Ruben H Zamar

Ruben H. Zamar is a Professor in the Department of Statistics at the University of British Columbia (UBC), affiliated with the Faculty of Science. His research focuses on robust statistics, data mining, statistical computing, and bioinformatics, with notable contributions to outlier detection and robust estimation methods such as the Linear Grouping Algorithm (LGA) and CLUES clustering. He collaborates extensively with computer scientists like Raymond Ng and Laks Lakshmanan on projects funded by MITACS and NSERC. Zamar holds a Ph.D. in Statistics from the University of Washington (1985), alongside degrees in Economics, Mathematics, and Statistics from institutions in Argentina, Chile, and Brazil.

His work has been recognized through awards such as the Best Paper Award at KDD 2001 and UBC's Science Research Achievement Awards. Key research areas include robust regression, outlier propagation modeling, and bioinformatics applications in cardiovascular studies. He has supervised numerous graduate students and postdoctoral fellows, contributing to advancements in robust statistical methodologies and their computational implementations.

Zamar’s current projects involve developing robust algorithms for high-dimensional data and integrating robust statistics with machine learning techniques. His research also extends to biomedical applications, including biomarker development for allograft rejection through collaborations with the iCAPTURE Centre.

• Education:
  • Ph.D., Statistics, University of Washington (1985)
  • M.Sc., Mathematics, Universidade de Pernambuco (1981)
  • M.Sc., Statistics, CIENES (1977)
  • Bachelor’s in Economics, Universidad de Córdoba (1973)
• Grants & Funding:
  • NSERC Discovery Grant (2004–2009)
  • Mitacs Project “Toward Interactive Data Mining” (2001–2003)
  • Collaborative NIH-funded project on biomarkers (2001–2004)