3rd Annual WSU Data Visualization Expo

Students in our DSCI 310: Data Summaries & Visualization course are participating in this event. Due to COVID restrictions, this event is happening online using the Gather.Town app.

Student Seminar

12:00 - 12:50 PM, Wednesday, Nov 18 , via ZOOM

Data & Market Analyst Internship at Cytilife, Inc Stephen Masha
I had an opportunity to work as an intern with Cytilife, Inc as a Data & Market Analyst this past summer. During this period, I conducted research on wearables that was crucial to acquiring data, retrieved and cleaned data from the database, modeled data, and conducted a market analysis for a new app, and offered business‐to‐business support. My internship was not limited to just data science tasks. In this presentation, I will take you through my internship experience and other opportunities at Cytilife, Inc.

Student Seminar

12:00 - 12:50 PM, Wednesday, Nov 4 , via ZOOM

2020 Summer Internship at U.S. Bank Sarah Lauwagie
I will be talking about my 2020 Summer Internship at U.S. Bank as a Business Analyst on the Mortgage Development and Support team. During my time there, I worked with the Mortgage IVR system and analyzed its process maps. I found areas for improvement and presented them to the business line with approval to move forward. Also, I had the opportunity to participate in a case competition with 91 teams regarding marketing to Millennials.

Dr. Kerby Awarded NSF Grant to Support Statistics and Data Science Education

Dr. April Kerby, a professor in the Department of Mathematics and Statistics at Winona State University, has been named as a co-principal investigator on a $600,000, three-year National Science Foundation grant supporting the Motivational Attitudes in Statistics and Data Science (MASDER) project.

With the ever-growing demand for professionals with the necessary skills to turn data into knowledge, statistics and data science have become two of the fastest growing fields worldwide, with a high demand in the U.S. specifically. Understanding students’ attitudes towards these subjects can be crucial for developing effective pedagogies in these areas and inspiring students to pursue a career in these fields.

MASDER will create a family of instruments in both statistics and data science to measure teaching and learning through data collected about students and instructors, in addition to the learning environment.  These instruments, which Kerby hopes will become a “go to” resource for assessing students’ attitudes towards statistics and data science, will be publicly available to instructors and researchers to help inform their teaching and improve those attitudes.

Kerby looks forward to involving undergraduate students in the project and is excited for what they will be able to contribute as well as gain from the experience. “I hope that students will get to utilize their programming skills to help us create customizable reports which will be available to the instructors who have their students take the survey.”

During her time at Winona State University, Dr. Kerby has helped create the undergraduate Data Science program, one of the first in the Midwest.  Her research has primarily focused on students’ attitudes towards statistics in relation to introducing a “Problem of the Week” into the introductory statistics course and she has published her findings in the Statistics Education Research Journal.

Source

2020-2021 Distinguished Lecturer in Mathematics and Statistics

Dr. Lisette de Pillis

Harvey Mudd College

Mathematical Medicine:  Modeling Disease and Treatment

Abstract:  Immune system dynamics have proven to play an increasingly central role in the development of new treatment strategies for immune-related diseases such as type 1 diabetes and certain cancers.  The critical importance of the immune system in fighting such diseases has been verified clinically, as well as through mathematical models.  Many open questions remain, however, including what may lead to non-uniform patient responses to treatments, and how to optimize and personalize therapy strategies.  Mathematical models can help to provide insights into the mechanisms that may be influencing patient outcomes.  In this talk, we will present a sampling of mathematical models that help us to simulate immune system interactions, disease dynamics, and treatment approaches that may slow, or even stop, disease progression.

Wednesday, October 28^th,
12:00—12:50 pm via Zoom

Student Capstone Presentation

12:00 - 12:50 PM, Wednesday, June 3, via ZOOM
(contact Dr. Malone for Zoom link)

NFL Rushing Analytics Aaron Augustine
For my project, I studied various predictors that influence rushing yards in the National Football League. I used Random Forests to predict the number of yards gained on a rushing play. I will talk about the steps I went through to clean and prepare the data, my model building processes, and some issues that I encountered along the way. Visualizations were constructed to further investigate some of the more important predictors in the model.

