This site spotlights the MIE Department Research Projects seeking Undergraduate Student Reseaarchers.  It will be updated frequently to add new projects seeking undeergraduate students.  If interested, please contact the Faculty Contact for each project listed below.

Project Title:   Project Description:   Faculty Name:   Faculty Contact Information:  
Engineering Education Research -Student Performance Prediction The project involves analyzing data from an adaptive learning platform to predict student performance in a course using different predictive modeling approaches.  Interested students must have strong programming (Python or R) and predictive modeling skills, and an interest in engineering education research. Dr, Ali Yalcin ali.yalcin@montana.edu
       
Energy of Things – What is running up my energy bill?! The project involves analyzing data from an energy meter monitoring energy usage in private homes.  The overarching goal is to identify which devices are using energy at any given time.  Interested students must have strong programming (python or R) and data analytics skills, and an interest in loT, distributed sensor systems, and solving unstructured and open-ended research problems. Dr, Ali Yalcin ali.yalcin@montana.edu
       
Stretch Broken Carbon Fiber for Primary Aircraft Structures (SBCF-PAS) The SCBF-PAS Program is a $25.6 million dollar program sponsored by the U.S. Army Combat Capabilities Development Command Aviation & Missile Center.  This research and development is to understand and overcome challenges to manufacture primary aircraft structure using SBCF.  The results will be used to design the next generation of more-efficient structure, saving weight and enabling improved maneuverability, and fuel efficiency.

Doug Cairns

Roberta Amendola

Cecily Ryan

Dilpreet Bajwa

Please contact the SBCF-PAS Program Manager, Cambrie Monfort

cambrie.monfort@montana.edu
       
Body-Worn Sensors for Prosthesis Control Help us understand how to translate information from body-worn sensors into control for robotic prostheses. We will be analyzing data from IMU, EMG, and other sensor types with Machine Learning to improve translation of user intent to device control. Corey Pew

corey.Pew@montana.edu
     

 
Real-Time Feedback for Runners We’re using real-time measurements of biomechanics to help runners improve their form. We will be collecting data from participants in our study and need help with data collection and analysis. Corey Pew corey.Pew@montana.edu