Grand Challenges require new approaches.
WID sets its sights on the biggest challenges facing humanity.
Powerful new tools from data science and biology enable WID scientists, engineers, and mathematicians to seek fundamental discoveries and applications that will improve the quality of human life, fairness in society, and the health of the planet.

Our Grand Challenges, modeled after the White House's 2013 initiatives, are lofty aspirations that inspire us to push the limits of possiblity, unite us in common causes, and guide our approach to science for a better world.

Our Grand Challenges Based on WID's research strengths, our faculty and fellows have come together to address four Grand Challenges. Our Challenges are ambitious enough to inspire us, but practical enough for us to strive for truly impactful discoveries and applications. Keep the human brain healthy Learn more trending_flat Mitigate soil loss and climate change Learn more trending_flat Ensure equity in the impact of data science Learn more trending_flat Bring science to people and people to science Learn more trending_flat Explore the research groups rising to meet these challenges:

Virtual Environments Group See all WID labs 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. Continue Reading Wisconsin Institute for Discovery Schloss Visual Reasoning Lab See all WID labs 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. Continue Reading Wisconsin Institute for Discovery Ponto Lab See all WID labs Kevin Ponto (PI) Develop techniques to better the experience of virtual reality through new devices, interfaces, and techniques. Continue Reading Wisconsin Institute for Discovery Wright Research Group See all WID labs Stephen Wright (PI) Numerical optimization, especially problems involving real (as opposed to integer or discrete) variables. Includes theory, algorithms, implementation and application. Continue Reading Wisconsin Institute for Discovery Nowak Research Group See all WID labs 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. Continue Reading Wisconsin Institute for Discovery Rutherford Research Group See all WID labs Thomas Rutherford (PI) Interests include energy markets, Climate Policy, international trade, technical change and computational economics. Continue Reading Wisconsin Institute for Discovery Lessard Research Group See all WID labs Laurent Lessard (PI) Research lies at the intersection of optimization and control, two fields that play a vitally important role in cyber-physical systems (CPS) applications but that tend to have very different goals and tools. Continue Reading Wisconsin Institute for Discovery