## News & Events

## Tuesday November 13 at 4:30pm in SMudd 206

### Math Colloquium by Ralph Morrison, Williams College

**Title: ** Chip-firing games on graphs

**Abstract:**A graph is a collection of nodes connected by edges. In this talk I'll present a family of chip-firing games, which start with a placement of chips on the nodes of a graph. After placing the chips, we move them around by "firing" a node, meaning it donates a chip to each of its neighbors. This leads to many mathematical questions: Given two placements of chips, can we move between them using a sequence of chip-firing moves? If so, what's the fastest way? It not, how can we prove it's impossible? And if some of the nodes start with a negative number of chips, can we perform chip-firing moves to get those nodes out of debt? This talk will showcase many results and open questions about these chip-firing games, including new theorems proved by undergraduates in Summer 2018.

## Wednesday November 7 at 4:30pm in SMudd 206

### Math Colloquium by Alyssa Crans, Loyola Marymount University

**Title**: Pizza Numbers!

**Abstract**: Our goal is to experience firsthand the joy, frustration, and creativity involved in exploring a question as a mathematician does. We’ll begin with a simple puzzle: If we slice a pizza with n straight line cuts, what is the maximum number of pieces we can make? Discovering these pizza numbers will inspire us to ask a variety of related questions, some of which we’ll answer and others of which will lead to unsolved problems at the level of current mathematical research!

Refreshments will be served at 4:00 pm in Seeley Mudd 208.

## Monday November 5 at 7:00pm in Science Center E108

### Math Club - first meeting of the year

## Monday November 5 at 4:00pm in Science Center A131

**Talk by Matteo Riondato**, who will join Amherst as an Assistant Professor in January 2019

**Title**: "Data Mining: Tasks, Systems, Challenges, and Research Directions"**Abstract**: In this talk, I describe the field of Data Mining (DM) from the point of view of a researcher in this discipline. Starting from my definition of DM, I give examples of DM tasks for different kinds of data, commenting on available systems for DM and discussing the algorithmic challenges in DM. I show how my research tackles some of these challenges and list the interesting questions I plan to answer in the near future with the help of Amherst students.

## Thursday November 1 at 4:30pm in SMudd 206

### Connecticut Valley Colloquium

#### Melody Chan, Brown University

**Title**: The Moduli of Space Curves**Abstract**: I will give a prerequisite-free introduction to the idea of a moduli space. Then I'll introduce the moduli space of algebraic curves of genus g, a space that has connections to many areas of mathematics and has been studied intensively, yet remains mostly a mystery. In recent joint work with Søren Galatius and Sam Payne, we obtained new results on the cohomology of Mg

Refreshments will be served at 4:00 pm in Seeley Mudd 208.

## Thursday November 1 at 4:30pm in SMudd 207

### Statistics colloquium by Krista Gile (UMass Amherst Mathematics and Statistics Dept)

**Title**: Inference from Multivariate Respondent-Driven Sampling Data

**Abstract**: Respondent-Driven Sampling is type of link-tracing network sampling used to study hard-to-reach populations. Beginning with a convenience sample, each person sampled is given 2-3 uniquely identified coupons to distribute to other members of the target population, making them eligible for enrollment in the study. This is effective at collecting large diverse samples from many populations. Due to the complexity of the sampling process, inference for the most fundamental of population features: population proportion, is challenging, and has been the subject of much work in recent years, typically using only data on local network size and the variable of interest. This talk focuses on work that considers inferential goals addressed using multiple variables measured on participants. We describe using data on local network composition for a variable biasing recruitment to adjust for preferential recruitment, semi-parametric testing for bivariate associations in the RDS dataset, and methods for clustering RDS participants based on covariate and referral data.

Refreshments will be served at 4:00 pm in Seeley Mudd 208.

## Wednesday October 31 at 4:30pm in SMudd 206

### Math colloquium by Marshall Ash

**Title**: Discontinuous functions as limits of compactly supported formulas

**Abstract**: A bounded real valued function with domain the entire real numbers and one point of discontinuity can be discontinuous in six ways. In beginning textbooks such functions are usually defined piecewise with each piece being given by a formula. Here we give six examples, each having a different type of discontinuity at its unique point of discontinuity. Each example type is represented as a pointwise limit of quite simple continuous functions. Each approximating function can be given by an elementary formula and also can be chosen to be of compact support. (A function has compact support if the set of points where it is non-zero is contained in some finite interval.)

