Part of the Online Ordering team building APIs, processing data, and designing user interfaces.- Integrated with LLM AI APIs to add semantic search of restaurant menus and provide purchase recommendations.- Improved and upgraded API integrations for multiple third-party dependencies.

Part of the Online Ordering team building APIs, processing data, and designing user interfaces.- Analyzed and optimized guest payment capture to reduce payment processing fees by 12%.- Improved product positioning in a competitive market by integrating with large white-label delivery providers, enabling hundreds of clients to increase engagement and revenue.- Streamlined and unified integrator invoice processing and client billing system.

Knowledge Discovery Laboratory in CICSResearching non-parametric causal effect estimation using Gaussian Processes.Analyzing robustness and making counterfactual explanations of reinforcement learning agents.Performing causal analysis of driver behavior during severe weather event in partnership with the CASA Engineering Research Center.Teaching Assistant for COMPSCI 187: Programming with Data Structures, Fall 202

Pursuing an Master of Science in Computer Science. Focusing research on explainable AI, applied machine learning, and fairness in AI.

Teaching assistant for COMPSCI 688: Probabilistic Graphical Models, a PhD-level statistical machine learning course

Leading lab sessions and holding office hours for COMPSCI 187: Programming with Data Structures, an entry-level course for undergraduates

Customer-facing rotational program focused on leadership training, user technical support, and software engineering for MATLAB and Simulink. • Extensively trained in ownership, documentation, and communication.• Built Docker-based micro-services with Go to create scalable cloud systems that afford load balancing to contribute to customer success. Highlights include concurrent programming, containerized workflows and thorough unit, and service-level integration testing.• Contributed to the Statistics and Machine Learning Toolbox optimizing graphing code for dendrogram chart.• Improved user experience in Graphics and Charting Tools by modifying charting behavior in C++ source code.• Provided technical support for the use of MATLAB to customers in a variety of research, scientific, and engineering domains. Documented patterns, reproduced customer workflows, and published workaround and how-to articles.

In the Biologically Inspired Neural and Dynamical Systems LaboratoryDeveloped deep learning models with TensorFlow for regressing silicon wafer etch measurements with Lam Research Corporation. Prediction accuracy approached the sensitivity of the imaging equipment used for measurement. Resulting paper:https://arxiv.org/abs/1910.10067

Received $10,000+ for placing first the HackUMass V challenge to produce a mobile application to crowd source information to aid in navigation around the UMass campus. We were hired on as a dedicated team working on the refinement and further development of the application.We designed and developed a cross-platform, mobile application for iOS and Android using ReactNative to help visitors and residents of the UMass campus navigate between and within buildings, with the primary focus of providing fast, safe routes from location to location. A primary goal of the development was to make the full app ADA-compliant, so we had rigorous screenreader testing performed as part of the development process.

Designed and implemented a document repository with ElasticSearch, Node, and Bootstrap.

Ensuring the safety and well-being of the students above all else, I helped children from preschool to eighth grade with projects, homework, improvement of skills, and time management when their parents worked outside the hours of the standard school day.

Trained in developing LAMP with Wordpress and Node.js-Express stacks with single-page architecture front ends and MySQL backend databases tied together with Socket.IO interactions.