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

Lightning Talk Speakers:

○ Sugat Dabholkar - PhD Candidate in the Learning Sciences program at the School of Education and Social Policy, Northwestern University.

Title: Emergent Systems Microworlds to teach and learn about complex emergent phenomena

Abstract: Learning and reasoning about complex systems is not simple. Both novices and experts often fall into the trap of level-slippage while reasoning about complex natural phenomena. Level-slippage is the confusion that arises when one expects emergent macro-level patterns to be similar to local micro-level patterns. Such confusion is people’s source of a deep misunderstanding of several patterns and phenomena in the world.

In my work, I seek to address this issue for high school science students by combining two powerful design approaches in Learning Sciences, namely, agent-based modeling of emergent systems and constructionism. We call this design approach Emergent Systems Microworlds (ESM). This approach is based on Wilensky and Papert’s restructuration theory (2010), which argues for the importance of representational infrastructure for changing fundamental aspects of knowledge encodings in a disciplinary domain. In this talk, I will discuss how agent-based restructurations in an ESM allow learners to develop fundamentally deeper insights into complex phenomena.

In an ESM-based curriculum, students explore and learn about emergent phenomena, using agent-based computational models that are designed in NetLogo (Wilensky, 1999) in the form of a microworld. In such models, an agent is a computational object with particular properties and actions. An ‘emergent’ phenomenon is modeled in terms of agents and their interactions. Microworlds are encapsulated open-ended computational exploratory environments in which a set of concepts can be explored, through interactions that lead to knowledge construction. In this talk, I will present some examples of ESM-based curricula that I designed for high school students to learn about genetics and evolution, two fundamental ideas in biology. I will discuss how the agent-based representational architecture in the ESMs allowed the students to engage in reasoning about complex systems principles in the context of the phenomena they were studying.

Bio: Sugat Dabholkar is a doctoral candidate in the Learning Sciences program at the School of Education and Social Policy, Northwestern University. His work involves designing technology-enhanced learning environments for learning scientific thinking, computational thinking, and complex systems thinking. Over the past four years, Sugat has developed several computational agent-based models, many of which have been incorporated into curricular units for high school students. He has conducted Professional Development programs for teachers focusing on designing Computational Thinking integrated STEM curricular units. These curricular units have been used in school settings in the US as well as in India.

○ Xuan Ma - Postdoctoral Fellow at the Feinberg School of Medicine, Northwestern University

Title: Probing motor control during naturalistic movements for extending BCI use

Abstract: Most existing sensorimotor and brain computer interface (BCI) studies have investigated the mapping from motor cortex (M1) to muscles by training monkeys to perform a few instructed movements in highly restricted conditions. Motivated by the demand of extending those in-lab studies to a wider realm, we propose to explore motor control during more natural movements of unrestrained monkeys. We simultaneously recorded M1 neural activity and electromyograph (EMG) wirelessly while the monkey was in a plastic telemetry cage in which it could perform various free-form movements. We then investigated the features of these signals and the consistency of the relationship between them. In this talk, I will describe progress we have made and challenges we are facing to extend BCI use in more naturalistic contexts, and will also introduce our efforts with deep learning methods to address those challenges.

Bio: Xuan Ma is currently a postdoctoral fellow in Feinberg School of Medicine, Northwestern University. He received the Ph.D. degree in control science and engineering from Huazhong University of Science and Technology, Wuhan, China, in 2017. His research interests include cortically-controlled functional electric stimulation, neural motor control system modeling, and biomedical signal processing.

○ Suman Kalyan Maity - Postdoctoral Fellow at the Kellogg School of Management, CSSI and NICO

Title: Winners, Losers, and Future Achievement

Abstract: One of the most robust findings on human performance is that past achievement predicts future achievements. Indeed, prior achievements may reflect underlying, differentiating characteristics rendering past winners more predictably outperforming their non-winning counterparts in future competitions. Further, the Matthew effect posits that past victories bring reputation and recognition that can translate into tangible assets, which increase the chance for future victories. Hence even if the deck was not stacked against some in favor of others, positive feedback operating on arbitrary initial advantage can increasingly set apart winners from losers. These mechanisms lead to one fundamental principle with crucial implications: Between past winners and losers, it is the former that are more likely to win in the future. Indeed, partly due to the robustness of this principle, the idea of selecting on winners has become one of the most commonly used heuristics in identifying and nurturing talents across a remarkably wide range of domains. In this talk, we systematically test against the principle of selecting between winners and losers across various settings. We observe that whenever there existed a reward based milestone (being on the podium, entering the main draw of a Tennis tournament etc.), the athletes who had just missed it ended up outperforming the athletes who narrowly achieved the milestone in future endeavors.

