Applied Research

Artificial Intelligence meets the brain – using AI for deeper insight into brain health.

Our daily experience with the world is multimodal. We see things. We feel textures. We hear noises, smell odors and taste foods — all to shape our understanding of the world. But most data on the human brain is siloed and not connected. Our I-BRAIN Science Team has built a one-of-a-kind data and human brain tissue repository with multiple sources of data integrated into one system, to understand and develop new treatments for human disorders and improve clinical care.

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The WISDOM science team will use data from Chicago hospitals to develop artificial intelligence technologies that improve patient outcomes.

The extraordinary team of clinicians, informaticians and engineers from UIC, UIUC and Rush are starting with data from cancer patients from underserved populations — seeking patterns and insights that will change the state of the practice.

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The science and technology of building robust and trustworthy AI-based systems will be one of the greatest challenges of our time.

Machines that learn from large amounts of data can mimic human intelligence to a large degree but are inherently fragile. Our research areas include autonomous vehicles and drones, robots in manufacturing and assisted living, robotic surgery, and AI applications in finance that call for privacy, fairness and ease of use.

This science team’s ambitions are to build an innovation center dedicated to advanced technology in the U.S. manufacturing, construction and agriculture industries.

Application areas include automated construction vehicles, cooperative autonomy for manufacturing, digital autonomous agriculture, additive manufacturing, and supply chain logistics, to name a few.

This science team is creating a non-invasive, cost-effective way to examine community spread of COVID-19, by measuring the virus in human fecal matter in wastewater.

Such monitoring, known as wastewater-based epidemiology, should warn of emerging viral hotspots up to a week earlier than traditional tests, and give public health workers valuable time to mobilize.
The program, however, will be important for additional and future public health concerns.

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The construction industry is ripe for transformation: inefficient, unsafe, and unpredictable. But digital technologies are showing promise.

Construction problems expose new challenges for AI, and this science team will look at solutions including image-based 3D reconstruction of interiors, 3D pose estimation, and semi-structured text analysis. Further AI methodologies will provide solutions in finance, insurance, and transportation logistics.

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Today, system designers focus on functionality and performance requirements, often adding security as an afterthought and ignoring privacy altogether.

Many view such privacy concerns as secondary and accepted their violation as a necessary byproduct of security. This science team will combine techniques drawn from cryptography, machine learning, software engineering and trustworthy computing to obtain practical, usable and scalable systems that will provide consumers with the level of privacy that they desire.

This science team will drive research, education, and outreach for autonomous systems in agriculture.

The ultimate goal is to improve Illinois farmers’ productivity, sustainability and profitability. We will advance AI in three areas: (1) robots to collect data for under-canopy crops, utilizing weeding and spraying robots; (2) urban food garden robots; (3) plant manipulation in berry-nut orchards with low-cost mobile robots and soft manipulators.

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Chronic kidney disease (CKD) affects approximately 15% of the U.S. population and Medicare costs exceed $120 billion annually.

This science team will develop strategies to improve the health and wellness of CKD patients while realizing tremendous economic impact. Our vision is to optimize the healthcare experience and quality of life (QOL) of individuals with CKD. Technology plays a key role, specifically using VR to increase exercise adherence and nutrition knowledge, and using machine learning to optimize patient-centered fluid management.

Learn More About the Kidney Wellness Institute

The future is electric. Cities will transform, and we will simulate the best way for their transportation systems to make the transition to net-zero carbon emissions.

Using remote sensing and artificial intelligence, we will work to quantify highly detailed crop and soil characteristics in Illinois. The data will provide an invaluable resource to farmers, businesses and policymakers.

This team will create an augmented reality application for rapid assessment of concrete and asphalt bridge deck health. This application will utilize sensor measurements, ubiquitous computing and machine learning.

This team will build AI software that will help people remotely create and mix music together to enhance well-being.

This team will combine observations, numerical models and new machine-learning prediction methods to provide better 14-day to 6-month weather and climate forecasts.

This team will build a state-of-the-art acoustic generation space similar to those now available at only a few large companies. This resource will enable testing of new algorithms or audio devices, such as microphones or hearing aids, in a complex real-world environment, enabling smaller companies and researchers to make important advances in the field.

The mobility-on-demand lab will run policy experiments on ride-sharing platforms, such as Uber/Lyft/Via, to provide insights and recommendations to regulators and to the companies themselves. This research will focus on how to improve environmental, economic, and equity outcomes.

This team will build easy-to-use software that will identify and label misinformation on social media websites.

Using electronic health records, we will develop a tool for the detection of Type 2 Diabetes in people unaware of the condition and determine which treatments are most likely to be successful for individual patients.

This team aims to establish an international center of excellence for hearing research that will transform the field by using AI and big data to translate research into clinical solutions.

This team will develop non-destructive, drone-based monitoring approaches that will enable easier and more frequent structural assessments of bridges.