About

Moira Zellner is a Professor of Public Policy and Urban Affairs at Northeastern University College of Engineering, where she is also an affiliated faculty member of the Civil and Environmental Engineering Center. Her academic background lies at the intersection of Urban and Regional Planning, Environmental Science, and Complexity. She has served as Principal Investigator and Co-Investigator in interdisciplinary projects examining how specific policy, technological, and behavioral factors influence the emergence and impacts of complex socio-ecological systems problems, where interaction effects make responsibilities, burdens, and future pathways unclear. Her research also examines how participatory complex systems modeling with stakeholders and decision-makers can support collaborative policy exploration, social learning, and system-wide transformation. Moira has taught a variety of workshops on complexity-based modeling of socio-ecological systems for training scientists and decision-makers in the US and abroad. She has served the academic community as a reviewer of journals and grants and as a member of various scientific organizations. Before joining Northeastern, she was an Associate Professor at the University of Illinois at Chicago, where she headed the Urban Data Visualization Lab. Her professional experience includes working as an environmental consultant for local and international environmental engineering firms and for the undersecretary of Environment in the City of Buenos Aires, Argentina.

Research topics

• Computer Science
• Engineering
• Political Science
• Psychology
• Management science
• Geography
• Business
• Artificial Intelligence
• Process management
• Environmental science
• Data science
• Social psychology
• Ecology
• Epistemology
• Agroforestry
• Management
• Geology
• Environmental planning
• Forestry
• Knowledge management
• Agricultural engineering

Selected publications

• Envisioning sustainable urban areas through integrative physical systems and governance frameworks

  Environmental Research Infrastructure and Sustainability · 2026-04-23

  articleOpen access

  Abstract Cities and urban areas present important opportunities for advancing toward sustainability and resilience goals. From a systems perspective, various targets and indicators of key outcomes reflect sustainability of urban areas, motivating consideration of local and regional context. We explore four key themes for creating sustainable urban areas: (1) urban areas are complex systems linked with diverse rural areas across the urban-rural gradient, (2) data and modeling of physical and non-physical systems can aid decision making for sustainability, (3) creating sustainable urban-rural systems requires collaboration with partner communities, and (4) change requires adaptive and transformative governance frameworks. These themes guide sustainability innovations through co-production of knowledge among communities, authorities, managers, and researchers. The sustainability of urban areas strongly depends on urban-rural connectivity regarding both physical systems and governance frameworks.

  PublisherDOI

• Enhancing digital twin technology with community-led, science-driven participatory modeling: A case in green infrastructure planning

  Environment and Planning B Urban Analytics and City Science · 2025-02-19 · 3 citations

  articleOpen access1st authorCorresponding

  Recent research, professional, and funding agendas have re-surfaced the importance of knowledge co-production and ethical participation to address urban tensions worldwide: urbanization and rapid climate change, disproportionately impacting socially vulnerable populations. Despite the rise of Digital Twins (DT), buoyed by the growth of computational and data technologies in the past 10 to 15 years, DT have fallen short of their promise to address these tensions. We present a participatory modeling (PM) platform, Fora.ai, to build on existing strengths of DT and overcome the most prevalent limitations of data-driven technologies. This platform (i.e., a set of visualization and simulation tools and facilitation and sense-making approaches) is organized around the iterative steps in PM: problem definition and goal setting, preference elicitation, collaborative scenario-building, simulation, tradeoff deliberation, and solution-building. We demonstrate the platform’s effectiveness when set within a stakeholder-led process that integrates diverse knowledge, data sources, and values in pursuit of equitable green infrastructure (GI) planning to address flooding. The immediate visualization of simulated impacts, followed by reflection on causal and spatial relationships and tradeoffs across diverse priorities, enhanced participants’ collective understanding of how GI interacts with the built environment and physical conditions to inform their intervention scenarios. The facilitated use of Fora.ai enabled a collaborative socio-technical sense-making process, whereby participants transitioned from untested beliefs to designs that were specifically tailored to the problem in the study area and the diversity of values represented, attending to both localized flooding and neighborhood-level impacts. They also derived generalizable design principles that could be applied elsewhere. We show how the combination of specific facilitation practices and platform features leverage the power of data, computational modeling, and social complexity to contribute to collaborative learning and creative and equitable solution-building for urban sustainability and climate resilience.

