All meetings will be virtual, Mondays at 4pm. zoom link



All meetings will be virtual, Mondays at 4pm. zoom link



All meetings will be virtual, Mondays at 4pm. zoom link
Date  Speaker  Title  Abstract 

9/28/20  Peter Maceli  Graphs and Algorithms  Graph theory is a young and exciting area of discrete mathematics. Visually, a graph is just a collection of dots together with lines joining certain pairs of these dots. Though at first glance graphs may seem like simple objects to study, the field of graph theory contains some of the deepest and most beautiful mathematics of the last fifty years. Being an extremely visual field, many questions and problems in graph theory are easily stated,yet have complex solutions with far reaching implications and applications.In this talk, we will explore the close relationship shared between graphs and algorithms. Describing how certain families of graphs “look” and can be“built,” and how, in turn, this allows one to efficiently solve certain important combinatorial problems. 
10/5/20  A Virtual Escape Room  Today we change gears from our typical talk. We'll break into teams to try out a virtual escape room! If you have a team in mind, email Matt Thomas (mthomas7@ithaca.edu) with your team. Otherwise, just show up and we'll make some teams!  
10/12/20  Priya V. Prasad, University of Texas at San Antonio  Teaching Geometric Congruence  Euclid and Hilbert both based their developments of axiomatic geometry on metric definitions of congruence, but current state standards (such as the Common Core State Standards for Mathematics and the Texas Essential Knowledge and Skills Standards) implicitly rely on an isometric definition of congruence. So how can teacher educators prepare future secondary geometry teachers to teach an axiomatically coherent geometry based on this definition? We developed a task using Taxicab geometry that can perturb students’ internalized metric definition of congruence. This talk is based on work done with Steven Boyce at Portland State University. 
10/19/20  Benjamin Levy, Fitchburg State University  An Introduction to Disease Modeling with an Application to HIV/AIDS in Kenya 
One can use mathematical techniques to model disease outbreaks such as COVID19, Ebola, or HIV/AIDS. We can then use model simulations to make future projections about the number of cases, consider the impact of intervention strategies, or analyze other key characteristics of an epidemic. This presentation will begin by introducing the compartmental framework commonly used to model infectious diseases, which will be illustrated by some simple models. After we lay some groundwork, a specific application to modeling HIV/AIDS in Kenya will be presented. In this application we formulate a compartmental system of ordinary differential equations (ODEs) to consider how stigma towards people living with HIV/AIDS has impeded the response to the disease. We take a datadriven approach to embed a timedependent stigma function within our model for HIV dynamics and estimate model parameters from published data. We then explore a range of scenarios to understand the potential impact of different public health interventions on key HIV metrics such as prevalence and diseaserelated death, and to see how close Kenya will get to achieving UN Goals for these HIV and stigma metrics by 2030. 
10/26/20  Emilie Wiesner, Ithaca College  Ping Pong and Sleeping Beauty: Playing with Paradoxes  We'll spend the first part of the hour thinking and talking about ping pong and Sleeping Beauty (two of my favorite paradoxes). The second part of the hour we'll have some paradox show and tell, so come prepared with your own favorite paradox. 
11/2/20  John Gemmer, Wake Forest University  Why is Lettuce so Wrinkly?  Many patterns in Nature and industry arise from the system minimizing an appropriate energy. Examples range from the periodic rippling in hanging drapes to the sixfold symmetries observed in snowflakes. Torn plastic sheets and growing leaves provide striking examples of pattern forming systems which can transition from single wavelength geometries (leaves) to complex fractal like shapes (lettuce). These fractal like patterns seem to have many length scales  the same amount of extra detail can be seen when looking closer (“statistical selfsimilarity”). It is a mystery how such complex patterns could arise from energy minimization alone. In this talk I will address this puzzle by showing that such patterns naturally arise from the sheet adopting a hyperbolic nonEuclidean geometry. However, there are many different hyperbolic geometries that the growing leaf could select. I will show using techniques from analysis, differential geometry and numerical optimization that the fractal like patterns are indeed the natural minimizers for the system. 
11/16/20  Gabe Pesco, Rachel King, and Jake Brown  Summer research/jobs panel  Come join us to hear about some of the work being done over the summers! Hear about what they did, and how they applied for and did their work. Ask questions to start thinking about what you might do next summer. 
12/7/20  Mingyue Wang, Incyte  On selecting the t best Bernoulli Treatments 
In many situations we are faced with the problem of choosing among several alternatives. We may want to make a decision about which alternative(s) are the best. Considering a typical clinical trial setting, we set the goal of selecting among k ( > 0) experimental Bernoulli treatments the t (1 < t < k) best treatments provided that they are significantly better than the control. If fewer than t treatments are significantly better than the control, our goal is to retain the control. A fixedsamplesize procedure and a curtailed procedure are proposed to reach the goal. We adopt the twostage selection/testing approach considered by Thall, Simon, and Ellenberg (1988) in both procedures. Properties of the proposed procedures will be presented through theorems and numerical results. 
Date  Speaker  Title  Abstract 

