Hau Chan
University of Nebraska-Lincoln, NE·Computer Science
Communities must make shared choices about scarce resources. Planners decide where to build a road so underserved neighborhoods can reach a hospital.
- Fields
Computer Science
Engineering
Mathematics & Statistics
- Topics
artificial intelligence
collective decision-making
sequential decision-making
- Grants
- 2 known grants, through Aug 2027
What they work on
- Develop collective decision-making frameworks for the facility accessibility improvement problem that handle multiple facilities and community preferences, using accessibility models and algorithms from operations research and AI.
- Design scalable mechanisms grounded in game theory and mechanism design to account for strategic behavior of agents in facility access problems.
- Model facility access decisions under disruptions such as partially functional infrastructure, and elicit preferences through tabletop exercises with planners, emergency managers and community leaders.
- Develop fair multi-objective collective decision methods for a single time period, applied to problems such as allocating water for agricultural drought resilience.
- Build fair sequential decision approaches that trade off short- and long-term efficiency and fairness, and study strategic stakeholder information, for vaccine distribution and refueling station siting.
More about the research
Water managers decide how to divide water during a drought. Health agencies decide how to send vaccines day by day in a pandemic. These are problems of collective decision-making, where many people with different preferences are affected. Often the choices also unfold over time. Both of the lab's projects aim to build theory and algorithms from artificial intelligence (AI), economics and operations research. The goal is decisions that are efficient, fair and practical at large scale.
Why it matters
Fair, scalable decision tools could help transportation planners and emergency managers improve underserved communities' access to hospitals, schools and transit, even after disasters. The same methods could help agencies share water during droughts, place clean-vehicle refueling stations, and distribute vaccines and supplies during outbreaks. Their decisions could then balance efficiency with fairness.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Juba Ziani
Georgia Institute of Technology, GA·Computer Science·Early-career
Model how individual data providers shape the outcomes of machine learning systems through strategic choices about what data to share, combining tools from computer science and economics.
Grant Schoenebeck
University of Michigan, MI·Computer Science
Develop models of informed group decision making that combine agents' subjective and objective preferences, information and answers to questions, drawing on social choice theory and information elicitation.
Hadi Hosseini
Pennsylvania State University, PA·Computer Science·Early-career
Design matching and allocation algorithms that remain fair when participants' preferences are uncertain or noisy, rather than assuming preferences are reported exactly.
The school
University of Nebraska-Lincoln: 17 labs on PI Pages, $657M a year on research, 261 research doctorates a year.
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