The Young Researcher (Peer-Reviewed Research Journal): I was one of 20 students in the nation to be selected for publication in "The Young Researcher" - a peer-reviewed journal dedicated to publishing original research.
College Board: I was one of 2 students in the country selected by the College Board, whose research work was published as a perfect scoring exemplar model for the AP Research course.
Upwards of 7.5 million people suffer from speech impairments caused by stroke, ALS, and cerebral palsy. To help these patients, we currently have a few technological solutions such as eye/cheek trackers which are inefficient/expensive.
To address these issues, SpeakUp, an ML-based speech-aid, was developed. Although paralyzed patients cannot speak, their brain still sends EMG signals to the speech system. Recent advancements in Machine Learning and AI have enabled these EMG signals to be processed and translated into speech. When a person tries to speak, SpeakUp captures and records the subtle neurological EMG signals generated from the speech muscles using modern sensors. SpeakUp was able to translate EMG signals into speech and enabled paralyzed patients to communicate in real-time. This device has an accuracy of 80.1% and was developed for under $100.