Experienced Water Resources Specialist with a demonstrated history of research and management. Skilled in Remote Sensing Applications, Hydrology, Spatial Analysis, and Groundwater.
Strong community and social services professional with a Master’s degree focused in Water Resources Eng. from Tarbiat Modares University. Nowadays I’m studying in Water Resources Department, University of Isfahan. Iran.

Muhammad Mobeen is doing his PhD from the University of Hamburg, Hamburg, Germany. Previously. he has earned his M.Phil. in Geography from Department of Earth Sciences, University of Sargodha. He received M.Sc Geography (Distinction) & MS.Ed. from the University of the Punjab Lahore. He is an MA in Political Science and PGD in International Affairs as a Private candidate from Punjab University. He started his professional career in Aug-2007 as an Assistant Meteorologist (BS-16), Pakistan Meteorological Department, and then in Aug- 2008 he moved as a lecturer in Geography (BS-17) at Islamabad College for Boys G-6/3 Islamabad. He has been working as Lecturer in Geography (BS-18) at the Department of Earth Sciences, the University of Sargodha since 2010 and now he is on study leave for his PhD on the HEC cum the DAAD funding. His research interests are Climate Change, and water conflicts.

I am an Associate Professor in the Department of Industrial Engineering at the University of Engineering and Technology Taxila, Pakistan. I hold a PhD in Industrial Engineering and have more than 20 years of academic experience in teaching, research, and student supervision.

My research focuses on industrial and systems engineering and data-driven decision analytics. It combines multi-criteria decision-making, agent-based modeling, simulation, optimization, and machine learning to examine complex decisions involving uncertainty, competing objectives, and multiple stakeholders. Applications include manufacturing, energy systems, sustainability, and organizational decision-making.

My published research includes assessments of hybrid energy policies, Industry 4.0 readiness, and sustainable cement production. I am also a coauthor of the peer-reviewed CoMSES computational model “Integrating Reinforcement Learning in Agent-Based Modeling for Dynamic Investment Decisions.” The associated 2026 journal article combines reinforcement learning, response surface methodology, and neural networks within an agent-based modeling framework. This work uses NetLogo simulations to investigate adaptive investment decisions under uncertainty.

My ongoing research and student supervision explore multi-agent reinforcement learning, large language models, and agent-based modeling for supply-chain decision support under disruptions. These activities extend my interests in adaptive decision-making and the analysis of complex industrial systems.

Alongside research, I teach undergraduate and graduate courses, supervise postgraduate research and undergraduate projects, and review manuscripts for scholarly journals. I welcome academic and industry research collaborations involving computational modeling, simulation experiments, decision-support systems, and sustainable industrial operations.