We help teams win more games by analyzing game footage.

- Enhanced perception algorithms for self-driving vehicle software, resulting in a 24% reduction in collision rates by accurately detecting finer details and elevated points- Redesigned the real-time path processing node using LIDAR cost maps, ROS2 perception modules, and custom models, decreasing latency by 3 seconds and achieving 43% smoother route navigation -Streamlined vehicle control publishing procedures and live messages, enhancing responsiveness and driving efficiency in dynamic conditions, resulting in 90% crashless runs

Utilized Azure DevOps and Agile Methodology to brainstorm, prototype, test, optimize, and deploy software Developed and deployed time-series machine-learning models to predict pipeline outcomes and forecast demand on a day-to-day basis with over 98% accuracyImplemented a data collection and visualization tool that tracks over 10,000 live shipments from 23 unique terminals and calculates running totals along with filters for terminal, destination, carrier, and date, allowing for effective data access, usage, and analysis resulting in over a $1M of saved costs.Generated an alert system with varying levels of severity to notify hubs when supply was forecasted to run out in the next 3/7/14 days

Set up the back-end for the mobile app with AWS Amplify, DynamoDB, and Node.jsDesigned the front-end with React.js and used HTML and JS to improve the webpage.