I am a Machine Learning Engineer. I am part of the Machine Learning and Algorithms team at Gentex, and I'm working on designing and optimizing Neural Networks for Driver Monitoring Systems. I port ML models onto hardware and perform runtime optimizations like quantization to minimize inference time while maintaining accuracy. I also perform hardware acceleration where appropriate - for instance -- the pre and post-processing steps of the models to reduce latency.
I am broadly interested in working in all things machine intelligence. I'm currently focusing on developing Machine Learning models that can run on compute-constrained devices, like mobile phones, tablets, and smart glasses.
At university, I was a research assistant at The Secure and Intelligent Things Lab, and working on the security of Autonomous Vehicles. I explored various methods of generating Adversarial Examples using DNNs, that fool state-of-the-art object detection models including those part of the YOLO family, in Autonomous driving scenarios.
My previous experience also includes working with United Airlines to develop a Machine Learning Quality Assurance web app, which used CNNs to score the quality of aircraft (accuracy 98%) automatically instead of Quality Engineers manually sifting through 1000s of images. The web app also helped the quality team automatically monitor the live sentiments of customers on X (then Twitter) using sentiment analysis
I love learning and experimenting, so here you will find all my hobby projects! I like to delve deep into things, so you will see some deep dives into common algorithms like Principal Component Analysis, code to visualize CNNs, and even some Assembly programming!
