Track 3: Machine Learning/Deep Learning | Room: 1205
Saeed Esmaili, Assistant Professor, Harrisburg University;
Siamak Aram, Assistant Professor, Harrisburg University;
Roozbeh Sadeghian, Assistant Professor, Harrisburg University

The study focuses on the information gathered by Functional Near-infrared Spectroscopy (fNIRS) and Iowa Gambling Task (IGT) to study how prefrontal cortex brain activation and gaming addiction correlate. This will give the primary results for the hypothesis on how the choices one makes in real life are connected to the prefrontal cortex’s hemodynamic changes, which are tied to the decision a person makes. As a pilot study, we are investigating brain activity using fNIRS to identify the characteristics of addictive behavior in gaming and e-sports.

Using both approaches, IGT and fNIRS gives us a new mechanism that enables us to make more accurate characterizations of the link between a person’s decision-making abilities, their hemodynamic factors, and the responses recorded for each patient during this experiment.

As assistant professor at Harrisburg University of Science and Technology, Dr. Saeed Esmaili Sardari hopes to instill a lifelong love of learning in his students in the computer science and Information System Engineering Courses. Dr. Esmaili earned a bachelor’s in Biomedical Engineering from the National University of Tehran, Iran in 2001 before continuing his education in the United States. Here, he received a master’s in Electrical and Computer Engineering from the University of Maryland in College Park. He then went on to earn his Ph.D. in Microelectronics and Device Physics from A James Clark School of Engineering at the University of Maryland.
Dr. Siamak Aram is Assistant Professor of Computer Science and Data Analytics at Harrisburg University of Science and Technology. Dr. Aram received his B.S. degree in Software Engineering. In December 2007, he was awarded the first prize in the student passive robotic contest organized by Sharif University. Later on, he graduated from Sharif University of Technology with an M.S. degree in Information Technology Engineering – Data Security & Networking in 2010. Also, during these years, Siamak Aram was a computer developer in different languages and with different platforms, from desktop to mobile applications.
After receiving his Master’s degree in electrical engineering, Dr. Sadeghian worked for several years in industries as a senior industrial automation engineer. He pursued his Ph.D. in signal processing whereas focused on diagnosing human health disorders using machine learning and speech processing. Dr. Sadeghian worked on speech features as the baseline to diagnose the speech delay of children and Alzheimer’s disease in elderly people. He is currently an Assistant Professor of data analytics in Harrisburg University and his teaching interests are machine learning and deep networks.