News and Events

Faculty News

Dr. Ruijun Zhao recently received a NSF grant with the project: Collaborative Research: A New Multiscale Framework for Integrating Socio-Economic Processes, Vector-Borne Disease Control, and the Impact of Transient Events.

Dr. Namyong Lee is the receptionist of 2022 MAA-NCS Meritorious Service Award.

Congratulations to Drs.Zhao and Lee!

Student News

The Data Derby is hosted by the Minnesota State IT Center of Excellence. This year's data was about global trade before and during the pandemic, studying the pattern of global trade in different countries and continents and the influence of the pandemic on global trade. The competition was a five-week data challenge. It was started on March 4th, and teams submitted the video recording of their presentation by April 3rd. Finally, the top five teams from each novice and advanced level presented their findings at the Data Derby virtual event on Saturday, April 9th. 

Two teams from Mathematics and Statistics and one team from CIS and Mathematics and Statistics won at the Data Derby competition. The 2022 Data Derby virtual event was held Saturday, April 9th. 

Advanced Level  

2nd Place  

Team L-MXTH  

Team Members: Lizzy Eccles, Mingyu Huang, Xeng Yang, Tatiana Quinonez, Hope Enright (Math & Stat)  

Faculty Advisor: Iresha Premarathna  

Novice Level  

1st Place  

Team Data Dive  

Team Member: Marcho Handoko (CIS), Prasanna Muppidi (CIS), Zelalem Denekew (CIS), Junsoo Seo (Math & Stat), Saud Alotaibi (Math & Stat)  

Faculty Advisor: Iresha Premarathna 

Novice Level 

4th Place 

Team Datoks56A 

Team Members: Aroni Basak, Saqawe Hassan (Math & Stat) 

Faculty Advisor: Iresha Premarathna

Congratulations Students!

Annual MSU High School Mathematics Contest

The 48th Annual Minnesota State University High School Mathematics Contest was held on Wednesday, April 13. There were 75 students competed, representing 9 high schools from Minnesota and Iowa. The contest is an individual and team competition. Awards are given to the top finishing teams and top individual scorers.

Team Awards

First Place Iowa City West High School Bill Chen
Thomas Keen
Anish Lodh
Ashley Seo
Steve Zeng
Second Place Mounds View High School Sophia Huang
Aurora Wang
Austin Wang
Justin Wang
Steven Zhou
Third Place Mankato West High School Sam Gersich
Parker Keenan
Calvin O’Connor
Jonah Zhao
Raymond Zhao

Individual Awards

First Place Anish Lodh Iowa City West High School
Second Place Justin Wang Mounds View High School
Third Place Aurora Wang Mounds View High School

Top Scorers by Grade

12th Grade Bill Chen Iowa City West High School
11th Grade Anish Lodh Iowa City West High School
10th Grade Sam Gersich Mankato West High School
7-9th Grade Austin Wang Mounds View High School

Team Top Scorer(s)

Anish Lodh, Ashley Seo, Steve Zeng Iowa City West High School
Emma Winters, Alex Harnitz Lake Crystal Wellcome Memorial High School
Christine Kim Mankato East High School
Jonah Zhao, Sam Gersich Mankato West High School
Mark Spengler Minnesota Valley Lutheran High School
Austin Wang, Aurora Wang, Justin Wang Mounds View High School
Miklos Bauman, Owen Larson Schaeffer Academy High School
Alex Matchinski, Jayson Macho, Caleb Holicky Tri-City United High School
Logan Bimberg, Ben Trucke, Preston Munio Watertown-Meyer High School

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Nomination for Membership

The following students are nominated by faculty of Department of Mathematics and Statistics for membership of American Mathematical Society for 2021-2022:

Moussa Abdoulaye Aboubacar, Eric Adu, Carter Barker, Aroni Basak, Shangyi Bi, Kaitlyn Birkholz, Kevin Bischoff, Anna Boettcher, Chrisantus Bongbeebina, Bradley Check, Elizabeth Eccles, Katherine Fennema, Mingyu Huang, Sujin Kim, Abimbola Kolebaje, Elafiossou Kouassi, Rachel Larkin, Sumit Mahajan, Bishal Maharjan, Jacob McCoy, Jason Motzko, Ammishaddai Ogyiri, Franck Arnaud Olilo, Tatania Heidy Quinonez Herrera, Aninda Roy, Md Raihatul Saimon, Michael Schaefer, Jenna Stitt, Nicholas Wagner, Xeng Yang.

Congratulations!


Nomination for Membership

The following student is nominated by faculty of Department of Mathematics and Statistics for membership of American Statistical Association for 2021-2022:

Sujin Kim

Congratulations!


