AKM Jahangir Alam Majumder, University of South Carolina Upstate, United States of America
Title : Predicting Early Warning Signs of Mental Health Crisis: A Robust Approach Using AI
Mental Health problems have significant negative impacts on a substantial number of the world’s population. Artificial Intelligence (AI) could help identify the mental health of individuals by analyzing
physiological data, especially the patient with underlying health condition and that raise their risk for developing more serious cases of novel corona virus (COVID-19). AI could aid in addressing mental health concerns to create a robust and secure Human-in-the-Loop system for mental health problems. Also, the widespread adoption of smart wearable Internet of Things (IoT) devices and social media is generating population-scale data about people’s behavior in their everyday lives. The goal of this project is to advance awareness of mental health issues that affect an increasing number of individuals. This work focus on using AI techniques to detect early warning signs of behavioral anomalies as a prerequisite for creating solutions. To accomplish this, the project will incorporate newly available technologies such as smart wearable IoT sensors that can be immediately useful to health professionals monitoring at risk patients. This research will be one of the first to utilize affective computing and true methodologies such as Generalize Linear Model, Logistic Regression, and Artificial Neural Networks (ANN) in accompaniment with wearable devices to
accomplish the desired outcomes. These methodologies will be used to provide a better understanding of hhuman physical and psychometric conditions so that intervention can be undertaken prior to an episode of devastating health.
AKM Jahangir Alam Majumder is an Assistant Professor at the Division of Mathematics and Computer Science at University of South Carolina Upstate, SC. His research explores the development of embedded Internet of Things (IoT) systems and Cyber-Physical-Systems (CPS) with special interests on CPS design automation, model-based design, development of mobile computing technologies, and CPS security. From 2016 to 2018, he was a Visiting Assistant Professor at the department of Electrical and Computer Engineering (ECE) at Miami University, Oxford, OH. He received his Ph.D. in Computational Sciences in 2016 from Marquette University, Milwaukee Wisconsin. Before coming to Marquette, he worked as an Assistant Professor in the department of Electrical and Electronic Engineering (EEE) at Ahsanullah University of Science and Technology (AUST) of Bangladesh. He has been serving as a program committee (PC) member and reviewer in many reputed Journals and Conferences, and his publications have been cited over 200 times.