Talks (unless otherwise indicated) are in Davis 301 from 4–5 PM on Mondays. Refreshments begin at 3:30 on the second floor of Davis.

To make sure you get email updates, add yourself to the mathstu (if a student) or mathothers (if not) email groups. Or check the Colby Math&Stats facebook page.

You can see last semester’s schedule.

**Sept. 10**

Scott Taylor

Colby College

*The mathematics of knotted objects
*

### Title

### Abstract

**Sept. 17**

Stephanie Eaneff

Talus Analytics

*What does the Biological Weapons Convention have to do with statistics?
Case studies in data science and public policy
*

### Title

### Abstract

**Sept. 24**

*Colby Student Summer Research
*

### Title

### Abstract

Shabab Ahmed ’19: Solvability of Polynomials

Simon Xu ’20 and Alice Gao ’20: Convex Neural Code

Charles Parham ’20 and Qidong He ’21: Knot Invariants

**October 1**

*Meet our new faculty!
*

### Title

### Abstract

Ariel Keller

Gabi Bontea

George Melvin

Jerzy Wieczorek

**Oct. 8**

Thiago Serra

Mitsubishi Electric Research Labs

*Bounding and Counting Linear Regions of Deep Neural Networks*

### Title

### Abstract

–

Joint work with Christian Tjandraatmadja (Carnegie Mellon University, now at Google) and Srikumar Ramalingam (The University of Utah), presented at the 35th International Conference on Machine Learning (ICML 2018).

**Oct. 11 (Thurs.)**

Danny Rorabaugh

University of Tennessee

*Integer Sequences
*

### Title

### Abstract

The number of neutrons in the most abundant isotope of each element on the periodic table: {0, 2, 4, 5, 6, 6, 7, 8, 10, 10, 12, …}. The year in which the population of earth reached n billion: {1804, 1927, 1959, 1974, 1987, 1999, 2011(, …?)}. Integer sequences are everywhere. Can you figure out what this sequence represents: {3, 3, 5, 4, 4, 3, 5, 5, 4, 3, 6, …}?

In this talk, we share the joys of studying integer sequences and tools available for investigation. With sequences, you can practice programming and make connections between disciplines; they are the source of both silly puzzles and deep, unsolved mathematical questions.

**Oct. 22**

Helen Wong

Claremont McKenna

*It’s not algebra, it’s knot algebra
*

### Title

### Abstract

**Oct. 29**

Chris Moore

Colby College (*Biology*)

*Tempering positive feedback in population models of mutualism
*

### Title

### Abstract

**Nov. 5**

Statistics Candidate

*Regression Methods for Network Indexed Data: Modeling Occurrences of Burglary in Boston, Massachusetts
*

### Title

### Abstract

After defining and giving examples of network data, we introduce our motivating example: modeling occurrences of residential burglary in Boston, MA. Viewing the city of Boston as a network of streets and intersections, we discuss a generalized linear model composed of vertex indexed predictors. We introduce the graph Laplacian as a regularization tool and briefly discuss the interpretations of our proposed model.

**Nov. 9 (Friday) ****Davis 201**

Statistics Candidate

*A casual approach to real-world data: emulating randomized trials in SEER-Medicare*

### Title

### Abstract

Hernán, M. A., & Robins, J. M. (2016). Using big data to emulate a target trial when a randomized trial is not available. *American journal of epidemiology*, *183*(8), 758-764.

Warren, J. L., Klabunde, C. N., Schrag, D., Bach, P. B., & Riley, G. F. (2002). Overview of the SEER-Medicare data: content, research applications, and generalizability to the United States elderly population. *Medical care*, IV3-IV18.

**Nov. 15 (Thursday) **

Statistics Candidate

*ARGO2: Accurate, real-time flu tracking with Internet search data
*

### Title

### Abstract

**Nov. 19**

Statistics Candidate

*Modeling Forensic Fingerprint Decisions with Item Response Theory
*

### Title

### Abstract

There are, however, fundamental differences between forensic science applications and traditional IRT settings. In this talk, I will discuss these differences and demonstrate the use of IRTrees, a tree-based IRT framework, to account for these differences. I will also discuss the utility of such an approach in the forensic science domain.

**Dec. 3**

Milja Poe

*On S-unit Equations
*

### Title

### Abstract

We will be studying S-unit equations, in particular the equation:

We fix a finite set of prime numbers, for example 2,3, and 5. We assume that X and Y are both S-units, in rational numbers. This means that X and Y are rational numbers such that their numerators and denominators factor into primes only in the set S. So if S is the set 2,3, and 5, then 1/4 + 3/4 =1, and 1/5 + 4/5 =1 would be solutions to the S-unit equation above.

We want to study the number of solutions, and their distribution, of the above S-unit equation. And how these solutions might depend on the set S.