Dr. Hooks Awarded WSU Professor of the Year

Winona State University statistics and data science Professor Tisha L. Hooks has been selected as Professor of the Year.

The Professor of the Year designation is awarded annually by the WSU Student Senate on behalf of the student body. Students vote for a professor that goes above and beyond for their students. These professors serve as exemplars in being accommodating, accountable, engaging to students, making an effort to have their curriculum relevant to daily life, and aiming to make their courses affordable for students to participate in. This award is run through Student Senate, but it is voted and decided by all students.

A professor in the WSU Department of Mathematics and Statistics, Hooks has been teaching at Winona State since 2006. She received her Bachelor of Science degree in Mathematics from the University of Nebraska at Kearney and a PhD in Statistics from the University of Nebraska – Lincoln.

Hooks, who initially had no intention of teaching, heeded the call to the classroom during graduate school, and she has never looked back. “Showing students the value of statistics and helping them succeed – especially when they thought they couldn’t, was extremely fulfilling. It still is today.”

Initially taken by surprise, Hooks is honored and grateful to have been chosen among “so many gifted teachers across campus…we pour so much of ourselves into our jobs as educators, and though we don’t expect to be recognized for our efforts, hearing that we have made a difference certainly helps to fill us back up again.”

Hooks honors the collective experience and professional collaboration of her WSU colleagues, with special thanks to her fellow statisticians and data scientists, saying “They are continually striving for excellence, which also pushes me to be the best teacher I can be. Together we have spent countless hours developing a curriculum that is relevant, engaging, and effective.”

“This award is special to me because it comes from the students, confirmation that I am helping students in the ways I had hoped when I changed my career path years ago. I just feel lucky to be a part of it all.”

Source

Student Capstone Presentation

12:00 - 12:50 PM, Wednesday, April 29, via ZOOM
(contact Dr. Kerby for Zoom link)

Implementing SQL for Table Toolz, Project Structures for Data Science Daniel Lew
I will be talking about implementing SQL for Tabletoolz, which is a data manipulation library inspired by R’s Dplyr in Python, what I did and what I learned from the project. Also, I will be sharing about using a project structure for data science.

Internship Presentations

12:00 - 12:50 PM, Friday, April 24, via ZOOM
(contact Dr. Kerby for Zoom link)

Internship Experience: Supply Chain Intern at Fastenal Danielle Buoy
Fastenal, an industrial supplies company based in Winona, MN has worked for years distributing goods used by hundreds of businesses. Inventory movement is emphasized in their supply chain department, where I’ve contributed my internship skills. Handling product redistribution amongst the branches, facilitating vendor returns, and assisting with liquidations of non-moving parts are three main areas of focus. An essential part of the process as a whole is to minimize and reduce noncontributing inventory via utilization of programs, tools, and databases. Optimization of productivity and profitability throughout the company is a major takeaway of my supply chain duties.
Internship: Fastenal Supply Chain and Data Team Peyton Schumacher
	I will speak about my duties at Fastenal as a Supply Chain Analyst and Data Team Member, as well as creating and refining new and existing processes in our Supply Chain.

Student Capstone Presentations

12:00 - 12:50 PM, Wednesday, April 22, via ZOOM
(contact Dr. Kerby for Zoom link)

Methods of Data Imputation Carson Howells
Imputation is the process of filling in missing values in data sets. This project is exploring which method of data imputation is best for different data types.
Deep Learning Classification of Retina Images: Detecting Diabetic Retinopathy Mikolaj Wieczorek
	Diabetic retinopathy (DR) is a common eye disease that causes vision loss for people with diabetes. It is one of the fastest growing causes of preventable blindness, and about 45% of Americans diagnosed with diabetes have some stage of DR. As the disease has no symptoms in early stages and treatments begin after the vision is already somewhat affected, early detection is of pivotal value to diabetic patients. The aim of this project is to build a deep learning classification model that could assist in early detection and severity grading of DR. The final results are obtained by implementing a Dense Convolutional Network Architecture model that yields 98% classification accuracy. Further study is being considered with application of larger training data and to deploy the final model as a web app.

