Jan Kwakkel
Professor at Technische Universiteit Delft
The Hague, South Holland, Netherlands
Summary
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Rockstar🎓
Top SchoolJan Kwakkel is a professor at TU Delft with 13 years of experience bridging systems engineering, policy analysis and decision science to manage deep uncertainty in long-term infrastructure planning. He combines academic rigor in scenario planning, robust decision making and system dynamics with hands-on software skills in Python, Java and modeling tools like Vensim and Matlab. His research on airport strategic planning and adaptive delta management is informed by practical contributions to open-source agent-based modeling—improving core Mesa components such as AgentSet for better performance and pickling. Jan’s background in philosophy and systems engineering gives him a rare ability to translate complex normative questions into tractable analytical models. He excels at turning exploratory modeling and analysis into actionable policy insights for governments and large infrastructure stakeholders.
13 years of coding experience
11 years of employment as a software developer
BA, Philosophy, BA, Philosophy at Leiden Universitynvtir., Systems Engineering, Policy Analysis and Management, ir., Systems Engineering, Policy Analysis and Management at Delft University of Technology
English
Stackoverflow
76reputation
779reached
2answers
1question
Github Skills (8)
agent-based-modeling10
python10
connections6
eclipse6
netlogo6
logging6
ipython6
ipython-parallel6
Programming languages (3)
Github contributions (5)
projectmesa/mesa
Dec 2023 - Apr 2025
Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:451 reviews, 231 PRs, 103 pushes in 1 year 3 months
Contributions summary:Jan primarily contributed to the development of core agent-based modeling components within the Mesa library. Their work involved refactoring and enhancing the `AgentSet` class, including implementing indexing, slicing, and various methods for agent manipulation. This included improvements to the efficiency of shuffling agents and refactoring model registration. The user also addressed pickling issues within the `AgentSet` implementation.
complex-systemsmodeling-agentspythonagent-basedagent
scalet98/EMAworkbench
Jul 2012 - Aug 2019
workbench for performing exploratory modeling and analysis
Contributions:1136 commits in 7 years 2 months
modelingexploratoryworkbench
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