invitations in self-assembling teams. We conducted a field study with 780 participants using an online platform that enables people to form teams. Participants completed an initial survey assessing traits, relationships, and skills. Next, they searched for and invited others to join a team. Recipients could then accept, reject, or ignore invitations. Using Exponential Random Graph Models (ERGMs), we studied how traits and social networks influence teammate choices. Our results demonstrated that (a) agreeable leaders with high psychological collectivism send invitations most frequently, (b) previous collaborators, leaders, competent workers, females, and younger individuals receive the most invitations, and (c) rejections are concentrated in the hands of a few.
Alex Mercanti - Ph.D Candidate, Engineering Sciences & Applied Mathematics
Title: Protecting your privacy in machine learning using randomness.
Abstract: Machine learning models are commonly trained over datasets that contain personal information about people and their daily routine, health, online activity, and social behavior. Although these models play a crucial role in modern software applications, the extent to which trained machine learning models leak private and sensitive features of their respective training data remains poorly understood. In this talk, I will discuss the privacy risks associated with publicly releasing trained machine learning models and will demonstrate that the addition of random noise to training algorithms guarantees privacy for each individual in the training dataset at minimal cost to the accuracy of the model.
Kyosuke Tanaka - Ph.D Candidate, Media, Technology, and Society
Title: How dispositional and positional factors affect an individual’s ability to efficiently route messages in a network
Abstract: Milgram’s small-world experiment provided evidence for six degrees of separation, on average a chain of five contacts separated any two random people in the world. However, this was only true for those messages that reached the final destination. While, in theory, the small-world phenomenon is structurally common in social networks, empirical evidence shows that human navigation of small-world social networks is remarkably challenging. Messages often reach the intended destination via a longer path than expected, get enmeshed in loops, and/or often never reach it. This leads to painful consequences for organizations that require information routing to share (or retrieve) knowledge among their members. Extreme examples of these failures contributed to the loss of the space shuttles Challenger and Columbia. Here, I present a study of an understudied type of error—network routing—and introduce network acuity to conceptualize and operationalize an individual’s ability to efficiently route messages. Using, 6-DoS (Six Degrees of Separation), a network routing task based on Milgram’s small-world experiment with 435 individuals organized into 25 networks, I explored two types of factors that impact an individual’s network acuity: positional factors (where you are in the network) and dispositional factors (who you are). Results show that (a) those in the core or brokerage position had high network acuity than did peripheral or non-bridge members, (b) neuroticism was positively associated with acuity, (c) conscientiousness was negatively associated with acuity. Further, individuals’ network positions impacted network acuity more than dispositional characteristics. The results of this experimental study illustrate not only the usefulness of the concept of network acuity to characterize network routing errors but also advance our understanding of factors that explain variance in individuals' network acuity.
Alexandria Volkening - NSF-Simons Fellow, NSF-Simons Center for Quantitative Biology
Title: Forecasting U.S. elections with compartmental models of infection
Abstract: U.S. election forecasting involves polling likely voters, making assumptions about voter turnout, and accounting for various features such as state demographics and voting history. While political elections in the United States are decided at the state level, errors in forecasting are correlated between states. With the goal of shedding light on the forecasting process and exploring how states influence each other, we develop a framework for forecasting elections in the U.S. from the perspective of dynamical systems. Through an interdisciplinary approach that borrows ideas from epidemiology, we show how to combine a compartmental model with public polling data from HuffPost and RealClearPolitics to forecast gubernatorial, senatorial, and presidential elections at the state level. Our results for the 2012 and 2016 U.S. races are largely in agreement with those of popular sources, and we use our model to explore how subjective choices about uncertainty impact results. We conclude by comparing our forecasts for the 2018 midterms with those of popular analysts, and we discuss future directions related to the 2020 elections. This is joint work with Daniel Linder (Augusta Univ.), Mason Porter (UCLA), and Grzegorz Rempala (Ohio State Univ.).
Live Stream:
Time
Wednesday, December 4, 2019 at 12:00 PM - 1:00 PM
Location
Lower Level, Chambers Hall Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, March 30, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, April 6, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, April 13, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, April 20, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, April 27, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
Data Connection Hub - April Meeting
Northwestern Institute on Complex Systems (NICO)
12:00 PM
Details
The Data Connection Hub is being created as a transdisciplinary space which builds communication, understanding, and relationships across a variety of stakeholders while also highlighting local community-engaged and participatory data science efforts. Our monthly meetings and the accompanying Slack communities are meant to be broadly inclusive, and we welcome students and faculty from all Chicagoland Institutions, as well as community partners and those who wish to learn more.
This hub is jointly organized by the CONNECT Research Program and the Metropolitan Chicago Data-Science Corps Program.
Sign up here: https://bit.ly/3XkaSKc
Time
Friday, April 28, 2023 at 12:00 PM - 1:00 PM
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, May 4, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, May 11, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, May 18, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)
NICO Reading Group - Weekly Thursday Meeting
Northwestern Institute on Complex Systems (NICO)
5:00 PM
//
Mudd Hall ( formerly Seeley G. Mudd Library)
Details
The NICO Reading Group is a community of individuals who are passionate about the intersection of complexity, data science, machine learning, and deep learning. We are an interdisciplinary and cross-departmental group, comprising staff, faculty, undergraduates, and graduate students from various schools and departments, including Kellogg, McCormick, Feinberg, and Weinberg. Our backgrounds range from data science, mechanical engineering, material science, computer science, physics, and mathematics.
Our discussions focus on fundamental and state-of-the-art techniques in complexity science and deep learning, covering topics such as data science, deep learning, AI for scientific knowledge discovery, computational modeling, and material design. We strive to create a welcoming and inclusive environment in which everyone can contribute to the discussion, regardless of their level of expertise.
Our goal is to foster mutual understanding and personal connections among people from different schools and departments who share a common interest in complex science and AI.
For more information, contact Xiaoyu Xie at XiaoyuXie2020@u.northwestern.edu
Meeting Times:
Date: Every Thursday during the 2023 winter and spring quarters.
Time: 5-6pm
Place: Mudd Library or the Garage. This location changes weekly. Please contact Xiaoyu Xie for the specific location.
Time
Thursday, May 25, 2023 at 5:00 PM - 6:00 PM
Location
Mudd Hall ( formerly Seeley G. Mudd Library) Map
Contact
Calendar
Northwestern Institute on Complex Systems (NICO)