Nomination for Membership

The following students are nominated by faculty of Department of Mathematics and Statistics for membership of Association for Women in Mathematics for 2021-2022:

Aroni Basak, Kaitlyn Birkholz, Anna Boettcher, Elizabeth Eccles, Katherine Fennema, Sujin Kim, Rachel Larkin, Tatania Heidy Quinonez Herrera, Jenna Stitt, Jennifer Gratz, Mai Dong, Eddle Mohamud, Kortney Southwick, Madelyn Saf, Fatuma Abdulkadir

Congratulations!


Annual Minnesota State University High School Mathematics Contest

The 47th Annual Minnesota State University High School Mathematics Contest was held virtually on Monday, April 19, 2021 and a virtual award ceremony took place on Wednesday, April 21, 2021. About 30 students competed, representing 6 high schools from Minnesota and Iowa. The contest is an individual and team competition. Awards are given to the top finishing teams and top individual scorers.

Team Awards

First Place Mankato West High School Lane Alfstad
Noah Gersich
Jack Roering
Jonah Zhao
Raymond Zhao
Second Place Mounds View High School Gavin Chang
Cynthia Dong
Elisa Guo
Sarvesh Sakthivel
Third Place Iowa City West High School Bill Chen
Miles Clark
Edward Li

Individual Awards

First Place Edward Li Iowa City West High School
Second Place Cynthia Dong Mounds View High School
Third Place Noah Gersich Mankato West High School

Top Scorers by Grade

12th Grade Noah Gersich Mankato West High School
11th Grade Cynthia Dong Mounds View High School
10th Grade Raymond Zhao Mankato West High School
7-9th Grade Edward Li Iowa City West High School

Team Top Scorer(s)

Edward Li Iowa City West High School
Kaitlyn Kirchner Lake Crystal Wellcome Memorial High School
Alex Emery Mankato East High School
Noah Gersich and Raymond Zhao Mankato West High School
Cynthia Dong Mounds View High School
Emerson Bengtson Zumbrota-Mazeppa Middle/High School

2021 Department of Mathematics and Statistics Research Month Activities

Conformal Deformation of Surfaces by the Extrinsic Dirac Operator

Wednesday, April 21, 9-9:50am

Location: https://minnstate.zoom.us/j/99847764630

Speaker: Katelyn LaPorte

Abstract: The purpose of the APP is to survey the methods used by Crane and others to create conformal deformations of surfaces in 3-dimensional Euclidean space. His goal was to utilize this for applications in image processing. Here we will go into more detail of the mathematical theory behind his method including the not so familiar Quaternion-Valued Extrinsic Dirac Operator. We will also explain the integrability conditions of the conformal deformation problem, which can be reduced to an eigenvalue problem related to this Dirac operator. As it is a first order linear operator, it has high efficiency in discretization and surface curvature editing.


Sequential Probability Ratio Test and Experiment

Wednesday, April 21, 10-10:50am

Location: https://minnstate.zoom.us/j/966 4794 7613

Speaker: Brianna Klapoetke

Abstract: The Sequential Probability Ratio Test (SPRT) is a method of testing simple hypotheses where the sample size is not determined in advance. In this talk I will describe the general process of using the SPRT, overview the theory that supports it, and describe how I applied it to data I collected to determine what alpha values people used to make their decisions in a simple game I designed.


Prediction of Heart Disease Using Bayesian Logistic Regression by Polya-Gamma Data Augmentation

Wednesday, April 21, 11-11:50am

Location: https://minnstate.zoom.us/j/939 3476 3132

Speaker: Zhenhan Fang

Abstract: Heart disease is one of the most common diseases nowadays, due to number of contributing factors, such as high blood pressure, high blood cholesterol, and smoking. About half of Americans (47%) have at least one of these three risk factors. To reduce the risk of heart disease, healthcare industries generate enormous amount of data, and have been seeking an early diagnosis of such disease for many years. Many data analytics tools have also been applied to help health care providers to identify some of the early signs of heart disease. Many tests can be performed on potential patients to take the extra precautions measures to reduce the effect of having such a disease, and reliable methods to predict early stages of heart disease. In this study, Logistic Regression and Bayesian Logistic Regression are used to establish models to predict heart disease. We apply the Polya-Gamma data augmentation to our Bayesian Logistic model. We found that Bayesian Logistic model can provide a better performance, although it is more expensive than general Logistic model.


Classification of Chess Games: An exploration of classifiers for anomaly detection in chess

Wednesday, April 21, 12-12:50pm

Location: https://minnstate.zoom.us/j/5074676277

Speaker: Masudul Hoque

Abstract: Chess is a strategy board game with its inception dating back to the 15th century. The Covid-19 pandemic has led to a chess boom online with 95,853,038 chess games being played on January 2021 on one online chess site (lichess.org) alone. Along with the chess boom, instances of cheating have also become more rampant. Classifications have been used for anomaly detection in fields such as network security and online games and thus it is a natural idea to develop classifiers to detect cheating. However, there are no such prior examples of this, and it is difficult to obtain data where cheating has occurred. So in this paper, we develop 4 machine learning classifiers, Linear Discriminant Analysis, Quadratic Discriminant Analysis, Multinomial Logistic Regression, and K Nearest Neighbour classifiers to predict chess game results and explore predictors that produce the best accuracy performance. We use Confusion Matrix, K Fold Cross Validation, and Leave One Out Cross Validation methods to find the accuracy metrics.

