Congressional districting maps in Ohio are scheduled to be redrawn in 2021. In order to do that, information about the population must be collected and analyzed in order to create fair districting that is representative of the needs of the people. The practice of gerrymandering is a threat to our democracy and aims to outsmart the voting process. If we are to combat this problem, we need new, efficient ways of understanding the dynamic nature of our population.
Innovative mapping tools are needed to rapidly analyze proposed voting maps and support redistricting to create better representation in our democratic process. This challenge will allow students to work with the latest voter and census data along with national experts in statistical and mathematical analyses of voting districts. In taking on this task, students will be able to have an impact on the voting rights of the electorate.
We imagine a team of students with a variety of backgrounds including, but not limited to, policy, data analytics, engineering, mathematics, and/or statistics along with a passion for the well-being of our democratic process. Use the knowledge you have gained in your classes and apply them to a wicked problem.
Make a real-world difference on an arena that is the backbone of our government and society while building your skillsets in communication, teamwork, and problem solving.
One of our challenges this semester involves machine learning to help innovate the process of creating the latest technology! This challenge involves creating an automated process for a computer to accurately create the schematic of an electronic circuit board using only images of that board.
Circuit boards are the heart of the technology we use every day. Currently, schematics must be created manually and require a high amount of time and labor. With various images using a plethora of modalities including X-ray, scanning electron microscope, etc., a toolchain is required that can automatically combine different images of the same circuit board to develop a schematic. The challenge asks for solutions that involve any combination of compressed sensing or imaging, machine vision, optical character recognition, and shape analysis.
We are seeking students with an interest in this technology as well as anyone with backgrounds in:
- Mechanical Engineering
- Material Science Engineering
- Civil Engineering
- Computer Science Engineering
- Electrical and Computer Engineering
- Integrated Systems Engineering
We are hoping to build an interdisciplinary team that can tackle this complex challenge and welcome any student who wishes to work on it. Sign up for PUBAFRS 5620, Rapid Innovation for Public Impact, that meets Fridays from 12-3 for a chance to contribute to the solution for this complex problem!
Note: this course has been used as a capstone substitute in many different colleges and can be done with approval depending on the problem worked on and the requirements of that college.