Data Hangout
Penn Undergraduate Data Science Hangout
School of Arts and Sciences
Summer 2020
The summer 2020 hangout is intended for undergraduate students whose summer research involves quantitative analysis of datasets, including variants of machine learning. The research project could be in the humanities, social sciences or natural sciences. As part of SAS’s initiative in data science, we have set up a resource that we hope will be interactive and stimulating for you.
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Typically there will be talks from 1-2pm, and tutorials on the basics of data science from 3-4pm. We can help set up other activities such as student talks and hack sessions on topics like data visualization and machine learning tools.
The talks are public and can be viewed live via zoom at: https://sasupenn.zoom.us/j/91162223949
Schedule and Speakers
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June 25
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Introduction to data science hangout - Bhuvnesh Jain (Physics and Astronomy), Sara Casella (Economics)
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Using text to understand politics & public opinion: Dan Hopkins (Political Science)
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Tutorial: Basics of probability and statistics - Ann Sizemore (Complex Systems Lab)
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July 2
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Network design in leaves, river deltas and human vasculature: Eleni Katifori (Physics and Astronomy)
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Human Happiness in High Resolution: Insights from large-scale experience sampling : Matt Killingsworth (Wharton)
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Tutorial: Basics of programming in Python - Pedro Bernardinelli (Physics and Astronomy)
July 9
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Simulating COVID-19 in a University Environment: Phil Gressmen (Math)
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How do we track where COVID-19 virus comes from? Estimating genealogies from DNA sequences: Junhyong Kim (Biology)
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Tutorial: Data visualization - Ann Sizemore (Complex Systems Lab)
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July 16
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Machine learning in the Milky Way: Robyn Sanderson (Physics and Astronomy)
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Data-driven Modeling of Human Color Vision: David Brainard (Psychology)
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Tutorial: Linear regression theory and practice - Ann Sizemore (Complex Systems Lab) and Sara Casella (Economics)
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July 23
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Understanding Misperceptions of Inequality in China Using Print and Social Media Data: Xi Song (Sociology)
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Why is the universe expanding so rapidly? Bhuv Jain (Physics and Astronomy)
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Tutorial: Machine learning I: Intro to neural networks - Cyrille Doux (Physics and Astronomy)
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July 30
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Evolutionary forces of cultural change: Josh Plotkin (Biology)
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High dimensional word embeddings to predict human judgment: Sudeep Bhatia (Psychology)
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Tutorial: Machine learning II: Applications to image analysis and others - Cyrille Doux (Physics and Astronomy)
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August 6th
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Data Science and Criminology: Greg Ridgway (Criminology)
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Ethical algorithms: Michael Kearns (Computer Science)
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Tutorial: Bayesian statistical inference: an application to cosmology - Marco Raveri (Physics and Astronomy)
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August 13th
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Renewing Inequality and Mapping Historical Data: Brent Cebul (History)
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Urban Analytics in Philadelphia: How can we use data to improve our cities? Shane Jensen (Statistics)
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Tutorial: Unstructured data and how to analyze texts - Sara Casella (Economics)