Hi, I'm Sead

Software Engineer, Machine Learning

Carnegie Robotics

I design and build software and algorithms for military and industrial applications. I'm responsible for systems across the stack, including backend microservices, computer vision pipelines (object detection & tracking), user interfaces, and system integration. I've led development on various projects including an R&D object tracking system that involved ML model creation and a custom tracking algorithm based on kalman filters. I work closely with cross-functional teams and customers to solidify requirements and guide development.

Machine Learning Researcher, Bioinformatics

Rutgers University

Led technical contribution on a paper that achieved state-of-the-art results (0.74 AUC, pending publication) in predicting progression of oral cancer. Used current literature to guide design and development of models. Trained, finetuned and ran inference on custom PyTorch models. Analyzed model results and data characteristics to pinpoint model weaknesses and improve performance ~0.20 F1. Tracked experimental outcomes and metrics, produced publication-level manuscript visualizations, and contributed to technical writing.

Co-op Software Engineer

Philips

Worked on a full-stack application to accurately fit users to a CPAP mask based on an image or 3D mesh. This involved development of a client side application (React) that inferfaced with a Postgres database in AWS as well as local hardware like a Bellus3D stereo camera. Also responsible for developing/evaluating custom and off-the-shelf model architectures for better sizing performance.

Bioinformatics Researcher

University of Pittsburgh

Contributed to a cross-functional machine learning research effort related to segmentation and analysis of biopsy images. Responsible for building ML infrastructure such as data pipelines (train / validation / test), utilities (data cleaning), and visualizations. Tested off-the-shelf networks for efficacy.

Software Engineering Intern

Carnegie Robotics

Developed a full-stack interal application to provide user-friendly access to hundreds of gigabytes of robot logs. Responsible for improving the aesthetics of the user interface, adding functionality like a 3D map viewer, and distilling developer requirements into feature roadmaps.

Systems Engineering Intern

Carnegie Robotics

Collected and analyzed logs from a car-mounted positioning system (GPS, IMU, etc). Resposible for data collection and producing analysis of key performance metrics like GPS coverage over time.