From introducing reusable takeout containers to Cornell’s dining facilities to reducing laboratory dependence on fossil fuels, the President’s Awards for Employee Excellence celebrated these and other achievements Nov. 19 in Barton Hall.
The 2024-2025 Cornell Center for Social Sciences (CCSS) faculty fellows represent seven Cornell schools and colleges. Fellows will tackle urgent social issues such as online misinformation, pay transparency laws and the impact of government support on clean energy innovation.
On November 1st, Cornell's Center for Advanced Computing and Weill Cornell Medicine Scientific Computing, ITS, and Clinical and Translational Science Center will launch a new Scientific Computing Training Series.
Social media companies need content moderation systems to keep users safe and prevent the spread of misinformation, but these systems are often based on Western norms, and unfairly penalize users in the Global South, according to new research at Cornell.
Cornell researchers have developed a robot called ReMotion that occupies physical space on a remote user’s behalf, automatically mirroring the user’s movements in real time and conveying key body language that is lost in standard virtual environments.
Ph.D. candidates Yurong You and Kim Hochstedler tied for first place in the eighth Cornell Three Minute Thesis (3MT) competition. 3MT challenges graduate students to present their thesis research compellingly to general audiences in just three minutes.
Owolabi Legunsen, assistant professor of computer science, is developing new methods for testing and validating code, with the goal of finding and removing costly bugs.
From realtime visualization in video games to realtime urban monitoring, advances in computer, communication, and media technologies offer exciting new possibilities while raising urgent questions for architecture, planning, and digital studies. The second Preston Thomas Memorial Symposium at Cornell AAP this spring invites artists, designers, and scholars to explore them.
Researchers have built a new, interpretable machine-learning framework that captures stock- and industry-specific information and predicts financial returns with greater accuracy than traditional models.