The Scholarships Creating Opportunities for Applying Mathematics (S-COAM) project at Indiana University of Pennsylvania is seeking applicants for our unique scholarship program. In addition to providing monetary scholarship support, S-COAM creates a network of students that engage in professional development activities to improve your career prospects and success in STEM fields.

While increasing numbers of students pursuing mathematics degrees, S-COAM is unique in its goal of establishing a supportive connection of graduate students with undergraduates through scholarship cohort activities.

Need-based scholarships annually support seven to nine students from the MS in Applied Mathematics and about 40 undergraduates seeking a mathematics major or minor in mathematics with a STEM major. Annually, 10 to 20 new freshmen are recruited with at least 87 distinct students supported over five years. We are seeking high-achieving high school students with financial need from across the region.

The selection process considers need, diversity, academic performance, activities, and a personal statement.

We Want You to Apply!

Apply according to your student group:

Monthly Meetings for 2020-21

  • August 23, 1:00-3:00 p.m. via Zoom
  • September 23, 3:30-5:00 p.m. via Zoom
  • October 29, 6:30-8:00 p.m. via Zoom
  • December 4, 3:30-5:00 p.m. via Zoom
  • January 18, 10:00 a.m.-Noon via Zoom
  • February 18, 3:30-5:00 p.m. via Zoom
  • March 31, 5:00-6:30 p.m. via Zoom
  • April 30, 3:30-5:00 p.m. via Zoom

Benefit

In addition to financial support, S-COAM scholars will also participate in the Mathematics Enrichment Activities Network.

Our Students Engage in Many Activities, Including:

  • Local, regional, or national conferences
  • Peer-led, team-learning sessions for freshmen
  • Research opportunities
  • Departmental or college-wide colloquia
  • Workshops in software training, job/internship search, and graduate school preparation
  • Connections with working professionals in science and engineering fields
  • Social gatherings with other S-COAM scholars
  • IUP clubs, including: Math Club, Actuary Club, or Preservice Teachers of Mathematics
  • Presentations by professionals from industry and academia

Scholarship Renewal Requirements

  • Participate in all required events in the program
  • Submit the FAFSA form, and continue to meet the federal financial aid requirements every semester
  • Continue as a full-time student at IUP making satisfactory progress toward a qualifying sciences and mathematics degree
  • Submit a summary of activities every semester with a short essay on the program and his/her academic progress
  • Complete the program outcomes and assessment survey
  • Undergraduates must maintain a cumulative GPA of at least 3.0 on a 4.0 scale, and graduates must maintain a cumulative GPA of at least 3.2 on a 4.0 scale.

This web page changes often. Please check back frequently for additional information.

Graduate Students

Check out our Survival Guide for Graduate Students in Applied Mathematics and Data Science.

Peer-Led Team Learning Materials

Workshops

Python Workshop I: The Basics

  • February 17,5:00-6:30 p.m.
  • via Zoom

Abstract:An introduction to python programming language will be conducted in a hands-on manner. Topics discussed will include: basic loops, functions, classes, importing libraries from other python scripts, as well as basic IO for files. A quick overview of several code development environments will be discussed. In the workshop, we will write a working piece of code that showcases the programming language. This small program can be extended by attendees for use on other tasks.

Python Workshop II: Beyond the Basics

  • February 24, 5:00-6:30 p.m.
  • via Zoom

Abstract: This workshop will extend some of the topics discussed in the Introductory Python workshop. Advanced features available in Jupyter notebooks will be discussed and demonstrated. Topics include interactive plotting, audio processing, image manipulation and processing, interactive notebook widgets, and pulling data from websites. Interactive python code can be placed almost anywhere!

R Workshops

R is a free statistical software package that is extensively used in both academia and industry. It is an open source platform that has over 16,000 contributed packages. Associated with R is the integrated development environment, RStudio. In this two-day online workshop, we introduce the major components of these packages using RStudio Cloud. RStudio Cloud is a cloud-based environment that incorporates both R and RStudio without a need for installation or dedicated hardware. Before the workshops, instructions on account setup will be sent to all registered participants. Workshop attendees should have an introductory statistics background that includes knowing how to construct confidence intervals and conduct hypothesis tests. Below are additional details about the workshop by day.

