10/20/2023
By Fanglin Che

Chemical Engineering Seminar on Thursday, Oct. 26 from 4 to 5 p.m. at Shah Hall 310

Title: Bridging Engineering Research with Decision Science

Prof. Weiwei Mo
Associate Professor, Department of Civil and Environmental Engineering
Sustainability Fellow, Sustainability Institute
Faculty Fellow, Carsey School of Public Policy
University of New Hampshire

Abstract: The disconnection between knowledge and actions is often referred to as the “loading dock” problem, where knowledge is transferred in one direction from researchers to stakeholders. Bridging engineering research with decision science can empower researchers to tap into the tremendous resource of the stakeholder knowledge base, allow the co-production of scientific knowledge and solutions, and enable the use of such knowledge and solutions in actual decision-making. This seminar talk will use two examples to illustrate how engineering research can be integrated with decision science to inform use-inspired solutions. In the first example, user preferences for decentralized water systems (i.e., household rainwater harvesting and greywater recycling systems) were collected and analyzed to inform place-based policies and incentives that promote adoption trajectories with the largest amounts of water, energy, and cost savings. The second example combines system dynamics modeling and role-play simulation to respond to the challenges of dam decision-making. This approach integrates knowledge from researchers and potential users and creates a safe space to bring them together to interact with one another, learn about dam systems and one another’s priorities, and foster innovations in problem-solving. The methods introduced in these two examples are transferable to other engineering disciplines, yet more can be borrowed from social sciences to allow researchers to effectively address the complex challenges that we are facing today.

Biography: Weiwei Mo’s research group conducts stakeholder-engaged, interdisciplinary research towards sustainable, resilient, and smart society. Working at the intersection of human, infrastructure, and natural systems, her group uses computational methods (e.g., system dynamics modeling, life cycle assessment, agent-based modeling, network analysis, machine learning) to capture the interactions within and across different types of physical and human systems and to predict their short- and long-term behaviors under perturbations. These are combined with social sciences methods (e.g., serious gaming, crowdsourcing, participatory modeling, interviews) to understand the processes and constraints of decision-making and coordination at different levels to strengthen the linkage between knowledge and actions. Dr. Mo has led several National Science Foundation (NSF)-funded projects including an NSF CAREER award, working on integrated planning of decentralized water and energy systems, crowdsourced drinking water quality monitoring, and sustainable in-space manufacturing.

For more information contact Fanglin_Che@uml.edu