Chakrabartty works to make AI more energy efficient
Shantanu Chakrabartty, at the McKelvey School of Engineering, will lead a project funded by a three-year $1.1 million grant from the National Science Foundation to make artificial intelligence systems more energy-efficient.
Oyen and team receive funding to study placental function
An award from Wellcome Leap will support Michelle Oyen’s study of fetal growth restriction during gestational development. The program aims to reduce stillbirth rates by half.
WashU researchers observe cancer-like nucleoli in healthy cells
A discovery in the lab of Amit Pathak at the McKelvey School of Engineering connects mechanobiology to nuclear condensates in healthy cells.
Machine learning generates 3D model from 2D pictures
Researchers at the McKelvey School of Engineering have developed a new model that can accurately create a continuous 3D model from a set of 2D images without being trained on previous images.
Kamilov awarded second Scialog grant
Ulugbek Kamilov at the McKelvey School of Engineering has twice been awarded a grant for cutting-edge imaging research.
Sugarcane fires associated with mortality rates in South Florida
Research from a multi-institutional team, including Randall Martin at the McKelvey School of Engineering, estimated sugarcane fires in South Florida produce harmful emissions in quantities on par with vehicles — and play a role in the region’s mortality rates.
He is turning waste into commodity with DOE grant
Zhen (Jason) He is leading a multi-institution team developing a scalable upgrade to current wastewater systems with a $2.3 million federal grant.
Personalized prediction of depression treatment outcomes with wearables
Using Fitbits and a novel machine learning model, a multi-institutional team led by Washington University’s Chenyang Lu is ushering in the next step in personalization for treatment of depression.
How do cells take out the trash?
New research led by Kiersten Ruff, a senior research scientist in the lab of Rohit Pappu at the McKelvey School of Engineering, has uncovered the rules that govern how unfolded proteins are identified — and found that exceptions to the rules may play a role in dysfunctional cells.
Evaluation of AI for medical imaging: A key requirement for clinical translation
To develop guidelines to evaluate artificial intelligence (AI) in nuclear-medicine imaging, an interdisciplinary team established by Richard L. Wahl, MD, director of Mallinckrodt Institute of Radiology (MIR) and led by Abhinav Jha, assistant professor at the McKelvey School of Engineering, published Recommendations for Evaluation of AI for Nuclear Medicine in the Journal of Nuclear Medicine.
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