There is three phases of analysis. In phase I, we train classifiers using 1.94 million over the board game as training data and 20 thousand online games as testing data and obtain accuracy metrics. In Phase II, we select a smaller pool of 212 games, pick 8 additional predictor variables from chess engine evaluation of the moves played in those games and check whether the inclusion of the variables improve performance. Finally, in Phase III, we shall investigate for patterns in misclassified cases to define anomalous values.

From Phase I, the models are not performing at a utilizable level of accuracy (44-63%). For all classifiers, it is no better than deciding the class with a coin toss. K Nearest Neighbour with K = 7 was the best model. In Phase II, adding the new predictors improved the performance of all the classifiers significantly across all validation methods. In fact, using only significant variables as predictors produced highly accurate classifiers. Finally, from Phase III, we could not find any patterns or significant differences between the predictors for both correct classifications and misclassifications.

In conclusion, Machine learning classification is only one useful tool to spot instances that indicates anomalies. However, we cannot simply judge for anomalous games using only one method.


Count regression models for Covid-19 related deaths and overall deaths.

Wednesday, April 21, 1-1:50am

Location: https://minnstate.zoom.us/j/94358910903

Speaker: Manori Ampe Mohottige Dona

Abstract: With the start of the ongoing Covid-19 pandemic, the number of deaths worldwide has increased in a considerable amount. Confirmed coronavirus cases in the United States increased significantly in the third week of March in 2020 as testing was made more rapid and overtook China’s on the 26th of March 2020, making the US the world’s most affected country by the coronavirus.

This study aims to determine the relationship of overall death counts and Covid-19 related death counts of five main states in the United States to the different age groups and gender over the period of one year. The data were collected from the government data repository, data.gov.

Poisson Regression analysis and Negative Binomial Regression analysis were used for model building purposes and total death count prediction. The k fold cross-validation and leave-one-out cross-validation were used to identify the best model.

The Negative Binomial regression model was identified as the best model compared to the Poisson regression model. According to the model, the most significant factor for total deaths and Covid-19 deaths is gender. Texas has the highest significant contribution to the Covid-19 model and the most significant age group is 84 years or over.


Nomination for Membership

The following students are nominated by faculty of Department of Mathematics and Statistics for membership of American Mathematical Society for 2020-2021:

Moussa Abdoulaye Aboubacar, Eric Adu, Afrah Alhammad, Manori Ampe Mohottige Dona, Kayode Ayorinde, Aroni Basak, Shangyi Bi, Huyen Cao, Taeyoung Choi, Zhenhan Fang, Rachel Holmes, Masudul Hoque, Hans Kapend, Sujin Kim, Brianna Klapoetke, Abimbola Kolebaje, Katelyn LaPorte, Changhong Li, Bishal Maharjan, Charlie Moe, Tracy Morrison, Jasson Motzko, Ammishaddai Ogyiri, Franck Arnaud Olilo, Dong Young Park, Deanna Pautzke, Aninda Roy, Michael Schaefer, Nicholas Wagner, Erin Watt, Austin Whitcombm.

Congratulations!


Nomination for Membership

The following student is nominated by faculty of Department of Mathematics and Statistics for membership of American Statistical Assosciation for 2020-2021:

Zhenhan Fang

Congratulations!


Nomination for Membership

The following students are nominated by faculty of Department of Mathematics and Statistics for membership of Association for Women in Mathematics for 2020-2021:

Alison Millerbernd, Fatuma Abdulkadir, Serida Zosse, Morgan Olson, Sonja Kohout, Samantha Banwell, Erica Johnson, Joan Fuhrman, Samantha Doom, and Taylor Burke

Congratulations!


Student News

Congratulations to Minnesota State University team on winning second place in advanced Data Derby 2020.

Team members: Tania Hasanpoor, Abdelrahman Elkenawy, Nishchint Upadhyaya, Arlton Cox, Shuk-ping Wong

Advisor: Dr. Cyrus Azarbod

Special congratulations to Shuk-ping Wong, Applied Statistics graduate student and Vice president of Stats Club.


Congratulations to Minnesota State University team on winning second place in Data Visualization at 2020 MUDAC.

Team members: Taisuke Usumi, Nusrat Chaity, Lindsay Miller, Alison Millerbernd, Junsoo Seo

Advisor: Dr. Soumya Banerjee