Tag Archives: machine learning

Algorithm & Blues: Machine-aided personnel decisions aim for fairness, risk side effects

By | December 3, 2020

When it comes to making human resources decisions, can humans be fair? What about relying on algorithms to make decisions instead? The answer to the first question is not always, which leads some business leaders to pursue the second. Yet, it turns out decisions made by machines are perceived as even less fair than those made by humans.… Read More »

Using machine learning to study wildlife refuge wetlands habitats

A U-M School for Environment and Sustainability (SEAS) student team is working with the Shiawassee National Wildlife Refuge to study how fish move through different wetland habitats. Their work is primarily dependent on being in the field, but in March the pandemic delayed fieldwork. In June, the team of SEAS master students was allowed to begin socially distant… Read More »

CoE researcher uses machine learning to improve brain imaging

By | September 2, 2020

Melissa Haskell, an ECE postdoctoral researcher, was awarded the Ruth L. Kirschstein Postdoctoral Individual National Research Service Award from the National Institutes of Health for her work using machine learning to improve functional magnetic resonance imaging (fMRI). Many factors, including movement, can affect the quality of an fMRI, which is used to measure and study brain activity. Haskell works to… Read More »

Student’s COVID-19 data model reaches CDC

By | August 31, 2020

U-M senior Sabrina Corsetti‘s efforts to model the pandemic’s spread using a machine learning algorithm has now been included in those being aggregated for the CDC’s weekly projections. Corsetti had her previous research halted when U-M suspended in-person classes and labs back in March. Thomas Schwarz, one of Corsetti’s research professors, happened to be modeling the pandemic’s data… Read More »

Enabling fairer data clusters for machine learning

By | August 20, 2020

Research published recently by CSE investigators can make training machine learning (ML) models fairer and faster. With a tool called AlloX, Mosharaf Chowdhury and a team from Stony Brook University developed a new way to fairly schedule high volumes of ML jobs in data centers that make use of multiple different types of computing hardware, like CPUs, GPUs,… Read More »

Faster than COVID-19: computer model predicts disease’s next move

By | May 15, 2020

M-CURES, a computational model now in development, could help hospitals anticipate fast-changing patient needs while keeping care providers safe. Developed by a team of researchers at the College of Engineering, Precision Health, and Michigan Medicine, the model uses a machine learning algorithm to crunch more than 200 health and demographic variables of individual COVID-19 patients. The model then… Read More »

Using machine learning to detect disease before symptoms manifest

By | March 27, 2020

Alfred Hero, professor of electrical engineering and computer science, has been working on predicting health and disease of people exposed to infectious viral pathogens since early 2007. His research uses machine learning to help discover genes in whole blood that can be used to detect early signs of acute respiratory viral infection (ARVI), as well as improve the… Read More »

Could this new technology finally end the battle over the thermostat?

By | October 24, 2019

UM-Dearborn Assistant Professor of Computer and Information Science Mohamed Abouelenien is exploring whether machine learning can help create a customized, responsive climate control system that would automatically detect a person’s level of “thermal comfort” and then make continuous adjustments to their environment. Abouelenien and his collaborator, UM-Flint Associate Professor of Mechanical Engineering Mihai Burzo, used a thermal camera… Read More »