Prativa

In the quest to break through the limitations of conventional computing paradigms, neuromorphic computing emerges as a revolutionary approach, inspired by the structure and functioning of the human brain. Neuromorphic computing seeks to mimic the neural architectures and operational principles of biological nervous systems to achieve promising levels of efficiency and adaptability. This talk delves into the fundamental concepts, potential applications, and areas for improvement in neuromorphic computing.

Biography:

Prativa Hartnett is a Research Computer Scientist in the Aritificial Intelligence Department at Southwest Research Institute (SwRI). Mrs. Hartnett received her master’s degree in Statistics and Data Science focusing on artificial intelligence (AI), machine learning (ML), and deep learning (DL); during her graduate studies, Mrs. Hartnett conducted research in the MATRIX Neuromorphic Artificial Intelligence Laboratory. Among her focus on bringing artificial intelligence and machine learning solutions to healthcare sector, she is passionate about the applications of Neuromorphic Computing. She has led an Internal Research and Development (IR&D) project entitled, “Real-Time, Personalized Cognitive Load Classification on The Edge Using Spiking Neural Networks (SNNs),” that involved using SNNs to classify cognitive load in subjects using data from a wrist-worn wearable device. She is also currently involved in “Spiking Neural Networks (SNNs) to Predict Outcomes of Mild Traumatic Brain Injury (mTBI)”. This IR is based on designing and training a Twin SNN architecture that model TBI brain dynamics in a public, longitudinal study consisting of mTBI patients and healthy controls. In addition, she has experience in developing SNNs for Cognitive Electronic Warfare systems, radioisotope detection, and human activity recognition.

Address:United States