Category: Events

Title:  Electoral College Math:  How to Become President with 20% of the Popular Vote

Abstract: The Electoral College makes it possible to become U. S. President with less than a majority of the popular vote. In a two-candidate election, what is the minimal percentage of the popular vote possible for a winning candidate? In this talk we’ll first mimic an approach suggested by George Pólya that to find a theoretical solution. We’ll then make use of of tools not readily available to Pólya – spreadsheets and binary linear integer problem software — to see if we can improve on his results using actual presidential election data. Anyone with a vague recollection of high school algebra has the mathematical background necessary to enjoy this talk.

Title:  Sequential data mining

Abstract:  Data representing DNA, proteins, literature, weather, and the stock market all share one common characteristic: their data are sequential. Sequence data present some of the most challenging problems for machine learning and data mining methods. In this talk, Professor Brian King will present a generalized, probabilistic framework for modeling sequential data. He will show how he and his students have adapted this model for classification and prediction tasks, reporting results from recent studies.

Title:  Being fair in a world of limited resources

Abstract:  Fair division is a problem that all of us encounter regularly.  Every time you and another person or several people have to divide something – pizza, money, space, Neapolitan ice cream, band width, candy, etc. – you are working on a fair-division problem.  How can several people share a limited resource and make sure that no person feels the resulting allocation is unfair?   Before we can answer this question, we need to figure out what exactly is means to be ‘fair’.  The mathematical development of this subject is fairly recent and the results touch issues in economics and game theory. We will do lots of examples.

Title:  From airlines to healthcare: scheduling services with high variability

Abstract:  What do the airline and healthcare industries have in common when it comes to managing their capacity? What makes scheduling surgeries so much more difficult than an airline’s management of its seat inventory? How can hospitals improve their surgical scheduling system? While most optimization models suffer from the curse of dimensionality, simulation-based optimization is often a better choice when dealing with demand that is highly variable. Drawing from revenue management techniques developed by the airline industry, I will show how simulation modeling can help hospitals to more efficiently schedule surgical procedures, in order to better address and balance over- and under-utilization of their resources.

Title:  There’s Nothing Common About It

Abstract:  Training yourself to think like a child is often counterintuitive and surprisingly difficult.  My research focuses on helping preservice teachers analyze and learn from children’s mathematical thinking.  For this talk, we will focus on different types of story problems as described in the Common Core State Standards for Mathematics and discuss how children change their solution approaches depending on the situation presented in the problem.  We will watch videos of children solving different story problems and will consider various samples of written student work.  Audience participation will be encouraged.