Fazel Famili

Biography

Dr. Fazel Famili is a Data Scientist working as a Data Analytics Consultant in various domains such as Engineering and Life Sciences. His research interests include data mining, pattern recognition, machine learning, bioinformatics, disease modeling based on genomics and proteomics data, and knowledge discovery from on-line or historical data. His research currently focuses on data analytics, automated knowledge discovery, bioinformatics and decision support systems. In 1986 he initiated the data mining research at NRC focusing on engineering applications (such as manufacturing and process control) and successfully deployed a data mining software in Semiconductor manufacturing and transferred this technology to a software company. He also worked extensively in Aerospace domain where he developed the first automated data mining software for which he obtained a US data mining patent. In 1999, he initiated the BioMine project at NRC, for which he was the Project Leader. This project became the foundation of joint data mining in genomics, proteomics, and bioinformatics research between several NRC Institutes and also research groups outside of NRC, such as University of Ottawa, Children’s Hospital of Eastern Ontario and Canadian Leukemia Studies Group. The project was partially funded by the Genome Health Initiative. This research Has produced several unique publications, collaborative case studies involving public and Private data sets and some novel discoveries related to many model organisms. Among his other achievements are several data mining tools and novel data mining methodologies, particularly suitable for gene identification, gene response analysis, disease classifications and disease modeling and also  a number of publications that include their case studies.  

Research Interest

Dr. Fazel's research interests include data mining, pattern recognition, machine learning, bioinformatics, disease modeling based on genomics and proteomics data, and knowledge discovery from on-line or historical data. His research currently focuses on data analytics, automated knowledge discovery, bioinformatics and decision support systems.