Research

Aditya Thakur Receives 2020 Facebook Probability and Programming Research Award

September 21, 2020

For the second year in a row, CS assistant professor Aditya Thakur is the winner of a Facebook Probability and Programming Research Award. The award, established in 2019, seek proposals from the worldwide computer science community that address problems at the intersection of machine learning, programming languages, statistics and software engineering. Thakur’s proposal was one of 19 selected.

Using AI to treat teenagers with schizophrenia

September 11, 2020
Computer science professor Ian Davidson will bring expertise in explainable artificial intelligence (XAI) and deep learning (DL) to a new National Institute of Health (NIH)-funded project to treat teenagers with schizophrenia. The five-year, $3.4 million project funds trials using AI to prescribe treatments for each patient based off medical images of their brains.

Solving credit card fraud

June 18, 2020

Computer science associate professor Sam King thinks he has a solution to credit card fraud. Using his experiences in Silicon Valley and his research at UC Davis, King has developed a new, secure app called Card Scan that uses machine learning to read credit cards in seconds and reject fraudulent cards, transactions and phones.

AI for Social Media Headline Editing

January 14, 2020

Any social media professional will tell you the headline is one of the most important parts of any post, because without an attention-grabbing title, readers are likely to scroll past your stories in favor of something else. Though large organizations have professional social media editors, smaller companies and individual content creators don’t have the money to compete with larger outlets.

CS Team Selected for Oral Presentation at the 2019 IEEE CVPR Conference

June 12, 2019
The paper, authored by Ph.D. student Krishna Kumar Singh, visiting researcher Utkarsh Ojha and assistant professor Yong Jae Lee, describes an algorithm the team developed that was able to identify, disentangle and layer different parts of generated images by associating random codes with different parts of the image.

Computer Scientists Create Programmable Self-Assembling DNA

March 20, 2019
Computer scientists at the University of California, Davis, and the California Institute of Technology have created DNA molecules that can self-assemble into patterns essentially by running their own program. The work is published March 21 in the journal Nature.