New study method shows rise in physician turnover

Using an innovative method for measuring doctor turnover, Weill Cornell Medicine researchers determined that between 2010 and 2018, the annual rate at which physicians left their practices increased by 43%, from 5.3% to 7.6% a year.

Inaugural 2023 Weill Institute Emerging Scholars Announced

Eight graduate students from across the U.S. to attend inaugural Weill Institute Emerging Scholars Symposium in Oct. 2023

Around Cornell

Bulky size frustrates radical molecules to boost chemical reactions

Cornell researchers attached large fragments to temperamental "radical" molecules, increasing their girth to insulate them from their hyperreactive partners  – a method that could help create improved derivatives of pharmaceutical compounds.

Bumblebee research sparks rapid industry change

A Cornell study that revealed commercial eastern common bumblebee hives pose a threat to their wild counterparts has led one major pollination company to quickly adapt the bumblebee hive boxes they ship to growers.

‘Making Camp’ explores camping’s ironies, rewards

In a new book, landscape architect Martin Hogue investigates the history and evolution of recreational camping through the lens of its most important and familiar components.

Music student helps expand Ethiopian nun’s musical legacy

Thomas Feng, a doctoral student in performance practice, is identifying and cataloging the piano music of the late Emahoy Tsege-Mariam Gebru, a composer with a cult following.

Unused renewable energy an option for powering NFT trade

Unused solar, wind and hydroelectric power in the U.S. could support the exponential growth of transactions involving non-fungible tokens, Cornell Engineering researchers have found.

Game-playing automaton acts like an ‘irrational’ human

When researchers limited the memories of automatons competing in a wildlife poaching game, the computer took the same kinds of decision-making shortcuts as actual humans playing the game.

Dashcam images reveal where police are deployed

Using a deep learning computer model and dashcam images from New York City rideshare drivers, Cornell Tech researchers were able to see which neighborhoods had the highest numbers of New York Police Department marked vehicles.