Biography

She began her professional education as a Bachelor of Science student at September 2010 in electrical engineering, at University of Tehran where she promoted her knowledge of electrical engineering and digital circuit design skills. 
 Then, she decided to put her focus on research and narrow down to a specific issue in electrical engineering. Hence, she continued her education as a Master of Science student under supervision of Prof. Zain Navabi at University of Tehran from September 2014 to June 2017. Due to her interest in digital systems design and optimization and also low power systems, she concentrated on approximate computing methods in her M.Sc. thesis.
 She started her PhD in electrical engineering at EPFL from August 2017 under supervision of Prof. David Atienza at ESL laboratory and she is now working on "Design of Event-Driven Multi-Parametric Bio-Signal Monitoring Systems" as her PhD thesis.

Current work

"Multi-Parametric Event-Driven Wearable Systems for Early Personalized Detection and Prediction of Pathological Health Conditions"
 
In my PhD, I aim to utilize advanced techniques in machine learning to have a shift toward event-driven methods. This will help to improve the performance and enable real-time monitoring of pathological health conditions detection and prediction systems. Among most common disorders, I have chosen epileptic seizures and migraine attacks to focus on, as both are ranked among the first five widespread neurological disorders worldwide. In order to fulfill these goals, during the past years, I have applied power management and self-awareness techniques in epileptic seizure detection system. I have also utilized the concept of self-awareness to efficiently communicate between edge, fog and cloud to minimize energy consumption on edge devices.  
According to the increasing demand for security of communication in order to guarantee the privacy of clients, I am moving toward the security of communication in biomedical applications using self-awareness concept.