• Led our club’s contract team responsible for client app development and published a client app on the App Store• Secured semester-long contracts with 3 startups and 1 nonprofit, implemented Agile development leading 3 PMs and 18 developers utilizing technologies such as Supabase, Twilio, Jest, Figma, React Native

• Worked on the Amazon Maps Location Intelligence Team• Built and deployed an ML prediction tracking system to collect predictions and input data from an onboard activity classification model in the Amazon Flex iOS app (used by all Prime drivers for delivery routing)

•Taught course on Java, inheritance, asymptotics, sorting, tree and graph traversals, hashing, and more

• Taught course on computer memory, assembly, CPU, parallelism, caching, virtual memory, coding a handwritten digit ML classifier in RISC-V, building a CPU in Logisim, and more

• Worked for the Laboratory for Materials and Device Innovation at Berkeley, advised by Professor Ali Javey, Ph.D.• Scaled BLE data transmission from sweat sensors to Android app 13X using Java, allowing novel sweat mapping• Implemented MVVM architectural pattern, enabling multi-device real-time sweat rate measurements, and integrated 3 event-driven listeners to ensure efficient UI data updates and seamless device connectivity

• Interned at Fingenic, Inc. through the Berkeley Skydeck ACE Program• Spearheaded a complete upgrade from the initial outsourced front-end, establishing a more robust mobile app MVP

• Worked for the Biomaterials and Interface Tissue Engineering Laboratory ML team, advised by Helen H. Lu, Ph.D.• Jointly developed and coded a cloud-based machine learning algorithm for lateral flow immunoassay-based quantitative detection of SARS-CoV-2 from nasal swabs utilizing transfer learning with TensorFlow and Inception-Resnet-V2•Fully designed and programmed a Flask website with three neural networks integrated and a full Firebase database and authentication and launched it to Google App Engine