Speaker:

César Hidalgo, Director of the Collective Learning Group, MIT Media Lab

Title:

The Principles of Collective Learning

Abstract:

How do teams, cities, and nations learn? In this talk I will discuss research on the principles that govern the creation, diffusion, and valuation of knowledge. These principles govern the accumulation of knowledge from experience, the diffusion of knowledge across social, geographic, and cognitive barriers, and the connection between the geography of knowledge and macroeconomic outcomes, such as income, economic growth, and income inequality. I will then use these principles to discuss optimal industrial diversification strategies, micro-mechanisms governing knowledge diffusion, and the application of these principles to industrial policy. To finalize, I will present applied work on the creation of national data integration, distribution, and visualization systems (e.g. datausa.io, datachile.io). I will show how these technologies are changing the way governments distribute data and paving the way for a world in which government executive action is augmented by artificial intelligence.

Speaker Bio:

César A. Hidalgo leads the Collective Learning group at The MIT Media Lab and is an Associate Professor of Media Arts and Sciences at MIT. Hidalgo's work focuses on understanding how teams, organizations, cities, and nations learn. At the Collective Learning group, Hidalgo studies knowledge flows and also creates software tools to facilitate learning in organizations. Hidalgo's academic publications have been cited more than 12,000 times and his online systems have received more than 100 million pageviews and numerous awards. Hidalgo's latest book, Why Information Grows (Basic Books, 2015), has been translated to over ten languages. Hidalgo is also the co-author of The Atlas of Economic Complexity (MIT Press, 2014), and a co-founder of Datawheel LLC, a company that has professionalized the creation of large data visualization engines. Hidalgo lives in Somerville Massachusetts with his wife Anna and their daughter Iris.

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Speaker:

Ágnes Horvát, Assistant Professor, School of Communications, Northwestern University

Title:

TBA

Abstract:

TBA

Speaker Bio:

Ágnes Horvát is an Assistant Professor in the Department of Communication Studies, an affiliated faculty of the Northwestern Institute on Complex Systems (NICO), and the Department of Management and Organizations of the Kellogg School of Management (by courtesy). She seeks to measure, understand, and forecast the collective behavior of networked crowds in large-scale sociotechnical systems like peer-to-peer platforms. Her current research develops empirical and theoretical methods to support creativity and predict success in culture industries, identify expressions of collective intelligence and opportunities for innovation in crowdsourcing communities, as well as detect shared misconceptions and biases in online capital markets. Her work work at the intersection of computational social science and social computing uses an interdisciplinary data-driven approach and builds on techniques from network science, machine learning, statistics, and exploratory visualization. Professor Horvát developed and teaches a ‘Cultural Analytics’ graduate course that is designed to train students for careers at the intersection of creative occupations and data science. She serves on the editorial board of PLOS One. Horvát has been the recipient of many fellowships and academic excellence awards, most recently a CISE CRII award from the National Science Foundation.

Live Stream:

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OCTOBER MEETING: Thursday, November 1, 2018 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. Each night will feature one hour of structured programming followed by a hacking night with data science project or learning groups of your choice.

Aspiring, beginning, and advanced data scientists are welcome!

Tentative Agenda:

6.15 p.m. – 6.30 p.m. Socializing and Refreshments
6.30 p.m. – 6.55 p.m. Introduction to Machine Learning - Nicholas Wagner and Abhijith Gopakumar, Materials Science and Engineering, Northwestern U.
7.00 p.m. – Join or suggest a project or learning group, or work on your own projects

For more info: data-science-nights.org

Supporting Groups:

This event is supported by the Northwestern Institute for Complex Systems, the Northwestern Data Science Initiative, and the Northwestern University Postdoctoral Forum.

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Speaker:

Cassidy Rose Sugimoto, Associate Professor, School of Informatics and Computing, Indiana University

Title:

TBA

Abstract:

TBA

Speaker Bio:

Sugimoto researches within the domain of scholarly communication and scientometrics. She examines the ways in which knowledge is produced, disseminated, and rewarded. She has co-edited four volumes and has published 70 journal articles on this topic. Her work has been presented at numerous conferences and has received research funding from the National Science Foundation, Institute for Museum and Library Services, and the Sloan Foundation, among other agencies. Sugimoto is actively involved in teaching and service and has been rewarded in these areas with an Indiana University Trustees Teaching award (2014) and a national service award from the Association for Information Science and Technology (2009). She is currently President of the International Society for Scientometrics and Informetrics. Sugimoto has an undergraduate degree in music performance, an M.S. in library science, and a Ph.D. in information and library science from the University of North Carolina at Chapel Hill.

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Speaker:

Nicholas Diakopoulos, Assistant Professor, School of Communication, Northwestern University

Title:

TBA

Abstract:

TBA

Speaker Bio:

Nicholas Diakopoulos is an Assistant Professor in the School of Communication at Northwestern University where he is Director of the Computational Journalism Lab (CJL). He is also a Tow Fellow at Columbia University School of Journalism as well as Associate Professor II at the University of Bergen Department of Information Science and Media Studies. He received his Ph.D. in Computer Science from the School of Interactive Computing at Georgia Tech where he co-founded the program in Computational Journalism. His research is in computational and data journalism with active research projects on (1) algorithmic accountability and transparency, (2) automation and algorithms in news production, and (3) social media in news contexts. He is the author of Automating the News: How Algorithms are Rewriting the Media forthcoming from Harvard University Press in early 2019. Nick also works as a consultant from time to time and is happy to discuss how to help your organization with a range of research or design projects related to computational and data journalism, automated news production, or social media and news.

Live Stream:

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Speaker:

Andrew Papachristos, Professor of Sociology, Northwestern University

Title:

TBA

Abstract:

TBA

Speaker Bio:

Andrew V. Papachristos is currently Professor of Sociology and the Director of the Northwestern Network and Neighborhood Initiative. Papachristos aims to understand how the connected nature of cities—how their citizens, neighborhoods, and institutions are tied to one another—affect what we feel, think, and do. His main research applies network science to the study of gun violence, police misconduct, illegal gun markets, Al Capone, street gangs, and urban neighborhoods. He is also in the process of completing a manuscript on the evolution of black street gangs and politics in Chicago from the 1950s to the early-2000s. Papachristos is also actively involved in policy related research, including the evaluation of gun violence prevention programs in more than a dozen U.S. cities. An author of more than 50 articles, Papachristos’ work has appeared in journals such as JAMA, The American Sociological Review, Criminology, The American Journal of Public Health, The New York Times, The Washington Post, and The Chicago Tribune, among other outlets. Papachristos was awarded an NSF Early CAREER award to examine how violence spreads through high-risk social networks in several U.S. cities.

Live Stream:

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NOVEMBER MEETING: Thursday, December 6, 2018 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. Each night will feature one hour of structured programming followed by a hacking night with data science project or learning groups of your choice.

Aspiring, beginning, and advanced data scientists are welcome!

Agenda: TBA

For more info: data-science-nights.org

Supporting Groups:

This event is supported by the Northwestern Institute for Complex Systems, the Northwestern Data Science Initiative, and the Northwestern University Postdoctoral Forum.

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