➤ Used Python, Flask, Plotly, and Dash to independently develop a working prototype of the National Science Foundation awarded research projectMetaDash, an intuitive teacher dashboard informed by real-time multichannel self-regulated learning data.➤ Currently using AngularJS, and nest.js to create a full-stack, scalable, application version of Metadash that connects teachers to students in the classroom through websockets and data streaming, employing d3.js for advanced data visualizations➤ Automated data processing by creating Python scripts with Pandas, conserving ~15 hours of hands-on work.➤ Conducting an Honors Thesis on the application and optimization of machine learning algorithms for datamodelling of students within an AI tutoring system, employing data science and statistics methodologies.➤ Authored technical documentation for the tools and methodologies used in essay collection research by the Center for Learning and Living with AI, and led data collection sessions utilizing the iMotions platform.