🦅 Dr. Ahmad Muhammad

Ahmad Muhammad is a data physicist and researcher and author currently serving at Qatar University, College of Arts and Sciences, Department of Physics and Materials Sciences. His work centers on developing mathematical frameworks for understanding system/environmental memory, causality, and coupling phenomena across multiple research domains, including Lithosphere-Atmosphere-Ionosphere (LAI). He approaches complex geophysical problems through the integration of theoretical modeling, statistical inference, machine learning, and high-performance simulation.

Dr. Muhammad's research is guided by a relational framework in which physical systems are understood through their memory properties and causal responses.

• Q-Theory (Causality & Environmental Memory): Developing the QSER framework for analyzing memory coherence in dynamical systems. The framework seeks to characterize how systems retain causal information and respond to prior states—applied to nuclear physics, lithosphere-atmosphere physics, plasma environments, and seismo-ionospheric coupling.
• Mathematical Modeling & Simulation: Application of magnetohydrodynamics (MHD), Monte Carlo methods, and computational fluid dynamics (CFD) to study aerosol transport, global electric circuit behavior, and boundary-layer ion dynamics.
• Data Analytics for Earth Physics: Use of hybrid time-series models, LSTM networks, autoencoders, and semi-supervised learning to detect anomalies in total electron content (TEC), radon emissions, and atmospheric parameters relevant to earthquake precursor studies and climate monitoring.
• Interdisciplinary Applications: Extension of these methods to renewable energy systems (e.g., perovskite and dye-sensitized solar cell stability), radioactivity assessment in water resources, and econometric modeling.

"Memory is an intrinsic property of physical systems"—a perspective informed by both theoretical physics and broader philosophical reflection.