• Launched three features in production for Google Ads, starting from the design document to the launchdocument• Restructured full-stack data piping flow for dynamically rendering hotel performance max (pmax) ad previews, leading to an 11% increase in the average ad strength score• Researched, designed, and implemented full-stack features to enable pre and post-save external preview sharing for Responsive Search Ads in the search ad editor (1M+ views per day), and Retail Pmax and Hotel Pmax in the pmax ad editor (100k+ views per day)

• Developed & trained a Fully Convolutional Network model to segment water in images, reached 73% segmentation precision & 80% bounding box precision; presented at AGU (2020) & EarthCube (2022)• Semi-automated monoplotting (a computer vision technique) process to establish a correlation between 100+ flood photos & elevation data; presented at AGU (2021)• Helped implement a Convolutional Neural Network model to predict flood phases from Twitter tweets, achieved 92% precision; published paper to IEEE Xplore (2020)

The New Jersey Governor's School of Engineering & Technology at Rutgers University is an intensive residential summer program that brings together some of New Jersey's most talented and motivated high school students. Free of grades and offical credit, students spend part of the summer following their junior year studying on the campus of the Rutgers University School of Engineering at no cost to their families. During the program, students will have the opportunity to collaborate with two to four students on a novel research project which will be showcased in a conference-style final paper and presentation in front of hundreds of invited guests at our research symposium. Additionally, students will be able to participate in a variety of life-skills workshops, attend site visits to local corporations, and engage in activities that will help them connect with professors, professionals, and peers from throughout the state.Core Courses: Robotics, PhysicsElectives: Fundamentals of Micro- and Nanofabrication, Computer Simulation of Electronic Circuits Project Name: Human Emotions and Gestures• Implemented, trained, & fine-tuned Convolutional Neural Network model to recognize facial emotion; fused model w/ tonal-emotion model achieved 69% testing accuracy• Published to IEEE Xplore (2022); presented in AI track to 100+ at the IEEE MIT URTC Conference (2021)• 1st in Robotics competition, efficiently programmed robots to navigate complex maze