For the last three years, I have designed and delivered a special course: Research Project in Industrial Mathematics.
This course was initiated by NSF-funded MAA PIC Math (Preparation for Industrial Careers in Mathematics) Program in 2017.
This course provides a unique educational experience by introducing students to the ways that advanced mathematics and statistics are used in the real world to analyze and solve complex problems. The students work in small teams on real problems, which are directly provided by business and industry. Most of the projects are data enabled and machine-learning oriented.

PROJECTS ADVISED

2018-2019 Research Project in Industrial Mathematics
Predictive Analytics in Child Welfare
by Daniel Oldham, Nathan Foster, Betiay Babacan, Maegan Revak, Geoffrey Mount
Industrial Sponsor: Partnership for Strong Families, Gainesville, FL
This project was supported by ERAU IGNITE grant

The Partnership for Strong Families (PSF) is a child welfare organization headquartered in Gainesville, Florida helping to serve 13 counties in northern Florida. DCF estimates that, within PSF’s area, approximately 45 children are removed every month from their parents’ (or guardians’) care. There is a clear need to identify, as early as possible, children who are at risk. The purpose of this project is to examine removals within PSF’s area over the last 7 years and to potentially identify factors that lead to a child’s re-entry into the state shelter system.

Results were presented by:
Daniel Oldham at ERAU STUDENT RESEARCH SYMPOSIUM (SRS), November 19, 2018, Daytona Beach, FL
Daniel Oldham at Florida Undergraduate Research Conference, February 22-23, 2019, Jacksonville, FL
Daniel Oldham at National Conference on Undergraduate Research, April 10-13, 2019, Atlanta, GA
Nathan Foster and Daniel Oldham at 2019 ERAU Discovery Day

Results were published:
Oldham, D., Foster, N., & Berezovski, M. (2019). Data Mining and Machine Learning to Improve Northern Florida’s Foster Care System. Beyond: Undergraduate Research Journal, 3(1), 3.

News article about the project:
Data Science Offers New Tools for Understanding Foster Care Outcomes

  • Daniel Oldham got Research Scholars Award
  • Daniel Oldham currently is Data Engineer at MassMutual
  • Geoffrey Mount currently is Computer Firmware Engineer at Cyient Inc
Spring 2019 Research Project in Industrial Mathematics - Capstone
Satellite-Image Detection of Ships with Convolutional Neural Network
by Clayton Birchenough

A convolutional neural network was built to provide automatic ship detection and localization from satellite images. The challenge of solving for the parameters of the neural network is a non-convex optimization problem with acceptable solutions and many deceptively acceptable solutions. To avoid deceptively acceptable solutions, different learning rate parameters, data augmentation methods, and neuron dropout rates were explored when training the network. Additionally, the effects of the number and order of convolutional, max pooling, and fully connected layers were varied to investigate the impacts on training and results.
Spring 2019 Research Project in Industrial Mathematics
Characterizing Seismic Events through Advanced Data Analytics
by Roger Acchione, Nikolaus Rentzke, Jessica Haselwood, Nathaniel Arzola Lilly, Dhairya Chokshi, Paige Rasmussen
Industrial Sponsor: Nevada National Security Site, Las Vegas, NV

The Signal Processing and Applied Mathematics research group at the Nevada National Security Site, is seeking to collaborate with students at Embry-Riddle Aeronautical University to develop advanced data analytics methods for characterizing seismic events in the southwest United States as near-field earthquakes, far-field earthquakes, or non-natural seismic events, using publicly available seismic data.
Spring 2019 Research Project in Industrial Mathematics
Unmanned Aerial Vehicle (UAV) DOF Dynamic Simulation Environment
by Philip Giuliano, Christopher Gutierrez, Eric Osorio, Eugenie Fontaine, Nicolas Prulhiere
Industrial Sponsor: Embedded Control Designs, MicaPlex, Daytona Beach, FL

The goal of this project is the development of a 6 DOF dynamic simulation environment. This simulation environment will play an integral role in the development of flight software and mission planning for standard operations as well as R&D.

