Rafeef Garbi (née Abugharbieh)

Professor, Biomedical Signal & Image Computing Lab, Founder 
MSc, PhD (Göteborg, Sweden), P.Eng

Office: KAIS 4051
Phone: (604) 822-6034
Fax: (604) 822-5949
Email: rafeef@ece.ubc.ca

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Dr. Garbi is a Professor in the Department of Electrical and Computer Engineering at UBC. She is the Founder and Director of BiSICL, The Biomedical Signal and Image Computing Lab, a UBC multidisciplinary research laboratory focusing on visual computing in biomedical imaging. Dr. Garbi received her PhD, Technical Licentiate, and MSc (with distinction) degrees from the School of Electrical and Computer Engineering, Chalmers University in Göteborg, Sweden where she was a member of the Department of Signals and Systems.  She is a registered member of the Association of Professional Engineers and Geoscientists of British Columbia (PEng, APEGBC), a UBC Killam Faculty Research Fellow, a Peter Wall Institute for Advanced Studies (PWIAS) Early Career Scholar, and a senior member of the Institute of Electrical and Electronics Engineers (IEEE). She is a member of the IEEE Engineering in Medicine and Biology Society (EMBS), an associate founding member of the IEEE EMBS Vancouver Section, and a member of the Medical Image Computing and Computer-Assisted Intervention (MICCAI) Society.

Rafeef Garbi (née Abugharbieh) received her PhD, Technical Licentiate, and MSc (with distinction) from the School of Electrical and Computer Engineering, Chalmers University in Göteborg, Sweden. She is a registered member of the Association of Professional Engineers and Geoscientists of British Columbia (PEng), a UBC Killam Faculty Research Fellow, a senior member of the Institute of Electrical and Electronics Engineers (IEEE), and an associate founding member of the IEEE Engineering in Medicine and Biology Society (EMBS) Vancouver Section.

The focus of Dr. Garbi’s multidisciplinary research laboratory is on visual computing in biomedical imaging. Her lab develops novel computational techniques for efficient, reproducible, accurate and robust analysis of structural and functional multi-dimensional biomedical data. This can be in the form of novel medical image-based metrics or biomarkers to assess and track disease and evaluate therapies, or automated techniques for computer-aided intervention.


Research Interests

Medical image computing; Computer vision; Image analysis; Machine learning for medical imaging; Biomedical applications


Research Area


Research Groups


Teaching

  • ELEC 202 – Circuit Analysis II
  • ELEC 221 – Signals and Systems
  • ELEC 421 – Digital Signal and Image Processing
  • ELEC 442 – Biosignals and Systems
  • EECE 570 – Fundamentals of  Visual Computing

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