India faces major healthcare access challenges, especially in rural areas with limited doctors and long travel times. Telemedicine bridges this gap, but current clinical history-taking at the community level is inefficient—CHWs often collect lengthy, unfocused histories before connecting with hub doctors. Our project leverages AI and Large Language Models (LLMs) to create an adaptive, efficient history-taking tool that guides CHWs to ask relevant questions based on patient responses. This system reduces consultation time, improves information quality, and helps doctors make quicker, more accurate decisions. We are developing and optimizing this tool using agent-based simulations and prompt engineering, and will evaluate its performance with both expert clinical reviewers and in a real-world pilot in rural Nashik, India. This innovation aims to enhance care quality, reduce delays, and ultimately scale across India’s public telemedicine ecosystem, including eSanjeevani.

In collaboration with the Disabled American Veterans (DAV) organization, our team was tasked with developing adaptive sports equipment to increase accessibility for veterans with disabilities. Following user interviews at DAV’s National Disabled Veterans Golf Clinic, we identified disc golf as a sport with high potential for inclusive participation. We divided into two sub-teams to address distinct user needs. The motor impairment sub-team focused on players with partial quadriplegia, designing a disc launcher that enables controlled throwing without requiring upper trunk rotation. The visual impairment sub-team developed a wearable armband that uses directional haptic feedback to help players locate the basket and retrieve discs independently. Together, these solutions promote greater independence, inclusion, and enjoyment in adaptive sports.

In high-intensity combat zones, military medics face immense challenges in documenting and transmitting critical patient data. The Tactical Combat Casualty Care (TCCC) card, currently used by the US military and NATO, is essential for recording injuries and treatments in the field. However, its paper-based format is prone to loss, damage, and delays in data transmission, leading to inefficiencies in medical response and treatment continuity.

Through interviews with US military personnel, we learned that 8 times out of 10, the TCCC card gets lost during evacuation, resulting in critical medical data not reaching the hospital in time. Our solution digitizes this process to enhance speed, accuracy, and integration with modern medical infrastructure

Our solution is a ruggedized military iPad application that digitizes the TCCC card through AI-powered image recognition and voice-to-text processing eliminating the inefficiencies of paper-based documentation.

A design for an electronic capsule capable of recording data from an IR thermal camera and transmitting it wirelessly to another transceiver.