Abstract
We propose a resource-efficient, real-time human activity recognition framework, transforming the multi-class classification problem into a hierarchical model based on the Metabolic Equivalent of Task (MET), creating a personalized structure for each individual.
Publication
In Activity Recognition and Prediction for Smart IoT Environments, Springer

Graduate Alumni
I am a fourth year PhD student at Washington State University. I work as a research assistant with Professor Hassan Ghasemzadeh. My research topics include embedded systems, health monitoring systems, wearable sensor development, sensor data mining, power optimization, and machine learning. I received my B.S. degree in Computer Cngineering from Amirkabir University of Technology, Tehran, Iran in 2014.

Graduate Alumni
Ramesh Kumar Sah, PhD, Computer Science, Washington State University (2018-2024)

Director
Hassan Ghasemzadeh is an Associate Professor of Biomedical Informatics at Arizona State University (ASU) and a Computer Science Adjunct Faculty at Washington State University (WSU).