Student Capstone Presentations

12:00 - 12:50 PM, Wednesday, April 15, via ZOOM
(contact Dr. Kerby for Zoom link)

Using Natural Language Processing to Analyze News Bias Bradley Erickson
As we live in the information age, finding reliable information becomes more and more difficult. All news sources contain bias, thus anything someone reads could be misinformation or interpreted differently. This research scrapes thousands of articles from many sources relating to 5 controversial topics: the impeachment, abortion, immigration, gun control, and climate change. We use unsupervised learning techniques to rank and filter out the top sentences by giving more weight to unbiased, more credible sources. This information will form an extractive-based summary. Finally, we compare the language used among 3 bias groups: left bias, no bias, and right bias. The research provides insights into the current bias state of news reporting.
Social Influence and the Freshman Experience Adam Funk
	We investigated the relationship between time at a university and who freshmen are most influenced by at that given time. The study took a subset of 1000 freshmen from the Winona State University class of 2023 and asked about different influence factors and changes in behavior over the course of 10 weeks. Different surveys were sent out at 1 week, 3 weeks, 6 weeks, and 10 weeks. Questions on who they were influenced by, both negatively and positively, were asked, as well as groups they were a part of and whether they felt they had changed as a person. We also attempted to monitor the change over time of specific individuals through an identification code, which was unsuccessful. However, summary statistics of each time point were successfully collected and reported.

Student Capstone Presentations

12:00 - 12:50 PM, Wednesday, April 8, via ZOOM
(contact Dr. Kerby for Zoom link)

Identifying Pulsar Stars Alexander Phillips
Pulsar stars, neutron stars that appear as rhythmic pulses of radio waves, are of great importance to astronomers as measuring devices. Scientists from two observatories in Australia and Germany compiled a dataset of 17,898 potential pulsar signals, recording data on each signal’s integrated profile and dispersion measure. This study considers variations on a logistic regression model to classify radio signals as pulsar stars or noise. The optimal predictive model considers the mean, standard deviation, skewness, and kurtosis of both the integrated profile and the dispersion measure, though a model with only the four best predictors also reaches a high level of accuracy.
Analyzing Filings Sentiment for Applications in Finance Marshall Will
	There has been increasing use of using sentiment in financial reports to create a better understanding of what is being read and how that can affect market prices. Analyzing sentiment for financial research has been around for a while, but over the past decades, there has been an increasing interest in looking at how changes in sentiment can affect market prices. Past research has shown that measuring sentiment can be used to generate Alpha and gauge a firm’s fundamentals. For my capstone, I looked at the sentiment of 10-K and 10-Q filings for publicly traded securities in the NASDAQ and NYSE from 1993 to 2018 to see if it is possible to predict if a security will rise in price based on the change in word sentiment in these public filings.

Student Capstone Presentations

12:00 - 12:50 PM, Wednesday, April 1, via ZOOM
(contact Dr. Kerby for Zoom link)

Data Analysis of the Arbitration Process in the MLB Alex Riles
The arbitration process in Major League Baseball is used to prevent holdouts and prolonged disputes. The ability to predict the outcome of the hearing will help the players and teams know where they stand. This could change the amount a player or team submits, so the outcome could turn in their favor. This project used Neural Network and Random Forests models to investigate whether a predictive model is worth using to predict the outcome of arbitration. Results indicated that Neural Network and Random Forests models can be used to predict the outcome of the arbitration process with a low misclassification rate.
Modelling Baseball Players’ Likelihood of Being Inducted into the Hall of Fame Connor Demorest
	I used logistic regression to model the probability a player will be inducted into the Hall of Fame. I found that my model has 96% accuracy when cross validating on players already in the Hall of Fame, and I discuss the implications of players who are still playing or not yet eligible. I determined what characteristics were most important to Hall of Fame voters and which were not. I identified several players who are not in the Hall of Fame yet and make a case for them to be inducted.