  PublisherDOI

• Improving the Integration of Diversity, Equity, Inclusion, and Justice Goals in Total Maximum Daily Load Model Implementation for Water Quality Management

  Journal of Environmental Engineering · 2025-10-31

  article

  Water quality modeling is used globally to assess surface water impairment and manage watershed pollution in formal programs like the United States’ (US) total maximum daily load and in less structured initiatives elsewhere. Despite these programs, progress toward realizing equitable water quality benefits to society is stymied through an inability to recognize, plan, and incorporate diversity, equity, inclusion, and justice (DEIJ) principles in the modeling efforts. In this paper, we describe the major barriers and limitations to the inclusion of DEIJ principles in the design and implementation of pollution load reduction programs in the US. We offer a blueprint to embrace participatory modeling approaches to engage more openly, honestly, and fairly with relevant participants (stakeholders) to achieve just and equitable water quality outcomes and upgrade water quality management principles nationwide. We provide case studies where the DEIJ principles have been applied and synthesized, showing how participatory modeling can enhance water quality management in more inclusive ways, providing specific pathways to support such a transformation in diverse communities.

  PublisherDOI

• CoMSES Digest: Summer 2025

  Zenodo (CERN European Organization for Nuclear Research) · 2025-06-15

  articleOpen access

  Volume 13, No. 2

  PublisherDOI

• Identifying leverage points for sustainable transitions in urban – rural systems: Application of graph theory to participatory causal loop diagramming

  Environmental Science & Policy · 2025-01-15 · 9 citations

  article
  PublisherDOI

• Participatory modeling for collaborative landscape and environmental planning: From potential to realization

  Landscape and Urban Planning · 2024-03-26 · 26 citations

  articleOpen access1st authorCorresponding

  Participatory modeling is a collaborative approach to formalize shared representations of a problem and, through the joint modeling process, design, and test solutions. This approach is particularly well-suited to address complex socio-environmental problems like climate change and its implications on equitable and sustainable resource management and landscape planning. Despite its potential to inform landscape and environmental planning and policy, participatory modeling has yet to become a mainstream practice in our field. The reasons are several. First, it is hard to standardize the approach, as it must be heavily tailored to the characteristics and context of each planning problem, including the stakeholders engaged in the process. It is also onerous, requiring long-term commitment and a broad range of skills that can only be attained through extensive training and collaboration. These and other barriers are currently being addressed with a resurgence of knowledge co-production and ethical participation in scholarship, in practice, and in funding agendas. While most of the participatory modeling scholarship has focused on modeling tools and engagement techniques, multiple other dimensions must be recognized and articulated for impactful planning support. Grounding this perspective on a more fully integrated picture of participatory modeling, I identify some of these gaps and suggest an interdisciplinary research agenda to further evolve and scale up this practice for landscape and environmental planning and policy. The agenda highlights aspects of interface design and model biases, value elicitation and inclusion, management of diversity and innovation through facilitation, and the potential of novel computer-assisted assessment methodologies.

  PublisherDOI

• Advances in Total Maximum Daily Load Implementation Planning by Modeling Best Management Practices and Green Infrastructures

  Journal of Environmental Engineering · 2024-04-26 · 12 citations

  article

  In this paper, a review of advances in total maximum daily load (TMDL) implementation planning by modeling best management practices (BMPs) and green infrastructure (GI) practices along with enhanced (hybrid/streamlining) approaches is presented. The review emanates from Chapter 12 of the recent ASCE Manual of Practice on TMDLs. The latest models and modeling tools, specifically the United States Environmental Protection Agency’s (USEPA’s) GI Modeling Toolkit and the Landscape and Green Infrastructure Design (L-GrlD) model for formulating GI strategies with flexibility to support stakeholder engagement, are reviewed. In addition, other decision support tools that can help advance the state-of-the-practice of TMDL implementation are included in the synthesis. Advances in incorporating model uncertainties related to BMPs and GI practices in TMDL analysis are briefly discussed. Furthermore, enhanced approaches to cost-effective TMDL implementation measures are discussed, which can be combined with other watershed management strategies for greater synergy between TMDL modelers and other watershed stakeholders. Some emerging technologies such as remote sensing can be useful for monitoring the effectiveness of the TMDL implementation measures over time. Several emerging technologies are discussed through an example illustrating the long-term efficacy of implementation practices. Finally, an enhanced approach to the full TMDL life cycle that explicitly incorporates BMPs and GI practices in the TMDL is proposed, and expected benefits of this approach are demonstrated with conceptual diagrams.

