Up & Coming Engineer: Meet Madeline Cotter

Meet another young engineer Madeline Cotter

by Howard Bussey

Have you ever met someone who you wonder how they ever have time to sleep? Madeline Cotter, who prefers to go by Mary, a senior at Allendale-Columbia Upper School, is one such person. She’s the President of the student government, Captain of the track team, Leader of the local chapter of ProjectCSGirls, and still has time for independent research in artificial intelligence and machine learning!

Mary has entered award-winning projects in the last three Terra Rochester Finger Lakes Science and Engineering Fair, tackling very different types of problems each year.

As someone very concerned about the environment, her sophomore project was teaching a simple 4-5 layer neural network to analyze the water quality of lakes by matching Landstat data with a large data set of Secchi Disk measurements, which is a measure of turbidity. For this project, she learned to use Pandas for data cleaning and Keras for deep learning.

Cotter Watch

In her junior year, wearing her fitness device and noticing that her heart rate surged while doing her supposedly “easy run”, prompted Mary to wonder if her heart rate actually did go up, or if it was an error in the device. That led to a project on Anomaly Detection, where she compared a standard anomaly detection algorithm with a newly Cotter Watch MIT-developed neural network approach. Among other findings, she established that the latter gave better results. This won her the opportunity to compete at the Regeneron International Science and Engineering Fair.

This year she explored how well machines could learn to play simple games versus a programmer hard coding winning actions. She chose 3 simple computer games: the mountain car with its simple back and forth motion, the acrobot with its swinging arms, and the cart pole balancing with the goal of keeping the pole upright. She then used a reward structure to teach a neural network to successfully play each game and compared that solution to one she hard coded. One lesson Mary drew from the project is that machine learning isn’t necessarily the best solution to all problems.

Cotter 3 Games

What all these projects do have in common is Mary’s love of coding. She first encountered programming in middle school as part of her school’s First Lego League team. Largely selftaught she began with simple block coding, then on-line lessons from Code.org, and eventually Python and other languages. Never satisfied with just replicating the given examples, Mary would see if she could make the program do something slightly differently. Once she successfully accomplished that, she would try further refinements, eventually becoming confident in writing code from scratch that would solve whatever problem she was tackling.

Her participation as a middle schooler in ProjectCSGirls was a key element in her development, and Mary is now giving back by mentoring 4th graders. While not all the girls continue, she finds it very satisfying to see mentees who are now 6th graders enthusiastically programming and engaged in STEM activities. Overcoming the stereotype of the coder as “a dude in a basement, isolated and alone” is important in encouraging girls. In her advice on a national panel for the ProjectCSGirls Gala, Mary recommends girls pick a project that addresses some social issue but that also has an adequate amount of data associated with it to avoid being frustrated by not being able to get concrete results.

Mary is now looking forward to graduation and starting her undergraduate studies at the University of Virginia in the Fall, where she has been designated a Jefferson Scholar, a very select program. She hopes to explore her passion for both the environment and computer science. One of her dreams is returning to Rochester after graduation to work in the City’s Office of Sustainability on transportation issues, something prompted by a paper she wrote on the environmental impact of mass transit. q