Introduction to R Workshop I

  • October 8, 3:30-5:00 p.m.
  • via Zoom

Abstract:We begin by giving an overview of R and RStudio. This includes showing where to download these software packages and how to install them. Using RStudio Cloud, we will go through several examples that demonstrate the following:

  • How to properly create data sets and read them into RStudio.
  • How to find descriptive statistics either by using or not using a grouping variable.
  • How to construct graphics such as histograms, box plots, and scatter plots.
  • How to perform a simple linear regression analysis.

Participants will then be given a chance to practice these skills by working through several problems.

Introduction to R Workshop II

  • October 13, 3:30-5:00 p.m.
  • via Zoom

Abstract:On day 2, we will expand on the tools from day 1 to conduct additional statistical analysis. This includes the following:

  • How to construct confidence intervals and perform hypothesis tests for one and two population mean problems.
  • How to conduct a one-way ANOVA.
  • How to conduct one and two sample inference procedures associated with population proportions.
  • How to perform a logistic regression analysis.
  • Advanced graphics using the ggplot2 package.

Participants will then be given a chance to practice these skills by working through several problems.

Major Events

Alumni Panel, March 10, 5:00-6:15 p.m. via Zoom

  • Jared Fee, PhD student, Department of Chemistry, University of Connecticut
  • Ben Jarret, Branch Chief of Office of Enforcements Division of Analytics and Surveillance, Federal Energy Regulatory Commission
  • Danielle Siebert, Chief Operations Officer and IT Administrator, Armstrong County Building and Loan Association
  • Jon Wayland, Senior Manager, Data Science, Florida Blue

November 19, SIAM Visiting Lecture, Dr. Sara Del Valle

Sara Del Valle is a scientist and deputy group leader for the Information Systems and Modeling Group at Los Alamos National Laboratory.

November 19, 4:30-5:30 p.m. via Zoom

"Real-time Data Fusion to Guide Disease Forecasting Models" (Joint Event with Science Inspires Series)

Sponsored by Mathematical and Computer Sciences Department, S-COAM (DUE 1742304), Science Inspires Series

Abstract: Globalization has created complex problems that can no longer be adequately understood and mitigated using traditional data analysis techniques and data sources. As such, there is a need for the integration of nontraditional data streams and approaches such as social media and machine learning to address these new challenges. In this talk, I will discuss how our team is applying approaches from the weather forecasting community including data collection, assimilating heterogeneous data streams into models, and quantifying uncertainty to forecast infectious diseases.

November 19, 6:30-7:30 p.m. via Zoom

"Assessing School Reopenings Scenarios in Response to COVID-19 Using Different Modeling Approaches"

Sponsored by Mathematical and Computer Sciences Department, S-COAM (DUE 1742304), SIAM IUP Student Chapter

Abstract: School-age children play a key role in the spread of airborne viruses like influenza due to the prolonged and close contacts they have in school settings. As a result, school closures and other non-pharmaceutical interventions were recommended as the first line of defense in response to the novel coronavirus pandemic (COVID-19). Assessing school reopening scenarios is a priority for states, administrators, parents, and children in order to balance educational disparities and negative population impacts of COVID-19. In this talk, I will discuss two different modeling approachesan agent-based simulation and an SEIR-type modelto simulate the potential impact of different scenarios, including remote learning, in-person school, and several hybrid options that stratify the student population into cohorts in order to reduce exposure and disease spread. Our results show that reducing the number of students attending school leads to better health outcomes, and the split cohort option enables in-classroom education while substantially reducing risk. I will conclude with a discussion on how mathematical modeling has been used to provide decision support for COVID-19.

Short Biography:
Sara Del Valle is a scientist and deputy group leader for the Information Systems and Modeling Group at Los Alamos National Laboratory, where she works on the development of mathematical and computational models for infectious diseases. Her research focuses on using mathematical and computational models to improve our understanding of human behavior and the spread of infectious diseases. She has also worked on investigating the role of Internet data streams on monitoring emergent behavior during outbreaks and forecasting infectious diseases.

If you have questions about this program, please contact:

Project Directors

Yu-Ju Kuo, yjkuo@iup.edu
Rick Adkins, fadkins@iup.edu
210 South Tenth Street
Mathematical and Computer Sciences Department
Indiana University of Pennsylvania
Phone: 724-357-2608

This project is funded by the National Science Foundation Scholarships in Science, Technology, Engineering, and Mathematics (S STEM) program under Award No. DUE 1742304.

Past S-COAM Scholarship Recipients