  PublisherDOI

• Explaining woody invasions in riparian systems with agent-based simulations: Implications for conservation management

  Forest Ecology and Management · 2024-11-22 · 1 citations

  article
  PublisherDOI

• Decentralizing infrastructure: expanding architectural practice towards equity and health

  2024-01-01

  articleOpen access

  Climate change impacts are not evenly distributed across the globe. Inequities also emerge at a local scale where buildings have the most perceivable impact, affecting anything from access and continuity of the public realm to microclimates.Design decisions can exacerbate or mitigate microspatial inequities—i.e. significant local variation in environmentalhazard exposures, like heat, air pollution, and flooding. Green Infrastructure (GI) is a range of nature-based solutionswith the potential to mitigate environmental hazards. Decentralizing GI is critical to health and resilience, buildingredundancy and capacity through a distributed network of smaller system nodes that are less prone to cascading failures.Architecture projects can support decentralization, targeted mitigation, and incremental implementation; however theircontribution to urban resilience, health, and environmental justice needs to be better characterized to support rationalizedexpansion of such approaches. This requires ways to explore complex and dynamic interactions of buildings within and beyond site boundaries, including: (1) methods for measuring local variation in hazards at relevant spatial scales and (2) tools for modeling the impacts of interventions in inclusive conversations with local stakeholders. This research examines an equity-focused approach to co-designing GI in architecture projects, using data and tools to inform and measure the impact of individual building projects and, eventually, networks of projects. In collaboration with the city of Chelsea, MA, our transdisciplinary team is studying sensor networks and a participatory modeling process to demonstrate how architecture projects can generate and leverage local knowledge about microspatial inequities and mitigation by GI to advance broader community health goals. Co-design activities around one pilot site reveal how decentralization becomes a significant paradigm shift—even among practitioners—eliciting ideas about maximizing capacity, connectivity, co-benefits, and shared responsibility. This paper examines the term decentralization in a multidisciplinary discourse, shares lessons from a specific context, and discusses implications to architectural practice.

  PublisherOA PDFDOI

• Viewpoints/Points of View: Building a Transdisciplinary Data Theatre Collaboration in Six Scenes

  Arts · 2024-02-18 · 1 citations

  articleOpen access

  Data now plays a central role in civic life and community practices. This has created a pressing need for new forms of translation and sense-making that can engage diverse publics. Research-based Theatre (RbT) has proven to be an effective approach to delivering qualitative data to community stakeholders. We extend this tradition by proposing “community-engaged data theatre”. This approach translates quantitative data into theatrical language to engage communities in deliberative conversations on relevant issues. Community-engaged data theatre requires bridging multiple disciplines and involves creating new definitions and shared vocabularies in discourses that formerly have had little overlap in meaning. In this article, we share key insights from our initial experiments in which we adapted quantitative and qualitative data to devise a pilot piece in collaboration with a local community partner. In this essay, we communicate our collaborative process in polyvocal, artistic form. We edit and adapt materials from our conversations and creative practices into scenes illustrating how we taught and learned from each other about data science, participatory modeling, material deliberation and Composition to pilot our lab’s first community-engaged data theatre prototype.

  PublisherOA PDFDOI

Recent grants

• CI-TEAM Demonstration Project: Enhancing Stakeholder Participation in Environmental Planning with Visualization Tools that Support Complex Systems Learning and Spatial Thinking

  NSF · $266k · 2011–2016

Frequent coauthors

• Saurav Kumar

  Indian Institute of Technology Guwahati

  27 shared

• Ebrahim Ahmadisharaf

  27 shared

• Deva K. Borah

  Chesapeake Public Schools

  26 shared

• Craig Lott

  Virginia Department of Environmental Quality

  26 shared

• Navaratnam Leelaruban

  26 shared

• Nigel W.T. Quinn

  Arizona State University

  26 shared

• Meghna Babbar‐Sebens

  Oregon State University

  26 shared

• Harry Zhang

  25 shared