Ricky holds a Ph.D. in Electrical and Computer Engineering, with a specialization in advanced data science and machine learning methodologies. As a Postdoctoral Research Fellow at the Implantable Biosensing Laboratory at the University of British Columbia, he focuses on developing novel machine learning algorithms to derive tissue perfusion from near-infrared spectroscopy (NIRS) measurements.
Education
- Ph.D., Electrical and Computer Engineering, University of Washington (2019–2023)
- M.Sc., Electrical and Computer Engineering, University of Washington (2017–2019)
- B.Sc., Electrical Engineering, Drexel University (2014–2017)
Current Projects
- Developing and testing advanced signal processing methods for using NIRS to calculate and monitor spinal cord perfusion parameters.
- Designing machine learning and deep learning algorithms to integrate multi-modal data and refine NIRS-derived metrics.
Interests
Machine Learning, Computer Vision, Natural Language Processing, Signal Processing, Data Science)