Jennifer Pawlewicz, Ithaca College Career Services

How to get a job, internship, or summer research experience

Students, have you ever wondered what opportunities are available for you, as a math major or minor?  Come find out about job, internship, and summer research opportunities.  Find out what's out there and how you can increase your chances of getting the experience you want!

Courtney Gibbons, Hamilton College

The Determinant Trick

Some people say there's more to life than linear algebra. They're not wrong — there are other types of algebra too! This talk will take one of those things everyone sees in linear algebra, the determinant, and use it in surprising ways for the noble purpose of proving a result (or two!) in commutative algebra. You don't need to know what commutative algebra is (it's better if you don't!) to enjoy this talk.

Tony Wong, Rochester Institute of Technology

Evaluating the Sensitivity of SARS-CoV-2 Infection Rates on College Campuses to Wastewater Surveillance

As college campuses reopen in Spring 2021, we are thrust into yet another large-scale experiment on the efficacy of various strategies to contain the SARS-CoV-2 virus. Traditional individual surveillance testing via nasal swabs and/or saliva are among the measures that colleges are pursuing to reduce the spread of the virus on campus. Additionally, some colleges are testing wastewater on their campuses for signs of infection, which can provide an early warning signal for campuses to locate COVID-positive individuals. We will discuss the implementation of a new model component for wastewater surveillance within an established epidemiological compartment model for the spread of COVID-19 on college campuses. We use a hypothetical residential university to evaluate the efficacy of wastewater surveillance for maintaining low infection rates. We find that wastewater sampling with a 1-day lag to initiate individual screening tests, plus completing the subsequent tests within a 4-day period can keep overall infections within 5% of the infection rates seen with weekly traditional individual surveillance testing. Our results also indicate that wastewater surveillance can be an effective way to dramatically reduce the number of false positive cases by identifying subpopulations for surveillance testing where infectious individuals are more likely to be found. Through a Monte Carlo risk analysis, we find that surveillance testing that relies solely on wastewater sampling can be fragile against scenarios with high viral reproductive numbers and high rates of infection of campus community members by outside sources. These results point to the practical importance of additional surveillance measures to limit the spread of the virus on campus and the necessity of a proactive response to the initial signs of outbreak.

Andrew Dykstra, Hamilton College

Complexity for symbolic dynamical systems

 In this talk, we will discuss dynamical systems that are symbolic in nature, meaning that points in the system are infinite sequences of symbols.  For example, the set of all possible infinite sequences of 0’s and 1’s, i.e., the set of all binary sequences, is a symbolic space which (as we will discuss) can be thought of as a dynamical system.  Whenever you have a symbolic dynamical system like this, it is natural to look for ways to measure how rich (or complicated) the system is.  One way of doing this is to calculate the entropy of a system. As we will see, even within the special class of systems that have entropy zero, it is still possible to distinguish among systems by measuring their complexity.  In particular, we will show how to use complexity to characterize important properties of systems such as recurrence, minimality, and transitivity.

Frank LiCausi,  Instructional Math Coach, Sweet Home Central Schools

Using math routines to build and deepen understanding

Jean Piaget once said, “Each time one prematurely teaches a child something he could have discovered himself, that child is kept from inventing it and consequently from understanding it completely.”

            Over the past 10 years, math education has undergone a major transformation towards Piaget’s ideal. As a math coach, it has been my role to convince both teachers and students this transformation is worth pursuing.  Our work is grounded in the math practices that will lend themselves to the critical thinking, problem solving and communication skills needed in today’s world. Today, we will explore some of the routines we have used to allow students to discover the and develop their own deep understanding of the world around us.

Nigar Altindis

Supporting students' meaningful understanding of functions: A learning ecology framework

In this talk, I introduce a learning-ecology framework that supports students’ meaningful understanding of functions. The learning-ecology framework consisted of three components: enacted task characteristics, teacher pedagogical moves, and small- and whole-group dynamics. In particular, I introduce enacted-tasks and tasks characteristics that might develop students’ meaningful understanding of functions.

Anca Radulescu, SUNY-New Paltz

Architecture-dependent bifurcations and clustering in brain networks

Modeling complex networks, and understanding how their hardwired circuitry relates to their dynamic evolution in time, can be of great importance to applications in the life sciences. However, the effect of connectivity patterns on network dynamics is only in the first stages of being understood. When the system is the brain, this becomes one of the most daunting current research questions: can brain connectivity (the “connectome”) be used to predict brain function and ultimately behavior?

