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Muhammad Khurram Ali Member since: Sun, Jan 18, 2015 at 11:46 AM Full Member

PhD Industrial Engineering, University of Engineering and Technology, Taxila, Pakistan, MSc Industrial Engineering, University of Engineering and Technology, Taxila, Pakistan

I am an Associate Professor of Industrial Engineering with over two decades of experience in teaching, research, and supervision in data-driven decision making, operations research, and computational modeling. My research integrates Multi-Criteria Decision Analysis (MCDA), Agent-Based Modeling (ABM), and Reinforcement Learning (RL) to support strategic decision systems in sustainability, investment, and industrial operations. My recent work explores human-centric and multi-actor systems, leveraging simulation-based optimization and AI-driven analytics to enhance resilience, efficiency, and sustainability in complex socio-technical environments. I have published extensively in international journals, reviewed over 75 manuscripts, and am an active member of INFORMS and the System Dynamics Society. My long-term goal is to bridge industrial systems modeling with intelligent decision support, aligning academic research with real-world sustainability and innovation challenges.

🔹 Experience
Associate Professor — Industrial Engineering, University of Engineering and Technology, Taxila (2018 – Present)• Teach graduate and undergraduate courses in Operations Research, Data Mining, Advanced Statistics, System Simulation, and Soft Computing.• Conduct funded research in agent-based and reinforcement learning models for sustainable and data-driven decision systems.• Supervise doctoral students in decision analytics, multi-agent modeling, and MCDM applications.• Reviewer for international journals including Neural Computing and Applications, the Journal of Cleaner Production, Annals of Operations Research, Environment, Development and Sustainability, Energy for Sustainable Development, Scientific Reports, IEEE Access, Cleaner Energy Systems, Utilities Policy, and Sustainable Futures

🔹 Research Interests•
Data-Driven Decision Making• Agent-Based Modeling (ABM)• Reinforcement Learning (RL)• Multi-Criteria Decision Analysis (MCDA / MAMCA)• Sustainable Supply Chains• System Dynamics; Simulation• E-Health and Humanitarian Systems

🔹 Selected Achievements•
30+ peer-reviewed publications; ~360+ citations• Reviewer for 75+ international journal papers• Completed Coursera Specializations in Machine Learning, Deep Learning, and Reinforcement Learning• 20+ years of experience integrating data science with sustainability modeling

Data-Driven Decision Making | Agent-Based & Reinforcement Learning Models | Multi-Criteria Decision Analysis | Sustainable Systems | Operations Research | Netlogo | R

David Earnest Member since: Sat, Mar 13, 2010 at 03:46 PM Full Member

Ph.D. in political science (2004), M.A. in security policy studies (1994)

Two themes unite my research: a commitment to methodological creativity and innovation as expressed in my work with computational social sciences, and an interest in the political economy of “globalization,” particularly its implications for the ontological claims of international relations theory.

I have demonstrated how the methods of computational social sciences can model bargaining and social choice problems for which traditional game theory has found only indeterminate and multiple equilibria. My June 2008 article in International Studies Quarterly (“Coordination in Large Numbers,” vol. 52, no. 2) illustrates that, contrary to the expectation of collective action theory, large groups may enjoy informational advantages that allow players with incomplete information to solve difficult three-choice coordination games. I extend this analysis in my 2009 paper at the International Studies Association annual convention, in which I apply ideas from evolutionary game theory to model learning processes among players faced with coordination and commitment problems. Currently I am extending this research to include social network theory as a means of modeling explicitly the patterns of interaction in large-n (i.e. greater than two) player coordination and cooperation games. I argue in my paper at the 2009 American Political Science Association annual convention that computational social science—the synthesis of agent-based modeling, social network analysis and evolutionary game theory—empowers scholars to analyze a broad range of previously indeterminate bargaining problems. I also argue this synthesis gives researchers purchase on two of the central debates in international political economy scholarship. By modeling explicitly processes of preference formation, computational social science moves beyond the rational actor model and endogenizes the processes of learning that constructivists have identified as essential to understanding change in the international system. This focus on the micro foundations of international political economy in turn allows researchers to understand how social structural features emerge and constrain actor choices. Computational social science thus allows IPE to formalize and generalize our understandings of mutual constitution and systemic change, an observation that explains the paradoxical interest of constructivists like Ian Lustick and Matthew Hoffmann in the formal methods of computational social science. Currently I am writing a manuscript that develops these ideas and applies them to several challenges of globalization: developing institutions to manage common pool resources; reforming capital adequacy standards for banks; and understanding cascading failures in global networks.