Refreshments will be served at 4:00 pm in Seeley Mudd 208.

## Friday October 26 3:30-5pm in SMudd 206

### Math & Stats Family Weekend Reception

## Wednesday October 24 at 4:30pm in SMudd 206

### Math colloquium by Christina Frederick, New Jersey Institute of Technology

**Title:**Aliasing in sampling theory and applications

**Abstract:**The area of inverse problems can be thought of as the “Jeopardy!” of mathematical research. Instead of trying to find solutions to complicated equations, the theory of inverse problems attempts to do the opposite: given solutions to equations, what are the equations themselves? Just as many questions have the same answer, it is true that many different equations have the same solution, making inverse problems extremely challenging to solve. In this talk I’ll describe the inverse problem of sampling continuous signals, and how to guarantee a perfect reconstruction by preventing the occurrence of “alias” signals.

## Tuesday October 23 at 4:30 pm in SMudd 206

### Statistics colloquium by Matthew Rattigan, Center for Data Science at UMass

**Title**: Data Science for Political Campaigns

**Abstract**: In recent years, presidential campaigns have become increasingly quantitative in nature. Once dominated by a small group of backroom strategists making gut decisions, modern campaigns have become increasingly reliant on data-backed decision support. Over the past two decades, this "moneyball-ization" of politics has transformed the way campaigns are run and how resources are allocated. In this talk, I will describe my experiences working for the Analytics Department of Obama For America during the 2012 election cycle. As a digital analyst, I worked alongside political scientists, statisticians, and physicists on problems ranging from social media analytics to quantifying the effects of communications and messaging. In addition, I'll touch upon some of the privacy issues brought up in the 2016 election cycle.

## Saturday September 22

### StatFest 2018 at Amherst College

STATFEST 2018 is a one day conference aimed at encouraging undergraduate students from historically underrepresented groups (African American, Hispanic, Native Americans) to consider careers and graduate studies in the statistical and data sciences. It includes presentations from established professionals, academic leaders, and current graduate students that will help attendees understand the opportunities and routes for success in the field. Many opportunities for networking will be created. Attendees are also encouraged to submit poster presentations. Panel forums provide information and tips for a rewarding graduate student experience, achieving success as an academic statistician or data scientist, and opportunities in the private and government arenas, among other topics.

StatFest 2018 will be taking place on Saturday, September 22nd. We are excited that StatFest 2018 will be held at Amherst College. Registration is free (but preregistration is required). More information can be found at: https://nhorton.people.amherst.edu/statfest.

## Thursday September 20 at 4:30pm in Mudd 206

### Math Colloquium by Doug Ensley

The MAA Instructional Practices Guide: A Resource for Change**Abstract**: The MAA Instructional Practices Guide presents evidence-based

methods for engaging students. Beyond documenting active-learning

classroom strategies, the guide also includes practices for assessment

and course design that support these strategies. This presentation will,

of course, include an overview of the guide, but be sure to bring a

pencil. Throughout the period, we will be putting some of the practices

into, well, practice.

Refreshments at 4 pm in SM 208

## Monday September 17 at 4:30pm in Mudd 206

### Math Colloquium by Prof Rob Benedetto

The*abc*Conjecture: An Introduction

**Abstract:**The

*abc*-conjecture is a straightforward statement about the prime factors of integers

*a*,

*b*, and

*c*satisfying the equation

*a+b*=

*c*. In spite of the simple name, simple equation, and simple statement, the conjecture is an important problem in number theory and is quite difficult. In this talk, we will motivate and state the

*abc*-conjecture. To help us along, we'll look at the related case of putting polynomials, rather than integers, in the roles of

*a*,

*b*, and

*c*. We'll also present some evidence supporting the conjecture, as well as some of its uses in number theory.

## Friday September 14 3:00-4:30pm in Ford Hall

### Math and Stats Welcome Tea

Searchable calendar of events in the Five College area.