Design, build, and test a human torso simulator for use in surgical training. The simulator will hold replica organs and be useful in training both humans and DaVinci surgical robots.

Traditional bathmats present several challenges, retaining moisture, promoting microbial growth, and requiring frequent maintenance, while stone-based alternatives are brittle and degrade over time. These limitations leave consumers without a durable, hygienic, and efficient solution for moisture management in both residential bathrooms and wet public environments like pool decks.
DryStep is a super-adsorbent, mineral-based bathmat that redefines moisture control through a freeze-casting technique that creates dendritic pore structures for rapid water wicking and evaporation. Our product incorporates a composite of diatomaceous earth, banana fibers, nano-silica, and environmentally safe binders to balance absorbency with mechanical strength. Unlike existing cloth or brittle stone mats, DryStep is designed for long-term durability, fast drying, and anti-slip performance.

This project focuses on real-time gesture-based motion control of the Crazyflie 2.1 nano quadcopter using a machine learning model deployed on the GAP8 AI deck. The system uses camera-based hand gesture recognition, where x-y coordinates of tracked hand movements are extracted using MediaPipe and processed as input to a lightweight neural network.
The gesture recognition model is trained offline using time-series data of hand positions captured during predefined motions—such as upward swipes for ascending, downward gestures for descending, or lateral movements for turning. This data is used to train a neural network capable of classifying dynamic gestures in real-time. Once trained, the model is quantized and deployed to the ultra-low-power GAP8 processor.
The project demonstrates the feasibility of vision-based embedded ML on resource-constrained platforms. It highlights the integration of real-time gesture classification, camera-based input processing, and embedded deployment using the GAPflow toolchain, showcasing skills in time-series vision data handling, model optimization, and real-time system design for edge AI applications in robotics.

Magic Mirror is an AI-powered skincare analysis app that puts personalized, expert-level insights directly in users’ hands. By simply taking a selfie, users receive instant skin assessments, including detection of concerns like breakouts, redness, and dryness. The app then delivers tailored product recommendations — from science-backed products (via affiliate brand partnerships) to daily habit adjustments — all designed to improve skin health, confidence, and decision-making.