The future of research is interdisciplinary. To address the biggest problems facing the world, researchers need to build connections across disciplines, cultivate skills that enable collaboration, and look to unconventional partnerships for new ideas. By convening experts at the intersections of disciplines, the Wisconsin Institute for Discovery creates an environment ripe for interdisciplinary experimentation.
WID’s research is focused in four areas that need interdisciplinary approaches to solve big problems. Explore WID’s expertise:
WID’s research strength is in its innovative collaborative environment, but each WID faculty member maintains a robust research program. Explore individual labs at WID:
Pimentel-Alarcón Research Group
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Solís-Lemus Research Group
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Claudia Solís-Lemus (PI)
My research involves the development of statistical models to answer biological questions.
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Wisconsin Institute for Discovery
Virtual Environments Group
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Karen Schloss (PI), Kevin Ponto (PI)
The Virtual Environments Group is a space and a place where scholars explore the connections among environment, technology, human action, experience, and visualization, with expertise in virtual and augmented reality.
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Wisconsin Institute for Discovery
Schloss Visual Reasoning Lab
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Karen Schloss (PI)
Investigating how observers make predictions about objects and entities based on their cognitive and emotional responses to perceptual information; focusing on how people’s associations with colors influence cognitive processing in aesthetic response, judgment and decision making, and interpretation of information visualizations.
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Ponto Lab
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Kevin Ponto (PI)
Develop techniques to better the experience of virtual reality through new devices, interfaces, and techniques.
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Wright Research Group
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Stephen Wright (PI)
Numerical optimization, especially problems involving real (as opposed to integer or discrete) variables. Includes theory, algorithms, implementation and application.
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Nowak Research Group
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Robert Nowak (PI)
The NRG focuses on signal processing, machine learning, optimization, and statistics. Areas of focus include sparsity and active learning, learning graphs and networks, and interactive machine learning with humans.
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Wisconsin Institute for Discovery