Shadi holds a BSc and MSc in Computer Science and Engineering, along with a Ph.D. in Mechatronics Engineering from SFU. With research experience at BC Cancer, she specializes in Data Science and Machine Learning for cancer detection and treatment. Proficient in Python, MATLAB, C++, and statistical analysis, she excels at extracting insights from complex datasets. In her role as a Postdoctoral Research Fellow at the Implantable Biosensing Laboratory (IBL) within the International Collaboration on Repair Discoveries (ICORD), UBC, she focuses on signal and image processing, biosensor development, and advanced data analysis, with key responsibilities in developing tissue hemodynamics measures from NIRS signals and establishing new measures of tissue perfusion.
Education
- PhD, Mechatronics Systems Engineering, Simon Fraser University (SFU), BC, Canada (2020 – 2023)
- MSc, Computer Science and Engineering, Shahid Beheshti University (SBU), Tehran, Iran (2016 – 2018)
- BSc, Computing Science, Simon Fraser University (SFU), BC, Canada (2011 – 2015)
Awards
- The Young Investigator Award, BC Cancer, 2023
- Research and Innovation Award, BC Cancer, 2023
- Faculty of Applied Science Graduate Fellowship, Simon Fraser University, 2023
- Mechatronics Systems Engineering Graduate Fellowship, Simon Fraser University, 2020, 2021, 2022
- Mechatronics Systems Engineering Entrance Scholarship, Simon Fraser University, 2020
- Ontario Graduate Scholarship (OGS), Ryerson University, 2019
- Highest M.Sc. Thesis Award, Shahid Beheshti University, 2018
Current Projects
- Developing tissue hemodynamics measures from NIRS signals
- Creating new measures of tissue perfusion through NIRS signal processing
- Conducting system testing, in vitro and in vivo data collection and analysis
Interests
Data Science, Machine Learning, Statistics, Biosensors, Signal & Image Processing, Research and Development