We will start by describing an original study of neuroimaging data in humans, analyzing differences within a group of subjects with wide differences in vulnerability to stress (from extremely stress resilient to extremely anxious). Our statistical analysis found that connectivity patterns between prefrontal and limbic regions could explain differences in emotion regulation efficiency between the two groups. We interpret this result within the theoretical framework of oriented networks with nonlinear nodes, by studying the relationship between edge configuration and ensemble dynamics.

We first illustrate this framework on networks of Wilson-Cowan oscillators (a historic ODE model describing mean-field firing dynamics in coupled neural populations). We use configuration dependent phase spaces and probabilistic bifurcation diagrams to investigate the relationship between classes of system architectures and classes of their possible dynamics. We differentiate between the effects on dynamics of altering edge weights, density, and configuration.

Since Wilson-Cowan is a mean-field model, it can only predict population-wide behavior, and does not offer any insight into spiking dynamics and individual synaptic restructuring. To illustrate the effects of network architecture on dynamical patterns at this level, we test the same framework on networks of reduced Hodgkin-Huxley type single neurons. Building upon a model of cluster synchronization in all-to-all inhibitory networks (by Golomb and Rinzel), we study the contributions of more complex network architectures to the clustering phenomenon.

Chad Topaz, Williams College

Quantitative Approaches to Social Justice

Civil rights leader, educator, and investigative journalist Ida B. Wells said that "the way to right wrongs is to shine the light of truth upon them."  This talk will demonstrate how quantitative and computational approaches can shine a light on social injustices and help build solutions to remedy them.  I will present quantitative social justice projects on topics ranging from diversity in art museums to equity in criminal sentencing to affirmative action, health care access, and more.  I hope that this talk leaves you informed about the breadth of social justice applications that one can tackle using accessible mathematical tools.

Dave Gondek, Leann Kanda, Ted Galanthay;

Ithaca College

COVID Modeling at Ithaca College

Mathematical modeling of the COVID19 pandemic cases at Ithaca College was an essential tool in planning for our Fall '20 & Spring '21 Semesters. Join us to learn why modeling is critical in a public health response, which model to choose, and how cross-disciplinary skills are needed to work in a dynamic environment. Get answers to these questions, come with your questions, and find out how Ithaca College professors advised campus decision-makers on COVID testing policy.

Sedar Ngoma, SUNY-Geneseo

An Overview of Inverse Problems

 In order to find approximate solutions to problems emanating from science, engineering, mathematics, and many other fields, a process called model is described in detail and an appropriate input called a cause is supplied. One is then required to find the unique output (or approximate solution) called effect. This is known as direct or forward problems, in which the media properties of a given model described by equations (for example, equation coefficients) are assumed to be known. However, media properties are often not readily observable. This lack of specification in the model leads to inverse problems, in which one is required to find the cause of the effect given the effect. For example, one can try to determine the equation coefficients (which usually represent important media properties) from the information about solutions of the direct problem. 

One of the downsides of inverse problems is that their approximate solutions are almost always ill-posed in the sense that they may not be unique or stable. In this talk we introduce inverse problems, investigate some examples, and describe analytically and numerically a regularization technique used to combat instability in the solutions. We conclude the talk with a time-dependent inverse source problem for a parabolic partial differential equation.

Kenan Ince, Westiminster College

Analysis of racial and gender bias in SLCPD's use of force and street checks, 2014-2017

Using data shared by the Salt Lake City Police Department (SLCPD) related to use of force and street checks between 2014 and 2017, we utilize a chi-squared test to determine whether SLCPD uses force and street checks against Black and Indigenous people and people of color (BIPOC) disproportionate to their prevalence in the Salt Lake City population. We find that Black and Indigenous Salt Lakers are disproportionately targeted by police force, while Black Salt Lakers are disproportionately targeted by street checks. Asian and Pacific Islanders are underrepresented as subjects of both use of force and street checks.

Ahmad Almomani, SUNY-Geneseo

Hybrid Optimization Algorithms

The demand for Hybrid Optimization Algorithms is increasing in the last two decades to minimize the weaknesses in the individual algorithm. In particular, Derivative-Free Optimization (DFO) methods are applicable for these problems where the derivatives are not available or hard to compute. Hybridizing different stochastic methods to form a robust algorithm deals with slow convergence and minimizes problems.  This talk will introduce hybrid algorithms between global and local optimization solvers and give many real-life applications.