Farag Shuweihdi
statistics machine learning data mining predictive analytics@ University of Leeds
Leeds, Leeds, United Kingdom
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Farag Shuweihdi is a highly experienced statistical analyst with 22.8 years of work experience. He holds a PhD in data mining from the UK and currently works as an academic staff at the University of Leeds, Leeds Institute of Health Science. Farag's expertise lies in statistical modeling, data mining, statistics, SPSS, and R. He has a strong background in teaching and research in classification and predictive modeling, and his current research focuses on machine learning and the use of primary/secondary care databases. Farag is skilled in conducting research using longitudinal and cross-sectional studies, conducting machine learning methods, and utilizing R, SPSS, and STATA programs. He also has considerable experience in Meta-Analysis.
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@christie.nhs.uk
@adm.leeds.ac.uk
@leeds.ac.uk
+44 113243****
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About

I have PhD in data mining from the UK. At present, I am academic staff at the University of Leeds, Leeds Institute of Health Science. I have many years’ experience in teaching and research in classification and predictive modeling. My current research involves Machine learning and the use primary/secondary care Database to evaluate long-term outcomes. I conduct research using longitudinal and cross-sectional studies in terms of; for example, structural equation models (SEM), latent growth models, diagnostic and prognostic analysis models. I perform and validate machine learning methods (supervised and supervised learning), such as: discriminant analysis, elastic-net, LASSO, logistic regression, PLS, neural network, vector support machine and clustering. I use R, SPSS and STATA programs in conducting statistical analysis for research and teaching. Moreover, I have considerable experience in Meta-Analysis. I speak Arabic and English languages.

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Work Experience

Woodhouse Lane, Leeds, West Yorkshire LS2 9JT, GB
11000
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Farag Shuweihdi's Professional Milestones

  • Research Visitor (2010-01-01~2013-01-01): Discovering new research materials and driving successful research projects.
  • Statistician (2015-12-01~): Developing accurate and comprehensive data analysis techniques to optimize decision-making and drive data-driven decision-making.
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