Rand Elshereef
Sessional Instructor @W Booth School Of Engineering Practice And Technology, Mcmaster University
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WORK HISTORY
Sessional Instructor @W Booth School Of Engineering Practice And Technology, Mcmaster University
EDUCATION
El-Istiklal Secondary School
High school diploma
University of Waterloo
PhD
Boğaziçi University
Bachelor of Science
Mohawk College
Diploma
McMaster University
Master of Engineering
SKILLS
ABOUT RAND ELSHEREEF
Data scientist and process modeling expert with +17 yrs of research and industrial experience in statistical data analysis and machine learning applications (i.e. optimization, troubleshooting, monitoring, fault detection, diagnostics, quality control of pharma processes). Results driven professional with impressive analytical and technical support abilities. PhD in chemical engineering from the university of Waterloo, ranked #1 school in Canada for computer science and engineering. Postdoctoral studies under supervision of Dr. John MacGregor, the father of modern process systems engineering in Canada. Extensive experience in: • conducting statistical multivariate data analysis for commercial biopharmaceutical processes. • cell culture processes, upstream and downstream processes, methods for final product quality assessment. • developing data workflows using KNIME to extract, transform and analyze data from multiple data sources ensuring data quality and integrity from source to the final output. • PAT applications in pharmaceutical industry, such as Fluorescence, UV-Vis, NIR, FTIR, Raman, Dielectric Spectroscopy. • statistical data analysis packages (JMP, SIMCA-P, Eigenvector, Aspen ProMV and Camo Unscrambler) • programming in Matlab and Python • taking leadership roles, working effectively in individual and team oriented environments. • handling multiple projects simultaneously in a fast-paced environment. • utilizing in-depth knowledge, advanced problem-solving skills, and awareness of priorities to achieve stated results. • effectively communicating complex statistical ideas to non-statisticians and multi-functional teams
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