Research at UCLA Statistics is organized into eight centers. The department also runs the Statistical Consulting Center which is a resource for researchers throughout UCLA. These are listed below:
The Lab for Statistics, Computing, Algorithms, Learning, and Economics (SCALE Lab), focuses on advancing conceptual and mathematical tools centered on data, inferences, and decisions. Its primary goal is to address a wide range of emerging challenges at the interface of AI and society.
The Trustworthy AI Lab at UCLA envisions AI 2.0 as being driven by trustworthiness, surpassing mere performance, and being built upon generative data, enhancing raw data. The lab develops data-centric tools, such as artificially generated tables, which enable privacy-preserving data sharing, with applications in digital marketing, finance, and healthcare sectors. On the theoretical front, the lab focuses on the emerging field of “Generative Data Science,” which elucidates the underlying principles behind generative AI.
Research in the Climate Statistics Lab sits at the nexus of climate science and statistics. We are interested in questions that span the weather-climate divide, shed light on the interactions between natural variability and human-caused climate change, and link to downstream human and biological impacts.
The Center for Environmental Statistics (CES) analyzes and models data sets describing traffic counts, trip generation, urban economics, seismicity, water supply, water quality, weather, wildfires, and air quality of locations mostly in Southern California. The emphasis will be on studying spatial and temporal variation in the various indicators, and in impact studies of future developments.
The Center for Social Statistics (CSS) aims to foster collaboration between statisticians and social scientists at UCLA. Building on the long history of the development of quantitative methodology at UCLA, the CSS aims to: (1) foster collaborative research between statistical and social scientists; and (2) substantially increase the quantitative sophistication of students in the social sciences. Current focus areas of research are: casual inference, the study of networked phenomena, and modern surveys and sampling designs. The CSS is in partnership with the California Center for Population Research (CCPR) to enhance population research with state-of-the art statistical methodology.
Various large-scale biological data have become available in the past ten years: the entire genome sequences of many species, gene expression profiles and transcription factor binding data under numerous experimental conditions, genotypes in large numbers of polymorphic loci, etc. The Center for Statistical Research in Computational Biology (CSRCB) develops statistical methods and computational algorithms to analyze these massive biological datasets and extract valuable information to enhance our understanding of the science. Within the center, the director Dr. Jingyi Jessica Li is leading a research group, the Junction of Statistics and Biology.
The Center for the Teaching of Statistics (CTS) provides a model for Statistics education in the Southern California region by integrating research in Statistics and Pedagogy with technological innovations. The mission of CTS is to develop resources to improve statistics and data science education at all levels, including K-12, two-year colleges, and, of course, at UCLA. We collaborate with UCLA’s Center X, the American Statistical Association, and local colleges and universities.
The Center for Vision, Cognition, Learning and Autonomy (VCLA) starts from Computer Vision and expands to other disciplines. Our objective is to pursue a unified framework for representation, learning, inference and reasoning, and to build intelligent computer systems for real world applications. Our projects span four directions:
- Vision: Image and video parsing, scene understanding, scheduling top-down/bottom-up processes, spatial-temporal-causal and-or graphs
- Cognition: Functionality, intuitive physics, intentionality, perceptual causality, theory-of-mind, and visual persuasion
- Learning: Information projection, stochastic grammars, and-or graph learning, and lifelong communicative learning
- Autonomy: Human robot collaboration, multi-agent task planning, situated dialogue, human value and moral norm
The Statistical Consulting Center (SCC) has the dual purpose of: 1) training graduate students in consulting work and real-life data analysis; and 2) providing free statistical consulting and data analysis services to the Campus and the Community. In addition, we offer electronic consulting, and a large number of mini-courses in various topics in statistics and statistical software.