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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
Posts
Future Blog Post
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Blog Post number 4
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
Blog Post number 3
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Blog Post number 2
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Blog Post number 1
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This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.
portfolio
A Causal Graph Generator
translating text to graphs via LLMs
publications
Leveraging Large Language Models for Automated Causal Loop Diagram Generation: Enhancing System Dynamics Modeling through Curated Prompting Techniques
Published in SSRN Electronic Journal, 2024
I developed and tested a prompting strategies for translating dynamic hypotheses (text) into causal loop diagrams (CLDs) using large language models (LLMs). With curated prompting, LLMs can generate CLDs comparable in quality to expert-built ones—dramatically speeding up the modeling process and lowering the barrier for novice system dynamicists.
Recommended citation: Liu, N. G., keith, D. (2024). Leveraging Large Language Models for Automated Causal Loop Diagram Generation: Enhancing System Dynamics Modeling through Curated Prompting Techniques. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4906094
Link to Paper
A multi-dimensional index of evaluating systems thinking skills from textual data
Published in Systems Research and Behavioral Science, 2024
I developed a quantitative framework to assess systems thinking (ST) skills from text, addressing the challenge of evaluating ST’s multi-dimensional nature. Using student data, we built an integrated ST index combining statistical and optimization methods (PCA, DEA, bootstrapping). The model helps identify how factors like math background and international experience relate to ST skill development.
Recommended citation: Liu, N. G., Mahmoudi, H., Triantis, K., & Ghaffarzadegan, N. (2024). A multi‐dimensional index of evaluating systems thinking skills from textual data. Systems Research and Behavioral Science. https://doi.org/10.1002/sres.3033
Link to Paper
Workload Dynamics in Safety-Critical Monitoring Roles: Evidence from the Belgian Railway Network
Published in SSRN Electronic Journal, 2024
I developed a dynamic simulation model to understand how workload impacts mental fatigue in railway traffic controllers. Using real-world data from the Belgian railway system, the model identifies a “comfort zone” for workload and shows how fatigue builds up when operators are over- or underloaded. These insights can inform scheduling, policy, and safety planning in automated transportation environments.
Recommended citation: Liu, Ning-Yuan Georgia and Triantis, Konstantinos and Roets, Bart, Workload Dynamics in Safety-Critical Monitoring Roles: Evidence from the Belgian Railway Network. Available at SSRN: https://ssrn.com/abstract=4798034 or http://dx.doi.org/10.2139/ssrn.4798034
Link to Paper
The Relationships among Workload, Automation Reliance, and Human Errors in Safety-Critical Monitoring Roles
Published in Safety Science, 2024
Using real-world data from Railway Traffic Control Centers, I studied how workload and automation interact to impact human errors. We found that errors are minimized when tasks are either mostly manual or mostly automated—highlighting the risks of mid-level automation. This work offers actionable insights for managing safety in complex socio-technical systems.
Recommended citation: Liu, N. G., Triantis, K., & Roets, B. (2024). The Relationships among Workload, Automation Reliance, and Human Errors in Safety-Critical Monitoring Roles. Safety Science, 106775. https://doi.org/10.1016/j.ssci.2024.106775
Link to Paper
Measuring Similarity in Causal Graphs: A Framework for Semantic and Structural Analysis
Published in arXiv preprint arXiv:2503.11046, 2025
I evaluated existing NLP and graph kernel methods for comparing causal graphs—considering both structural differences and the meaning of variable names. Using AI-generated synthetic data, we simulated how different people might map the same system. Our findings highlight key trade-offs between structural and semantic metrics, paving the way for better tools to interpret both human- and AI-generated models.
Recommended citation: Liu, N. Y. G., Yang, F., & Jalali, M. S. (2025). Measuring Similarity in Causal Graphs: A Framework for Semantic and Structural Analysis. arXiv preprint arXiv:2503.11046
Link to Paper
talks
The Transformative Potential of Large Language Models for System Dynamics Modeling
Published:
I presented this paper in the 2024 international system dynamics conference! In this presentation In this paper, Iintroduce and test a method for automating the translation of dynamic hypotheses (text) into Casual Loop Diagrams using large language models (LLMs)
A Dynamic Model on Organizational Learning and Forgetting based on “Serious” Errors
Published:
I presented the third paper of my dissertation in the 2024 international system dynamics conference! In this presentation I introduce a dynamic model theorizing how organizations transition from a non-safety focus to a safety-focus following “serious” errors. Extending from the concept of the oscillation cycle of Organizational learning and forgetting, our model shows that time delay, organizational culture and safety threshold within an organization can have an lasting impact on safety outcomes in the organizations.
Evaluating Systems Thinking Skills from Textual Data and Generating Causal Loop Diagrams Using Large Language Models
Published:
I’m thrilled to announce that I’ve been invited as a guest speaker at the Research Colloquium hosted by the Purdue System Thinkers (PurSysT) Club
teaching
Facility Planning and Logistics
Undergraduate course, Virginia Tech, Department of Industrial and Systems Engineering, 2021
I was an instructor for the undergraduate course Facility Planning and Logistics. In this course, I taught theory, concepts, and methods for designing and analyzing facilities and material flow in manufacturing, storage, and distribution environments. Topic areas include material handling systems, facility layout, facility location, warehousing, distribution, logistics, and transportation