About the Conference
At every scale, in every domain, from intracellular molecular signaling pathways to global carbon emissions, we need to model complicated systems and their interactions.
Modeling is difficult work, but new technologies from artificial intelligence and data science promise to make it easier and more accurate. Managing systems also is challenging, though the challenges are political, economic and social rather than technical.
The University of Pittsburgh, through its newly formed School of Computing and Information, leads an initiative to enhance the technological and policy aspects of modeling and managing the world’s complicated, interacting systems.
This goal – rational analysis and management of complicated systems – is shared by unusually diverse stakeholders from government, industry, non-profits, foundations and academics. The meeting is therefore a convening of stakeholders, not an academic conference.
The meeting will recognize and mobilize a latent community of stakeholders, and organize a professional society and develop modes of communication, survey the state of the art in technologies for modeling and managing complicated systems, and discuss important applications.
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Modeling the World’s Systems (MWS20) is about the science, technology and applications of modeling and managing complicated, interacting systems, at all scales (from molecular to global processes) and in multiple domains. Challenges such as food insecurity, land use, managing patients with complex conditions, urban renewal and gentrification, and drug development for poorly understood conditions such as Alzheimer’s Disease all require models of complicated, interacting processes.
Building and maintaining models is human-intensive work. The premise of MWS is that many aspects of modeling that are today done exclusively by humans can be automated to some extent and improved by computing and information technology. Examples include machine reading to extract “causal nuggets” from papers, ontology alignment to facilitate integrating legacy models, machine learning of lightweight proxy models, theoretical work to unify modeling paradigms, workflow support and software stacks optimized for modeling, and so on.
MWS has three goals:
- Bring together modelers with diverse stakeholders in government, industry and non-profits around important use cases;
- Share new developments in the science and technology of modeling and model-based management of complicated, interacting systems;
- Share modeling resources and data to promote the development of modeling technology and model-based management.
The inaugural conference, MWS18, featured sessions on the opioid crisis, urban systems, social investing, global and national security, and the biology of ageing; as well as tutorials on modeling technologies.
MWS20 will feature refereed papers and posters in addition to invited sessions. Topics for papers and posters include:
- Technologies to accelerate and improve modeling;
- General theoretical and algorithmic results in modeling, ideally supported by empirical results;
- Mature and shareable modeling frameworks and data corpora, steps toward model and data commons, etc;
- High-impact use cases that demonstrate the practical value of modeling, lessons learned by modelers, novel modeling technologies, etc.;
- Meta-modeling issues such as model description languages, provenance, validation and replicability.
The primary review criterion is: “Does this paper/poster hasten the day when important policy and management decisions are informed by models?” MWS is interested in shareable modeling resources and technologies, not in small, simple examples or minor technological tweaks.
MWS will review papers and, with the author’s permission, distribute them in a technical report to attendees. Technical reports are not formal publications, so authors can publish their work elsewhere.
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