Nadia Yaghoobi

I am an engineer and research scientist with a strong background in advanced analytics, predictive modeling, and machine learning, with experience spanning academic research and industry applications. My work focuses on extracting actionable insights from complex, multi-source datasets using statistical analysis and time-series modeling. I have led end-to-end analytics projects, developed and validated predictive models, and communicated results to both technical and non-technical stakeholders.

I am an engineer and a research scientist with experience across academic research, healthcare, and industry analytics. I have led end-to-end analytics and machine learning projects involving large, multi-dimensional and time-series datasets, developing and validating predictive models using regression and neural network approaches. My background includes applied research in wearable sensing and physiological modeling, advanced analytics in healthcare and technology environments, and cross-functional collaboration with engineering, clinical, and analytics teams. I am experienced in building scalable Python pipelines, performing rigorous model evaluation, and translating complex analytical results into clear, actionable insights for diverse stakeholders.

I hold a Master of Science in Mechatronic Systems Engineering from Simon Fraser University, where my research focused on developing clinically accurate, wearable-based systems for blood pressure estimation using advanced signal processing and machine learning techniques. I also earned a Bachelor of Science in Electrical Engineering from Iran University of Science and Technology, which provided a strong foundation in systems engineering, data analysis, and applied mathematics.