Synthesizing quantitative and qualitative data to understand user needs and pain points, develop solutions, and prioritize them. Executing build projects, context sharing with engineers and designers, and making sure teams feel good about the work they do. Exploring the intersection of product work with learning sciences research around collaboration, embodiment, and mathematics education.

Developed Desmos-based curriculum with emphasis on how students interact and experience digital artifacts. Worked with designers, curriculum developers, and content specialists to create and ideate digital interactions for various Amplify products.

Migrated existing software into a new system. I interfaced, tested, and refined new database models to existing and new web pages over the site and played an active role in design planning and decision making. Much thanks to John Kelly who actively mentored me and the other interns (Saar Sayfan, Emily Cang, Robert Slutsky).

Data Science Challenge hosted by LLNL. Worked under Brenden Petersen for Deep Symbolic Regression, which generates an equation, given an input set of data. Added data visualization and regularization to a reinforcement learning model to simplify generated expressions.

By repurposing low-cost hardware purchased during the pandemic, we can create spaces for students to learn and demonstrate learning through group-based movement. Students hold AruCo markers which are detected by a system of webcams to project their position in the room onto a graph, and "become" points on a graph. This leads into easily into any kind of mathematical activity--polygon transformations, function shifts, drawing a line between two students, etc. This project is overseen by Dr. Earl Aguilera, Dr. Lynette Guzman, and Dr. Alexandria Hansen. Work in Progress presentations at CSCL 2022 and IDC 2022.

Using qualitative, interpretive analysis to walk through teaching simulation software, simSchool to provide critical perspectives on technology in teaching and learning. We shared analysis in a roundtable at AERA 2022 and in an upcoming edited volume by Phil Nichols and Antero Garcia. Publication.

Recreating Papert's Turtle at low cost to provide students with an tangle, interactive solution for teaching computer science, computational thinking, and mathematics. Worked with Daniel Milliate on CAD and mechanical engineering. Project is overseen by Ahmed Arif through UC Merced's HCI Group and is held in the CalTeach Learning Lab

Final project for EDUC 130 (Knowing and Learning in Mathematics and Science). Interaction analysis of students coding through a Python simulation of the RC Cola Problem. Defined different styles of coding and discussed the limitations and affordances of each in terms of mathematical discussion and understanding.

MESA lab built a classifier of good versus bad pilots through their remote control signals logs. Once known, the quadcopter would take any appropriate action (emergency land, switch to auto-pilot, etc.). We explored the use of generative adversarial networks to generate pilot flight logs to feed into simulations as well. Explored various simulation softwares to train neural networks and onboarded new students to learn introductory robotics.