- Created a hardware-optimized computer vision library in C/C++ designed to run on lightweight drones. This library offloads core computer vision logic to signal processors, resulting in a significant reduction in CPU utilization, power consumption, and heat generation.- Used aforementioned library to create a custom visual feature tracker in C++ to assist in Visual-Inertial Odometry. As a result of hardware optimizations, tracker is significantly more efficient enabling performant real-time tracking on-device.- Assumed ownership and maintenance responsibilities for key packages within the company's SDK focused on computer vision including our machine learning models, depth from stereo server, and thermal optic flow.

- Worked in Cornell University’s EmPRISE lab to engineer a caregiving robot to assist with feeding. Project involves developing Deep Learning models in PyTorch to expand the number of recognizable food items. Integrated model using computer vision, Python, C++ and ROS. Advised by Tapomayukh Bhattacharjee.

- Designed a scalable and transparent Optical Character Recognition pipeline to process uploaded clinical documents using Tesseract, AWS, Docker and Kafka. Pipeline operates 85% faster than its predecessor leading to a large operational savings.- Developed Natural Language Processing pipelines using SpaCy to extract clinical information from a patient’s documents. These pipelines assist patients in being approved for insurance creating cost savings while reducing burden on nurses.- Worked in an agile-based team using Git, AWS, and Docker.

- Developed quantitative lung airway features to be used in a machine learning model to predict patient response to immunotherapy treatment leading to a classifier able to predict with an AUC of 0.67. Second-authored a publication on the project: https://jitc.bmj.com/content/9/Suppl_2/A44- Implemented a post-processing algorithm which takes CT scans whose lung boundaries have been corrupted by COVID-19 and automatically corrects them. This algorithm is part of a fully-functional pipeline using Python and OpenCV which automates the lung segmentation imaging process for radiologists and is under peer-review for publication in a medical journal.

- Created an algorithm using C and OpenGL which takes spaceflight parameters for the International Space Station and generates a visualization indicating the spacecraft’s orientation in flight. This provides insight to how self-shadowing occurs on the solar panels during orbit - an invaluable resource to the power analysis team at NASA to assist with solar panel and battery development.