New Complex Systems Course:

Complex Systems, Biophysics and Physics Assistant Professor Jordan Horowitz, who joined us in January of 2019, will be teaching a brand new Complex Systems course starting Fall of 2019.  The course is part of Section IV: Theory & Methods of the Complex Systems Minor and qualifies as an elective for the Complex Systems Graduate Certificate.

CMPLXSYS 489.002 Course Description: 

As a general measure of uncertainty, Entropy finds diverse applications in numerous disciplines, such as physics, chemistry and biology.  This course will highlight many of these applications.  After introducing the basic notions of entropy and information, we will study the theoretical underpinnings of its many interpretations.   Illustrations of these ideas will be drawn from information theory, statistical inference, statistical mechanics, network theory, and biophysics. 

New Complex Systems Eligible Elective:

Complex Systems and Sociology Professor Elizabeth Bruch is also team teaching a new course in the fall.  The course is currently offered as SOC 295.002, and has been added to the list of approved Complex Systems electives.   The course will be found under Section II: Social Science of the Complex Systems Minor.

SOC 295.002 Course Description:

Due to the growth in electronic sources such as cell phones, Facebook Twitter, and other online platforms, researchers now have enormous amounts of data about every aspect of our lives – from what we buy, to where we go, to who we know, to what we believe. This has led to a revolution in social science, as we are able to measure human behavior with precision largely thought impossible just a decade ago. Computational Social Science is an exciting and emerging field that sits at the intersection of computer science, statistics, and social science. This course provides a hands-on, non-technical introduction to the methods and ideas of Computational Social Science. We will discuss how new online data sources and the methods that are being used to analyze them can shed new light on old social science questions, and also ask brand new questions. We will also explore some of the ethical and privacy challenges of living in a world where big data and algorithmic decision-making have become more commonplace. Each week, students will have the opportunity to try their hand at analyzing big data from sources ranging from online dating profiles to New York City taxicabs to #metoo Tweets and other sources. Note that this course is a 4-credit course that includes a weekly, 2-hour lab component in addition to lecture and discussion.