Resume

Prof. Dr. Kamarul Imran Musa MD, M Comm Med, PhD- Resume

Prof. Dr. Kamarul Imran Musa

MD, M Comm Med, PhD

Professor in Epidemiology & Statistics | AI & Machine Learning Researcher | Public Health Physician

📧 drkamarul@usm.my
🌐 myanalytics.com.my
💻 GitHub: @drkamarul
📍 Universiti Sains Malaysia, Kelantan

🎯 Professional Summary

Distinguished epidemiologist and statistical modeling expert with 25+ years of experience bridging clinical medicine, advanced statistics, and artificial intelligence.

Currently serving as Professor (VK7) and Head of Department of Community Medicine at Universiti Sains Malaysia. Recognized globally as Top 2% Scientist by Stanford University (2020-2024).

125,840+
Total Citations
55
H-Index
162
Publications
25+
Years Experience

🏢 Leadership Positions

Professor VK7 | Head of Department
Department of Community Medicine, School of Medical Sciences, Universiti Sains Malaysia
Sept 2023 – Present
  • Leading Malaysia’s premier epidemiology and statistics department
  • Spearheading AI/ML research initiatives in healthcare
  • Supervising 15+ doctoral students in AI/epidemiology research
Research Coordinator for Health Campus
Universiti Sains Malaysia
Jan 2024 – Dec 2026

Coordinating research activities across health disciplines and promoting interdisciplinary collaboration in AI and healthcare.

🔬 AI/ML & Technical Expertise

🤖 AI/ML Applications

  • Breast Cancer Detection (90% AUC)
  • COVID-19 Modeling & Prediction
  • Medical Image Analysis
  • Risk Prediction Models
  • Deep Learning for Healthcare

💻 Programming & Analytics

  • R Programming (Expert)
  • Python for Data Science
  • Machine Learning Algorithms
  • Statistical Modeling
  • Bayesian Methods

📊 Data Science & Visualization

  • Reproducible Research
  • Geospatial Analysis
  • R Shiny Dashboards
  • Time Series Analysis
  • Survival Analysis

🏥 Healthcare Domains

  • Epidemiological Modeling
  • Disease Surveillance
  • Cardiovascular Risk Assessment
  • Stroke Outcomes Prediction
  • Public Health Analytics

📚 Notable Publications & Books

“Data Analysis in Medicine and Health Using R”
CRC Press, 2024
Analytics and AI for Healthcare Series. Comprehensive guide covering statistical modeling, machine learning, and AI applications in healthcare research.
“Diagnostic Accuracy of Machine Learning Models on Mammography”
Diagnostics, 2022
Meta-analysis of 36 studies containing 68 ML models. Overall AUC: 0.90, demonstrating excellence in AI-powered medical diagnostics.
“Over-the-Counter Breast Cancer Classification Using Machine Learning”
Diagnostics, 2022
Developed 8 ML models for breast cancer risk estimation using patient registration records.

🌍 International Collaborations

Global Burden of Disease (GBD)
University of Washington
NCD Risk Factor Collaboration
Imperial College London
R Epidemic Consortium
Infectious Disease Modeling
MIDAS Network
Mathematical Modeling
RIBURST Study
Steering Committee Member
WHO COVID-19
Expert Advisory Group

🏆 Recognition & Impact

  • 🥇 Top 2% Scientists List – Stanford University (2020-2024)
  • 🎓 Fellow of the American College of Epidemiology (FACE)
  • 🏅 Universiti Sains Malaysia Excellent Service Award (2010, 2018)
  • 📚 Published Author – 2 R Programming Books
  • 💰 Research Grants – RM 773,861 as Principal Investigator

🎓 Education Excellence

PhD in Statistics and Epidemiology
Lancaster University, United Kingdom
2012-2017

Supervisors: Dr. Thomas J. Keegan & Distinguished Professor Peter J. Diggle
Thesis: “Modelling of Risk Factors, Fatality and Functional Status Among Stroke Patients in Malaysia”

Master of Community Medicine
Universiti Sains Malaysia
2001-2005

Specialty: Epidemiology and Biostatistics

“Passionate about leveraging data science, artificial intelligence, and epidemiological expertise to solve complex public health challenges and improve healthcare outcomes globally.”

Resume May 2025


Resume 2023