  • Results were presented at 2019 ERAU Discovery Day
  • Eugenie Fontaine got internship as Systems Engineering intern with Boeing for Summer 2019
Spring 2019 Research Project in Industrial Mathematics
OneSky Optimization Project
by Jose Gachancipa Parga, Ian Mungovan, Ada Chika, Timothy Mitchell, Ian Young
Industrial Sponsor: OneSky, MicaPlex, Daytona Beach, FL

The ultimate goal for the OneSky Optimization project is to create a new fleet optimizer that works across all of the OneSky Flight five established private jet brands: Flexjet, Sentient Jet, SkyJet, PrivateFly, and Sirio. There are industry-specific rules and business-specific requirements that ERAU team working on this project will discuss with members of the OneSky Innovation Center in the MicaPlex.

  • Results were presented at 2019 ERAU Discovery Day
  • Jose Gachancipa Parga got internship with Airbus for Summer 2019
Spring 2018 Research Project in Industrial Mathematics
Quantifying Uncertainties in Image Segmentation
by Jean-Lucien Gionet, Tori Hoff
Industrial Sponsor: Nevada National Security Site, Las Vegas, NV

The Signal Processing and Applied Mathematics research group at the Nevada National Security Site (NNSS) is excited to partner with students at Embry-Riddle Aeronautical University to develop a rigorous statistical method for characterizing the effects of user interaction on supervised image segmentation.

  • Jean-Lucien Gionet got internship with Northrop Grumman for Summer 2018 and Summer 2019
  • Clayton Birchenough got internship with NNSS for summer 2018
  • Tory Hoff got internship with NNSS for summer 2018
    Results were published in:
    Luttman, A., Catenacci, J., Constantino, D., Hoff, T., Jackson, E., Putman, B., ... & Hoeller, M. (2018). Dynamic Test Prediction and Characterization through Modeling-Informed, Multi-Source Data Fusion, NLV-006-17, Year 2 of 3 (No. DOE/NV/03624-0246). Nevada National Security Site/Mission Support and Test Services LLC.
  • Tory Hoff is currently persuing the PhD at Georgia Tech in Quantitative Psychology
Spring 2018 Research Project in Industrial Mathematics
Predictive Analytics in Child Welfare
by Maegan Revak, Tori Hoff, Cynthia Butcher
Industrial Sponsor: Partnership for Strong Families, Gainesville, FL

The purpose of this project is to study the data provided by Partnership for Strong Families (PSF) and identify any factors that could lead to a child being removed from his/her home multiple times.

  • Grace Butcher and Maegan Revak got IGNITE grant to continue the project for 2018-2019 academic year
Spring 2017 PIC Math Course
Mie Scattering Diagnostic
by Clayton Birchenough, Tilden Roberson, Joao Rocha Belmonte, Sophie Jorgensen
Industrial Sponsor: Nevada National Security Site, Las Vegas, NV
This project was supported by PIC Math Program

The Signal Processing and Applied Mathematics Research Group at the Nevada National Security Site teamed up with Embry-Riddle Aeronautical University (ERAU) to collaborate on a research project under the framework of PIC math program with challenge to make a recommendation about whether to use a technique, used in the air quality industry, called Mie scattering, and repurpose this method to measure particle sizes that are emitted from a metal surface when it’s shocked by explosives.

  • Clayton Birchenough got internship with NNSS for summer 2017
  • Tilden Roberson got CO-OP with NASA’s Armstrong Flight Research Center for fall 2017
  • Joao Rocha Belmonte got internship in Germany with MTU Aero Engines for fall 2017
  • Team presented results at 2017 MathFest as poster presentation
  • Clayton Birchenough won 2nd place for poster presentation at 2018 ERAU Discovery Day