Muhammed Aljifri

Data science and analytics professional with expertise in statistical modeling, machine learning, and data-driven decision support. Experienced in developing and applying advanced analytical methods for monitoring, prediction, and optimization across academic and industry domains. Skilled in working with complex, high-dimensional data and implementing robust solutions using statistical computing tools. Proven ability to lead and collaborate on multidisciplinary projects by applying technical expertise to deliver practical, high-impact solutions in complex data environments.

• developing Statistical Processing Control methods to monitor data processes.
• Constructed a monitoring program to monitor surgical performances and patients' readmission rates who underwent PTBD procedures at VCU hospital.
• Involved in a project to build a predictive model to predict whether a CFE lender will approve or deny a loan based on historical data.
• Built machine learning models to predict the injury severity of car crashes in association with the Civil Engineering department at UCF.

• Machine Learning-based Risk Adjusted CUSUM Control Chart for Monitoring Readmission Rate Following PTBD Catheter Placement.
• Multi-Layer Model for UV-Vis]{Beyond Beer-Lambert Linear Regression: Multi-Layer Modeling for Wide-Range Concentration Quantification based on UV-Vis Spectroscopy.
• Multiple Changepoint Detection for Ordinal Time Series