Bio: Suman Kalyan Maity is a Postdoctoral Fellow at the Kellogg School of Management, The Center for Science of Science & Innovation (CSSI), and NICO.

○ Rebeka O. Szabo - Pre-Doctoral Fellow at the Kellogg School of Management, Northwestern University

Title: The Micro-Dynamic Nature of Team Interaction

Abstract: Teams have become a popular organization form since well-functioning task-focused groups are basic pillars of successful organizations. While there is much interest in contemporary social science in understanding team processes that lead to efficiency, most of these researches rely heavily on self-reported data yielding static and potentially biased information and tends to overlook actual interaction processes. We propose a novel approach that allows portraying a nuanced, complex picture of problem-solving group behavior by measuring performance dynamics as it evolves in real-time, in a controlled environment. The research aims to explore how collaboration networks of small project teams evolve across time and team members, and how it relates to successful task performance. We investigate interaction patterns in escape rooms, where all teams are video recorded during the task-solving process in the same experimental environment. We expected that homogeneous distribution of interaction ties across time and team members fosters successful problem-solving. Concerning the impact of the initial social roles on the dynamics of the interaction pattern, we hypothesized that flexible, less hierarchical team structures favor for problem-solving. This research aims to advance the new science of teams' by focusing on the network micro-mechanisms that allows us to treat teams as dynamic, adaptive, task-performing systems.

Bio: Rebeka O. Szabo is a visiting Pre-Doctoral Fellow at the Kellogg School of Management. She is a PhD candidate at the Central European University's Department of Network and Data Science.

About the Speaker Series:

Wednesdays@NICO is a vibrant weekly seminar series focusing broadly on the topics of complex systems and data 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.

Live Stream:

bluejeans.com/8474912528

Related Info

Spring Break Begins

Spring Classes begin 8 a.m.

Northwestern Monday: In the fall of 2019, President Schapiro and Provost Holloway announced changes to commencement, spring break and the start of the spring quarter: spring quarters will now routinely start on Tuesday, rather than Monday, to afford two full weekends of break.

Though spring quarters will begin on a Tuesday, the Monday class schedule will be in effect, a practice referred to as “Northwestern Monday.” Classes that usually meet only on Tuesdays will not meet during the first week of the term. This calendar applies to all quarter classes except those offered in the evening programs in the Kellogg School of Management and the School of Professional Studies (SPS).

APRIL MEETING: Wednesday, April 1 2020 at 6:30pm in Chambers Hall, Evanston

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!

SPEAKER: Dimitris Papanikolaou, Professor of Finance, Kellogg School of Management

TOPIC: TBA

AGENDA:

6:15pm - Socializing and Refreshments
6:30pm - Presentation by Dimitris Papanikolaou, Professor of Finance, Kellogg School of Management
7pm - Hacking session: project and learning groups

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.

Related Info

Liza Mundy, an award-winning journalist and New York Times-best-selling author of four books including Code Girls: The Untold Story of the American Women Code Breakers of World War II, will be talking about how she discovered the story of some 10,000 women during the war working on different aspects of code breaking.

Published in 2017, Code Girls tells the story of more than 10,000 women who were recruited to break Axis codes, work that saved countless lives, shortened the war—and pioneered the modern computer and cybersecurity industries. The book was a New York Times best-seller, a Washington Post best-seller, and a Wall Street Journal best-seller. It has sold more than 200,000 copies and has been translated into ten languages to date. It received rave reviews in publications including The Washington Post, The New York Times Book Review, and Studies in Intelligence, which said that “Code Girls pays tribute to an unsung group of patriotic Americans who, more than seven decades later, are just now receiving their due." It has won awards including "Best General Audience Intelligence Book" of 2018 from the Association of Former Intelligence Officers, which said that "Code Girls does for women of that era what Hidden Figures did for African American women of the 1960s and Windtalkers did for the native American code communicators of World War II."

Co-sponsored by: Department of Statistics, Department of Mathematics, Northwestern Institute on Complex Systems, Edith Kreeger Wolf Fund for Distinguished Visitors, Science in Human Culture

RSVP is appreciated, but not required.

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