Halpern elected to National Academy of Engineering

Joseph Halpern, the Joseph C. Ford Professor of Engineering, has been elected a member of the National Academy of Engineering.

Active Learning Initiative funds nine projects

Innovative projects to enhance undergraduate teaching and learning in nine departments have received funding administered by Cornell’s Active Learning Initiative.

People admit they trust news stories that contradict their views – for a price

Researchers at Cornell Tech found that people are far more likely to say they believe news stories that align with their own political views no matter what outlet they’re from. But when offered a cash bonus for accuracy, participants were more likely to trust the news stories that countered their views.

Study: AI may mask racial disparities in credit, lending

A method intended to evaluate racial disparities in lending decisions can yield very different results depending on tiny changes in how it guesses applicants’ races, according to a new Cornell-led study.

AI adjusts for gaps in citizen science data

Citizen science databases can be inconsistent, but Cornell researchers have developed a deep learning model that effectively corrects for location biases, leading to more reliable predictions.

Streaming chill vibes? Spotify data says the season is the reason

A study of 765 million downloads from streaming service Spotify reveals clear patterns in musical preferences based on geography, gender, time of day and other considerations.

Margaret Martonosi ’86 visits as A.D. White Professor-at-Large

Computer scientist Margaret Martonosi '86 will interact with students and faculty Jan. 22-26 as an Andrew Dickson White Professor-at-Large.

Predicting future combos, from rap songs to pharmaceuticals

Cornell researchers have developed an algorithm to predict which groups are likely to work together in the future based on their past partnerships.

Is seeing believing? Depends on photo quality, study says

On secondhand marketplaces like eBay, people trust online sellers who post their own high-quality photos of items for sale more than they trust those who use stock images or poor-quality photos, a Cornell Tech study has found.