We welcome our new postdoc Dr. Shahab Pasha! His research field is applying machine learning and artificial intelligence to the field of acoustics and speech processing. Shahab will be focusing on cardiovascular anomaly detection by Artificial Intelligence (AI). The goal is that patients with heart conditions can record their heart sounds and get it assessed by an AI system online.
Can you tell us a little about your background?
As a kid, I was fascinated by technology and what humans can design and build to get complex tasks done. The level of human creativity in the engineering context has always been interesting and inspiring for me. From my perspective engineering is how humanity goes beyond the natural limits.
Therefore, I applied to Iran University of Science and Technology (IUST), where I received a bachelor of Electrical Engineering. I got my Master of Digital Electronics from Sharif University of Technology (International campus) in Iran. I did my PhD on Acoustic scene analysis using machine learning at the University of Wollongong, NSW, Australia.
After finishing my PhD, I worked for the Bluescope steel industry at port-kembla, NSW, Australia as a researcher. I designed and implemented deep learnt acoustic monitoring systems.
What is your area of interest?
My research field is applying artificial intelligence in the context of acoustics and speech processing.
What is it that you are going to research on here at STC?
I will investigating the applications of deep learning techniques in tele-medicine and remotely controlled health assessments. I will be focusing on cardiovascular anomaly detection by sound.
Using machine learning and acoustic monitoring facilitate the concept of remote health assessment. It will be possible for patients with heart conditions to record their own heart sound and get it assessed by an AI system online. The doctors would be called in, only if necessary. This saves both long trips for the patients and time for the doctors. The system can also be applied for regular heart assessments. Real-time monitoring of the patient’s heart sound and other vital signs can also help predicting emergency issues.
How do you like it here at Mid Sweden University?
I am enjoying the positive and supportive atmosphere of the department. I am also very happy that I work in the calm and beautiful city of Sundsvall. The natural sceneries are wonderful.
What do you do in your spare time?
I like hiking, swimming and reading. I will see if I dare to try skiing…