Breast cancer is the leading cause of cancer-related deaths among women in Uganda, due to diagnostic delays of 11 months driven by limited pathology resources and centralized healthcare services. Over 80% of Ugandan women are diagnosed at late stages with significantly increased treatment costs. To address this challenge, Ekyaalo Diagnostics, a novel low-cost cytopathology assessment system, aims to provide point-of-care breast cancer diagnosis in rural healthcare centers in Uganda. Our solution integrates existing smartphones and microscopes with Machine Learning algorithms to interpret fine needle aspiration (FNA) biopsy samples for a more efficient and accurate diagnosis.

As Baltimore continues to urbanize, monitoring and preserving its biodiversity is critical. This project proposes a scalable, automated system for bird population monitoring using passive acoustic sensing. Compact, low-power devices will be deployed to continuously capture bird chirps. Each unit features a microphone, microcontroller for real-time audio processing, GPS for location tagging, and wireless communication for data transmission. Onboard algorithms will classify bird species by their vocalizations and log activity patterns over time. Aggregated data will reveal trends in species distribution, vocalization frequency, and long-term population changes.

This project explores how various collodiol materials can be manipulated in AC electric fields for applications in aerospace, defense, and soft robotics. Materials investigated include SU-8, Lithium Iron Phosphate (LFP) Lithium Aluminum Titanium Phosphate (LATP), and Sodium Super Ionic Conductor (NASICON). These materials were examined for their ability to respond to electric fields, with particular focus on the interactions between particles and the field, such as the dipole-field potential.

Dancers face high foot, ankle, and knee injury rates due to improper form during pointe work and jumping movements from en pointe positions. Our device combines pressure mapping, haptic feedback motors, and an inertial measurement unit (IMU) to provide dancers with live feedback on their pointe work, preventing injuries before they occur. A flexible printed circuit board (PCB) with force sensors and a rigid PCB with microcontroller and IMU work together to correct dancers. The motors will vibrate to guide the dancer on how they should adjust to achieve proper form, alongside an LED for visual feedback. The sensors are housed in a 3D printed sleeve with connections to the rigid PCB worn on a band around the ankle, making it easy to integrate into a dancer’s existing routine. Ten dancers of varying skill levels will be tested to evaluate the device’s performance. We anticipate this innovation improving dancer safety by offering an accessible and affordable tool for injury prevention.