While computational social science increasingly informs my research, I have also contributed to debates about the epistemological claims of computational social science. My chapter with James N. Rosenau in Complexity in World Politics (ed. by Neil E. Harrison, SUNY Press 2006) argues that agent-based modeling suffers from underdeveloped and hidden epistemological and ontological commitments. On a more light-hearted note, my article in PS: Political Science and Politics (“Clocks, Not Dartboards,” vol. 39, no. 3, July 2006) discusses problems with pseudo-random number generators and illustrates how they can surprise unsuspecting teachers and researchers.

Francesc Bellaubi Member since: Thu, Jun 27, 2013 at 03:40 PM

PhD candidate

performance of urban water service provision, high levels of inequities and inefficiency persist. In terms of water distribution and cost, these undesirable patterns have a high impact on peri-urban areas usually populated by marginalized and poor populations. The high levels of Non-Revenue Water (NRW), together with the existence of corrupt practices and mismanagement of water utilities, remain a highly controversial issue.

This situation confronts rent-seeking theory directly, explaining the performance-corruption relationship (Repetto, 1986). The presumption is that low performance in water supply service provision results from corruption because rent-seeking occurs. Hence, the implementation of performance-oriented reforms in the water supply sector, such as regulation or private sector participation, will reduce corruption, increasing the efficiency of water service provision. Nevertheless, latest evidence shows that “key elements of good political governance have a positive effect on the access to water services in developing countries. In turn, private sector participation has little influence other than increasing internal efficiency of water providers” (Krausse, 2009).

Indeed the relation between governance, corruption and performance seems to be more complex than theory wants to acknowledge. It must be reviewed further than a simple cause-effect relationship. It appears that poor management of water utilities, evidenced by high levels of NRW, justifies new investments. Such practices can be encouraged by an “opportunistic management”, whilst at the same time maintaining an influential “hydrocratic elite” in the sphere of water control.

The present research proposal aims to understand the relation between mismanagement and corruption of water control practices in water supply service provision. The research examines how this relationship affects the performance of water service provision and relates to water supply governance models at municipal peri-urban level in three African countries.

To understand the mismanagement-corruption relationship, we look at different case studies of water supply service provision in Senegal, Ghana and Kenya. Each case represents a different governance model in terms of management practices, institutional and organizational settings, and the actors in place, which affects the performance of water service provision in terms of allocative efficiency and access to water (equity). Whether regulation, decentralization and private sector participation constitute possible ways to reduce corruption is examined in the context of water sector reform.

In a second step, we propose a theoretical model based on Agent Based Modelling (ABM) (Pahl-Wostl, 2007) to reproduce complex social networks under a Socio-Ecological System (SES) framework approach. The model will allow us to test whether collaborative governance in the form of collective action in a participatory and negotiated decision-making process for water control, can reduce corruption and increase performance.

The present research benefits from the project “Transparency and Integrity in Service Delivery in Sub-Saharan Africa”. This project, carried out by Transparency International (TI) in 8 Sub-Saharan countries, aims to increase access to education, health and water by improving transparency and integrity in basic service delivery. The proposal retains focus on Senegal, Ghana and Kenya in the water sector.

Key words: water control, mismanagement, corruption, performance, collaborative governance, modelling, collective action, negotiation, participation

Displaying 3 of 53 results for "E Frances Cassirer" clear search

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