Reidentifying faces from genomic data more difficult than previously thought
Despite others’ previous claims, the lab of Yevgeniy Vorobeychik and collaborators have determined it’s not so easy for a neural network to recreate a person’s face from DNA.
Krawczynski wins grant from Smithsonian Astrophysical Observatory
Henric Krawczynski in Arts & Sciences received a $41,255 award from the Smithsonian Astrophysical Observatory for quasar research.
Less energy, better quality PAM images with machine learning
A team of researchers led by Song Hu at the McKelvey School of Engineering has developed a two-step denoising technique for photoacoustic microscopy, a method that allows researchers to see tiny vessels in the body.
It’s complicated: Social media and well-being during COVID-19
Research from the lab of Renee J. Thompson in Arts & Sciences shows social media use associated with mixed outcomes when it comes to well-being during the pandemic.
Ryan receives fellowship from NIH
Jeremy Ryan, a graduate student working with Meredith Jackrel in the Department of Chemistry in Arts & Sciences, won a three-year $123,090 fellowship from the National Institutes of Health (NIH).
Student featured on BBC climate special
Dakotah Jennifer, a senior majoring in English in Arts & Sciences, and a Danforth Scholar, was featured on the BBC’s “Global Climate Debate” news special, featuring leaders gathered in Glasgow, Scotland, for the United Nations’ recent COP26 climate change meeting.
Persistent, distressing psychotic-like experiences associated with impairment in youth
Research from the lab of Deanna Barch shows that youth who indicate they have persistent, distressing psychotic-like episodes show impairment in a variety of areas.
Krawczynski receives NSF grant
Michael J. Krawczynski in Arts & Sciences received a three-year $178,445 grant from the National Science Foundation for a collaborative petrology and geochemistry research project.
Early warning system model predicts cancer patients’ deterioration
A multidisciplinary team of researchers at Washington University is developing a machine-learning-based early warning system to predict cancer patients’ deterioration and improve patient outcomes.
Synthetic biology yields easy-to-use underwater adhesives
The lab of Fuzhong Zhang at the McKelvey School of Engineering has used synthetic biology to bring together the best of spider silk and mussel foot protein in a biocompatible adhesive.
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