The Statistics Online Computational Resource (SOCR) is an online platform including web-services and advanced methods in probability, statistics, and machine learning in the health sector. This team will develop an enhanced analysis and visualization toolbox with an emphasis on “Big Data” - very large datasets that are difficult to analyze and interpret in meaningful ways with basic probability and statistical methods.

As therapies for cancer become more available world-wide, there is a need to develop screening tools to diagnose potential patients overcoming geographical and economic limitations. This team will develop software-based tools to facilitate diagnosis and interpretation of cancer image data. To aid this work, the DIAG team is also developing a personalized education AI assistant by leveraging LLMs and open-source materials

To assess vehicle safety and ease of operation, the SIM team is designing a virtual driving simulator through open-source, simple hardware, and virtual roadway and scenario simulation. This team will also conduct experiments with users of software/hardware to validate ease of use and functional requirements.

This faculty research team uses core principles of animal locomotion to create advanced robot technologies by distilling their mathematical principles and using machine learning automation. Students will design and fabricate robots, write core software components, and run robot and animal experiments, all in support of this mission.

This Atombot project will build a controllable miniature swarm robot system, based on a prototype developed by the Z Lab, study the fundamental emergent behavior of many-robot systems, and explore mission-critical applications in homeland security.

The CLUES Project uses artificial intelligence methods to index both what was said and visually presented in class sessions. Through this innovation an unprecedented data set is being created that identifies the knowledge being transmitted in college courses and allows students the ability to search for specific moments in their class sessions.

The Heliophysics team is developing a data processing pipeline to detect planetary emissions during extreme space weather incidents in support of the NASA SunRISE mission. Additionally, the team is constructing and operating a ground-based radio antenna array, with overlapping frequency coverage to SunRISE. This term, the team will expand their ground-based radio interferometer both locally and in the Upper Peninsula.

Wireless sensor networks are needed for studying Earth’s climate and for real time monitoring of the spread of viruses or pathogens. The Mapleseed team aims to develop miniaturized robotic vehicles capable of carrying various sensors and automatically measuring certain atmospheric parameters and particle/virus concentrations in targeted spaces.

Researchers at the University of Michigan Transportation Research Institute (UMTRI) have been improving accident impact simulations by broadening the types of body sizes and shapes considered. Students will develop parametric human body models that are capable of testing wide ranges of body sizes, types, and shapes to help create better adaptive and personalized designs for human safety and mobility.

The Heliophysics team is designing a ground radio prototype and data analysis pipeline to detect radio bursts from extreme space weather in collaboration with NASA’s SunRISE mission, which will send up a space-based array composed of 6 small satellites to Earth orbit to image the lowest frequency radio bursts for the first time.

Wireless sensor networks (WSN) are needed for studying Earth’s climate and for real time monitoring of the spread of viruses or pathogens such as those related to Covid-19. The Mapleseed team aims to develop miniaturized robotic vehicles (e.g., microdrones, mini-airplanes, and rovers) capable of carrying various sensors and automatically measuring certain atmospheric parameters and particle/virus concentrations in targeted spaces.

The Statistics Online Computational Resource (SOCR) is an online platform including web-services and advanced methods in probability, statistics, and machine learning in the health sector. This team will develop an enhanced analysis and visualization toolbox with an emphasis on “Big Data” - very large datasets that are difficult to analyze and interpret in meaningful ways with basic probability and statistical methods.

As therapies for cancer become more available world-wide, there is a need to develop screening tools to diagnose potential patients overcoming geographical and economic limitations. This faculty research team will develop software-based tools to facilitate diagnosis and interpretation of cancer image data.

This Atombot project will build a controllable miniature swarm robot system, based on a prototype developed by the Z Lab, study the fundamental emergent behavior of many-robot systems, and explore mission-critical applications in homeland security.

This faculty research team uses core principles of animal locomotion to create advanced robot technologies by distilling their mathematical principles and using machine learning automation.

Researchers at the University of Michigan Transportation Research Institute (UMTRI) have been improving accident impact simulations by broadening the types of body sizes and shapes considered. Students will develop parametric human body models that are capable of testing wide ranges of body sizes, types, and shapes to help create better adaptive and personalized designs for human safety and mobility.

To assess vehicle safety and ease to operation, we will improve upon the design of a virtual driving simulator through open-source software, simple hardware, and virtual roadway and scenario simulation.

The CLUES Project uses artificial intelligence methods to index both what was said and visually presented in class sessions. Through this innovation an unprecedented data set is being created that identifies the knowledge being transmitted in college courses and allows students the ability to search for specific moments in their class sessions.

Wireless sensor networks (WSN) are needed for studying Earth’s climate and for real time monitoring of the spread of viruses or pathogens such as those related to Covid-19. The Mapleseed team aims to develop miniaturized robotic vehicles (e.g., microdrones, mini-airplanes, and rovers) capable of carrying various sensors and automatically measuring certain atmospheric parameters and particle/virus concentrations in targeted spaces.

To assess vehicle safety and ease to operation, we will improve upon the design of a virtual driving simulator through open-source software, simple hardware, and virtual roadway and scenario simulation.

Researchers at the University of Michigan Transportation Research Institute (UMTRI) have been improving accident impact simulations by broadening the types of body sizes and shapes considered. Students will develop parametric human body models that are capable of testing wide ranges of body sizes, types, and shapes to help create better adaptive and personalized designs for human safety and mobility.

The CLUES Project uses artificial intelligence methods to index both what was said and visually presented in class sessions. Through this innovation an unprecedented data set is being created that identifies the knowledge being transmitted in college courses and allows students the ability to search for specific moments in their class sessions. This technology will be made available to a wide range of educational institutions and industry.

The Heliophysics team is designing a ground radio prototype and data analysis pipeline to detect radio bursts from extreme space weather in collaboration with NASA’s SunRISE mission, which will send up a space-based array composed of 6 small satellites to Earth orbit to image the lowest frequency radio bursts for the first time.

This faculty research team uses core principles of animal locomotion to create advanced robot technologies by distilling their mathematical principles and using machine learning automation.

This faculty research team is designing a nanospacecraft and operating a space mission that will explore the feasibility of a novel propulsion technology – miniature electrodynamic tethers – as propellant-less propulsion to new classes of very small satellites known as picosats and femtosats. Students will create a spacecraft with an operational ED tether for the first experimental testing of propellantless operation in space.