News: Research

New research done by Edwin Kite suggests that the idea of transforming the Red Planet might not be so far-fetched after all.
 

Wendy Freedman's research using the James Webb Space Telescope suggests that the Standard Model of the universe is holding up.

One of the world’s largest optical telescopes reaches a key milestone toward US federal construction support.

MD/PhD Candidate Steven Song and collaborators Spencer Ellis and Derek Reiman designed a machine learning model able to predict non-melanoma skin cancer under resource-limited settings.
 

New insights into the role of RNA in cancer took center stage at a recent symposium hosted at the University of Chicago.
 

The prairie restoration success at Fermilab has become a living laboratory — supporting scientific research, fostering biodiversity and providing essential ecosystem services like erosion control and enhanced soil health.

Team led by UChicago scientist Wendy Freedman using James Webb Space Telescope finds no evidence of tension in Hubble Constant.

Huanzhou Yang's research uses simulations to determine how telescopes could detect oxygen gas and ozone, revealing clouds could aid in the detection of biosignatures. 

Weather forecasts based on AI are faster and sometimes more accurate than traditional ones, but they may miss rare and unprecedented weather events. 

Rafael Luque's research receives widespread discussion after a reanalysis of the original data. 

UChicago analysis of new and old data suggests the signal is weak and explainable by other molecules.

The new device created by Prof. Bozhi Tian's lab to detect molecules in air samples could one day be used to diagnose a wide array of diseases.
 

Researchers in PME and Chemistry have developed a new computational tool that predicts which metal-organic frameworks will be most stable for a given need, such as catalyzing reactions to store and extract energy from chemical energy carriers without combustion.

The Data Science Institute’s annual event showcased cross-campus collaborations spanning climate science, government, and more.
 

A new study from scientists from the University of Chicago found that neural networks cannot forecast “gray swan” weather events, which might not appear in existing training data but could still happen—like 200-year floods or massive hurricanes.