Cornell Bowers CIS has been awarded a three-year, $300,000 grant from the Clare Boothe Luce Program for Women in STEM to increase the number of undergraduate women pursuing research in computer science.
As scientists continue to catalog genomic variations in everything from plants to people, today’s computers are struggling to provide the power needed to find the secrets hidden within mass amounts of genomic data.
Finding illuminates why mitigating strategies to curb disinformation haven’t worked, while also suggesting that the most effective strategy against fake news may begin with its users.
The Association for Computational Linguistics (ACL) awarded its 2021 Distinguished Service Award to Lillian Lee, the Charles Roy Davis Professor in the departments of computer science and information science in the Ann S. Bowers College of Computing and Information Science
A team of Cornell students has won a grant from NASA’s University Student Research Challenge for a proposed sensor that can help 3D printers build better, more reliable products. To collect the prize, the team is now crowdfunding a cost-share required by NASA.
Researchers at the Cornell University Center for Advanced Computing (CAC), Texas Tech University, and Indiana University are engaged in a $298,000 NSF-funded EAGER grant designed to optimize future cyberinfrastructure projects.
Ranjit Singh, Ph.D. ’20, and Steven Jackson, associate professor of information science in Cornell Bowers CIS, examined how India’s biometrics-based identification system, Aadhaar, works for the country’s nearly 1.4 billion people.
Cornell researchers in natural language processing have found that the word lists packaged and shared amongst researchers to measure for bias in online texts oftentimes carry words, or “seeds,” with baked-in biases and stereotypes, which could skew findings.
Using a Packard Fellowship for Science and Engineering from the David and Lucile Packard Foundation, Peter McMahon, assistant professor of applied and engineering physics, aims to harness the power of photonics to build processors for neural networks that are more than 1,000 times more energy efficient.
