The AI Institute for Food Systems or AIFS, aims to meet growing demands in food supply by increasing efficiencies using AI and bioinformatics spanning the entire system — from growing crops through consumption. This includes optimizing plant traits for yield, crop quality and disease resistance through advances in molecular breeding, in addition to minimizing resource consumption and waste through development of agriculture-specific AI applications, sensing platforms, and robotics.

Artificial Intelligence in Veterinary Medicine is an informal group of people with the common goal of promoting the use of artificial intelligence in veterinary medicine at UC Davis. They seek to spark interest in the novice and engage the expert. They strive to provide an environment for learning, networking, and sharing of ideas and knowledge and involve people of any background, training, and career stage.

The Center for Precision Medicine and Data Sciences convenes diverse research teams to tackle today's healthcare challenges in nutrition, data science, clinical care and more. Precision medicine focuses on targeted, personalized care using big data. The objective of precision medicine is to make diagnosis of disease or illness, treatment therapies, and prevention more personalized, proactive, predictive and precise.

The Biomedical Informatics program provides broad access to clinical and translational informatics tools, data resources, training, and expertise in supporting and expanding the capabilities of the research community for securely designing and analyzing clinical and integrative data-driven research. The program partners with emerging research initiatives to advance data-driven precision medicine, population health, and technology enabled medicine.

The Data Center of Excellence aims to support UC Davis Health’s goal to become a world leader in the use of data and analytics to achieve clinical, operational, research, and academic excellence. Their mission is to ensure delivery of the right data to the right people, at the right time, to the right place, and in the right format for computation, presentation and analysis.

Davis Data Science Club is one of the premier professional student organizations on campus for the 2022-2023 school year. Their mission is to foster a greater data science community by connecting students with industry professionals, researchers, and faculty members. They hold multiple events and project groups every quarter to help students build career and technical skills. They are open to all majors, years and experience level.

NCIBT develops optical imagining technologies and combine them with AI-deep learning platform to provide real-time guidance of decision-making during medical and surgical procedures. The center will support research and development, clinical application, and training and education of the new technologies and promote their adoption to improve the quality of interventional health care. 

DataLab fosters, promotes and facilitates data science to accelerate discovery at the frontiers of scientific, engineering and social disciplines.  DataLab partners with researchers across UC Davis to push the envelope both within and across disciplines to enable qualitatively novel, interdisciplinary research.  By combining techniques across domains, they problem solve to further both data science application and theory.

The UC Davis ML and AI Group of Computer Science Department creates algorithms of the future to address the challenges of today. They work on complementary research areas that integrate in a variety of projects. They offer division undergraduate and graduate classes in various ML/AI aspects.  

The institute promotes interdisciplinary collaborations among 35 faculty members from four departments: computer science, electrical and computer engineering, mathematics, and statistics. The UCD4IDS encourages innovative and robust research and provides education and mentoring for graduate students and postdocs in data science. Students and postdocs engaged in this project will be trained to be the next generation of interdisciplinary data scientists in diverse fields.