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Schedule of Upcoming Seminars

BLOCK 4 - November/December 2017

**Note: This block will feature talks predominately by candidates for Statistics Tenure Track position.**

Thursday, December 14th, 3pm
TSC 229

An Option Pricing Model With Memory
Flavia Research

Friday, December 15th, 12pm
TSC 122 Lecture Hall
(Pizza will be served!)

A Random Walk Through Probability and Statistics 
Flavia student

Thursday, November 30th, 3pm

TSC 229

Title: Computational Probability: Lifetime(s) of Research
Rated: PG-13 (with some R scenes)

Andy glen113017-1


Friday, December 1st, 12pm
TSC 122 Lecture hall

Title: A First Year Experience: Real World Solutions with Simulation
Rated: G

Andy glen113017-2

BLOCK 3 -October/November 2017

Friday November 10th, 2:30pm
TSC 229

Speaker: Kathy Merrill, Professor Emerita
Title: Wavelets for Crystallographic Groups
Rated: R


Friday November 3rd, Noon 12pm
TSC 122 Lecture Hall
with Pizza!


Speaker: Robert Gordon
Title: A sampling of Statistics at Intel Corporation
Rated: PG

Week 1: Kirsten Hogenson 

BLOCK 2 - September/October 2017

Friday October 6th, Noon - 1pm
TSC 122 Lecture Hall
Pizza will be provided! 

Speaker: Steven Janke, Professor Emeritus 
Title: "Celtic Knots: Drawing and Analysis" 
Rated:  PG (Some undergraduate mathematics or computer science knowledge assumed.)

Celitic knots


Friday September 29, 2:30pm
TSC 122 Lecture Hall

Speaker: Richard Koo, Visiting Assistant Professor

BLOCK 1 - September 2017

Friday September 15th,
Skilling Commons (TSC 2nd Floor)

Student Poster Session


Friday September 8th, Noon - 1pm
TSC 122 Lecture Hall

Department Research Overview, followed by an ICE CREAM SOCIAL in the Math/CS Lounge.
Thinking about writing a senior thesis? Or a summer research project? Come to the Fearless Friday this week to get an idea of what your professors are working on. Each department member will give a brief overview of their research and projects that students might get involved in. Followed by an ice cream social in the Math&CS Lounge.


Friday, September 1st at 2:30pm
TSC 122 Lecture Hall
 Assistant Professor Matthew Whitehead, Colorado College
Title: "Visualizing Artificial Neural Network Language Learning" 
Rated:  PG/PG13 (A lot of computer science knowledge assumed.)

Abstract:  When working with artificial neural networks that have complex structure, perhaps consisting of millions of parameters, it can be extremely difficult for humans to understand how the system is making decisions. For example, software emulating a pathologist may process visual biopsy data and classify a tumor as malignant, but it would have no ability to relay how and why that classification was made. In this talk, we will discuss a technique for visualizing what language processing deep artificial neural networks have learned and how they have learned it.