Department Colloquium

12:00 - 12:50 PM, Friday, February 28, Gildemeister 155

Refreshments served beforehand Gildemeister 135. 

Two Research Projects Birthed from

Curiosity, Recreation, and Joy

Dr. aBa Mbirika

Univ. Wisconsin—Eau Claire

 

This talk will center around two undergraduate research projects born from recreational math topics. The first project emerged from a connection between the Fibonacci sequence modulo 10 and astrology. The second project arose from noticing the magical and mystic golden ratio appearing as an eigenvalue of a certain tridiagonal real symmetric matrix. A cute connection between the two topics will be revealed at the end of the talk.

Student/Faculty Social/Trivia Night

Internship Presentations

12:00 - 12:50 PM, Wednesday, February 19, Gildemeister 155

Refreshments served beforehand Gildemeister 135. 

 

Data Science Internship: Tuohy Furniture Adam Clemens
I will describe the tasks that I performed and what I learned from my internship experience. I will also talk about the software and skills that I used on the job.
Internship at Fastenal: Fastbin Research Nina Horabik
	I worked on various projects to gain more insight about how Fastenal’s Fastbins work, and to help Fastenal improve Fastbin technology in future versions.

Guest Speaker

12:45 - 1:50 PM, Thursday, February 13, Gildemeister 329

Refreshments served beforehand Gildemeister 319. 

Sensitive Dependence on Initial Conditions
A Ski Jumping Story 

Greg Windsperger Former Olympic Ski Jumper and Former Head Coach of US Men’s Olympic Ski Jumping Team Greg will talk about his unique history of growing up ski jumping in north Minneapolis which lead to his participation in the 1976 Olympics and his eventual position as the US men’s ski jumping coach for the 1984 and 1988 Olympic games. During Greg’s time as head coach, the US team saw their most successful results. He will also talk about how math, science, and collaboration has revolutionized the sport since its inception in Redwing, MN in 1887.

Department Colloquium

12:00 - 12:50 PM, Monday, February 10, Gildemeister 155

Refreshments served beforehand Gildemeister 135. 

Mathematical Colorings from Ramsey Theory

Dr. Darren Row
  St. Mary’s University

 

The topic of Ramsey Theory will be presented through exploration of some typical problem types. Known results, open problems, and proof strategies will be discussed. Special attention will be paid to Ramsey Numbers and Rado Numbers. Audience participation will be encouraged. Crayons are optional.

Internship Presentations

12:00 - 12:50 PM, Wednesday, February 5, Gildemeister 155

Refreshments served beforehand Gildemeister 135. 

 

Internship: Fastenal Data Team Katelin Catton
I will describe my internship duties and responsibilities as a Supply Chain Analyst, and will discuss a report analyzing inventory at all Fastenal Stores in the United States.
Internship: Medxcel Samantha Matera
	I worked with a team to create a benchmark for Medxcel's facilities, as well as completing other solo side projects that I will describe in this talk.

Student Presenations

12:00 - 12:50 PM, Wednesday, January 22, Gildemeister 155

Refreshments served beforehand Gildemeister 135. 

 

SIBS: Evaluating Impact of Therapy Timing on Tuberculosis Risk in HIV Patients Margaux Douvier
I will discuss my research experience at the University of Iowa focusing on evaluating the timing of ART treatment and how it affects tuberculosis risk in HIV/Aids patients.
Distributing Expected Soccer Goals: Giving Passes Due Credit Kapil Khanal
	I worked on models to give all soccer players involved in a goal or attempted goal kick some form of reward, using a StatsBomb dataset. Rewarding all players helps with ranking and classifying performance, designing a better team.