Dr. Babar Zaman / Research & Teaching
Statistician &
Data Scientist
Statistics · Machine Learning · Quantitative Analysis
Dr. Babar Zaman
Statistician & Data Scientist
Assistant Professor · GIK Institute of Engineering Sciences and Technology
Topi, Swabi, Pakistan
My work brings together statistical process control, machine learning, digital twins and biostatistics. I also apply AI and machine learning to quantitative analysis of forex, stock and cryptocurrency markets.
Research directions
Statistical process control
Mixed and adaptive memory control charts, EWMA and CUSUM methods, and efficient detection of shifts in process location and dispersion.
02 / Data driven methodsMachine learning for monitoring
Neural networks, supervised learning and predictive analytics for statistical process monitoring.
03 / Dynamical systemsDigital twins
Physics-informed modelling, structural health monitoring and prognostics of dynamical systems.
04 / Health dataBiostatistics and registries
Clinical data management, statistical analysis and web-based disease registries, informed by research experience in ophthalmology.
05 / Financial marketsAI and ML for quantitative analysis
Applying artificial intelligence (AI) and machine learning (ML) to quantitative analysis of forex, stocks and cryptocurrencies.
Teaching and mentorship
Statistics and mathematics provide the foundations for engineering, data science and artificial intelligence. My teaching spans undergraduate and graduate courses, alongside research supervision and student advising.
- Probability and statistical inference
- Mathematics for machine learning
- Research in process monitoring and digital twins
Selected recent publications
- 2026
Shaheen, A., Zaman, B., Nadir, S., Mukhtiar, F., & Butt, N. R. (2026). Semi-parametric Bayesian physics-informed neural network-based digital twin for dynamical systems. Expert Systems with Applications, 133907
- 2026
Tauqeer, F., Zaman, B., Riaz, M., & Arshad, I. A. (2026). A multivariate adaptive cumulative sum control chart based on machine learning approach, support vector regression with applications. The International Journal of Advanced Manufacturing Technology, 1-29
- 2026
Mukhtiar, F., Zaman, B., Butt, N. R., Ajab, M., & Faraz, M. I. (2026). Data-driven control charts for monitoring Gamma-distributed manufacturing processes using machine learning. The International Journal of Advanced Manufacturing Technology, 1-30
Start a conversation
For research collaboration, supervision enquiries or academic discussions, contact me through my institutional email.
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