Feb 17, 2020  Xingye Qiao, Binghamton University  Data Science in Action: Setvalued Classification and Applications to Precision Medicine  Classification is a common machine learning task. Precision Medicine refers to selecting treatments that are most likely to help patients based on the patient's unique characteristics. In this lecture, I will talk about the fundamentals of classification, setvalued classification, and how the latter can be applied to achieve precision medicine. I will also talk about the research and education development of data science programs at Binghamton University. No particular knowledge is needed for the talk though knowledge of probability theory and some linear algebra will be helpful. 
March 2, 2020  Megan Martinez  Crocheting Mathematics  Crocheting is a process that turns yarn into fabric. It has been used for centuries to painstakingly create oneofakind fabrics and clothing. More recently, the art of crochet has been used to create physical models of mathematical structures, such as hyperbolic planes, spheres, and manifolds. This provides us a tactile (and crafty!) way to engage with mathematics; indeed, the very process of making a crochet pattern requires a deep understanding of the model you are constructing. In this talk, we will give an overview of different ways crochet has been used to make models, and then dive specifically into how we can construct patterns for volumes of revolution (the ones from Calc II!). 
April 20, 2020  Stan Seltzer, by zoom  click here  Gerrymandering  Every ten years the United States conducts a census, after which the 435 seats in the House of Representatives are apportioned to the states. The final step in all but the very smallest states that are entitled to one representative is the process of dividing each state into the appropriate number of congressional districts. (State, county, and municipal districts may also have to be redrawn.) When districting is done in a way intended to establish an unfair political advantage for a particular party or group by manipulating district boundaries, it is known as gerrymandering.
This brief introduction, based on the gerrymandering unit in Math, Fairness, and Democracy (MATH 16400), will include redistricting principles, gerrymandering strategies, historical and legal background, and some topics that are more mathematical: winner’s bonus, partisan symmetry, efficiency gap, and measures of compactness. Also lots of pictures and quotes. 
Date  Speaker  Title  Abstract 

Sept 16, 2019  Dave Brown  American Revolutionary and Civil War Cryptography 
“One if by Land Two if by Sea” This line from Longfellow’s poem describes a secret signal to the patriots about approaching British troops and goes on to commemorate Paul Revere’s Midnight Ride. At the same time, the poem reveals that Revere served as a spy and that the colonists engaged in early attempts at cryptology — sending, receiving, and decoding secret messages. We will explore the role that spycraft and cryptology played in the American Revolution and in the U.S. Civil War. 
Sept 30, 2019  Molly Noel and Jamie Woodworth  Summer Research  Molly and Jamie will share their experiences from their summer research. 
Oct 14, 2019  Ted Galanthay 
Shall we play a game? Hawks, Doves, and More 
In the 1960's, ecologists began to use game theory to study evolutionary questions on topics such as animal aggression, the sex ratio, and altruism. Further study led to the creation of evolutionary game theory. In contrast to traditional game theory, evolutionary game theory seeks to describe changes in the frequency of strategies over repeated iterations of a game. Typically, the number of players in the game is fixed. In this talk, I will describe recent efforts to integrate population dynamics and evolutionary game theory models to answer questions about the evolution of animal aggression. 
Oct 28, 2019  Math Department  Preview of Spring Courses  Join the department to hear about the courses being offered in the spring! 
Nov 11, 2019  Josh Hayden and Heetisha Inderjeet  Two Part Talk On Mathematics and Community 
Part 1: Data and Donations, Joshua Hayden A talk on using data to help project donations and find top donor prospects for the Ithaca State Theatre. How data analysis and machine learning can be put to work in the nonprofit space to help communities. Part 2: Application of Math in Real Life, Heetisha Inderjeet As a math major, people sometimes expect that the only career goal is to teach. However, math can be a career in different ways. This project which involves working with Matthew LeRoux from the Cornell Cooperative Extension (Tompkins County) is a good example. This project consists of working with the cooperative extension partner to evaluate a meat pricing calculator and drill down on significant statistical numbers which will be able to be used for workshops and grant writing. 
Dec 2, 2019  Xingye Qiao, Binghamton University  Postponed due to snow 