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Eric C

- Research Program Mentor

PhD candidate at University of Michigan - Ann Arbor


Medical Imaging, Computer Vision and Object Tracking, Machine Learning, Deep Learning, Image Processing, Natural Language Processing, Large Language Models, Generative AI


Hello! My name is Eric, and I am currently a Ph.D. Precandidate at the University of Michigan - Ann Arbor. My research involves optimization techniques and machine learning for medical imaging applications, primarily Single Photon Emission Computed Tomography (SPECT). I am also an Algorithm Engineer at KLA, where I leverage deep learning techniques to measure structures on silicon wafers that are only a few nanometers large! I have been a mentor with Polygence for over a year! In my free time, I enjoy weightlifting, reading, video games, coding, and spending time outdoors with my two beloved dogs. I was able to hit my lifetime goal of a 500-pound deadlift late last year! I'm working now on being more mindful and learning to be present every day. I am thankful to be able to add Polygence mentor to my list of current activities and am looking forward to helping you reach your project goals :).

Project ideas

Project ideas are meant to help inspire student thinking about their own project. Students are in the driver seat of their research and are free to use any or none of the ideas shared by their mentors.

Deep Learning for Automatic Brain Tumor, Edema, and Necrosis detection

For this project, the goal is to create, train, and deploy a deep neural network on images of MRI brain scans to look for a series of dangerous brain conditions. By creating this network, we can ensure that each patient scan receives two examinations; one from a radiologist and another from our product. Doing so reduces the odds that any harmful condition may be missed.

Automatic Bird Identification using Deep Neural Networks

Imagine you were a conservationist who wanted to track the presence of specific types of birds in a given area. However, the birds are nocturnal or extremely rare, so they can hardly be caught by cameras. This project would enable wildlife researchers to identify bird species purely based sounds they make while chirping! Using deep learning, the goal of this project is to create a model which can accurately identify bird species based on audio signals alone.

Help catch bad guys, with image filtering!

One of the most common tasks in image processing is image denoising. From pictures on your cell phone to the notoriously low-quality images of gas station security cameras, a noise-free image is a desirable image. In this project, one will learn the basics of denoising images using a variety of modern image processing techniques for their desired imaging modality. This could be medical imaging, optical imaging, or even radar imaging!

Coding skills

Python, Matlab, Julia

Languages I know

Spanish, novice

Teaching experience

Reading books alongside Elementary school students (weekly), volunteering as an Electrical Engineering tutor within the engineering honor society Tau Beta Pi (weekly), hosting "Middle School Science Day!" type activities with the Graduate Society of Black Engineers and Scientists at U of M. I have now successfully mentored four Polygence projects, two of which have gone on to publish in scientific journals like IEEE! In all of my experiences, I like to do a combination of demonstrating the exercise, building confidence in my mentee, and then acting as more of a guiding force and watch them complete tasks on their own.


Work experience

KLA (2022 - Current)
Algorithm Engineer


University of Michigan - Dearborn
BSE Bachelor of Science in Engineering (2020)
Electrical and Computer Engineering
University of Michigan - Ann Arbor
MSE Master of Science in Engineering (2021)
Signal and Image Processing and Machine Learning
University of Michigan - Ann Arbor
PhD Doctor of Philosophy candidate
Deep Learning for Single Photon Emission Computed Tomography

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