Research in Statistical Science
The students and faculty in the Statistical Science program carry out world-class research in the foundations and applications of statistics and data science. Their work has been funded by a variety of federal agencies, including the National Science Foundation (NSF), the National Institutes of Health (NIH), the Nacional Oceanographic and Atmospheric Agency (NOAA), the National Aeronautics and Space Administration (NASA), the Department of Defense (DOD) and the Department of Energy (DOE). Most of these projects provide graduate student support in the form of Graduate Student Assistantships (GSRs).
The work carried out by our students and faculty is published in the top statistics journals. These are some examples of recent papers by our faculty (bold names) and students (red names). You can learn more about the work in which our faculty is involved by exploring their personal websites.
- Barata, R., Prado, R., & Sanso, B. (2021+) Fast inference for time varying quantiles via flexible dynamic models with application to the characterization of atmospheric rivers. The Annals of Applied Statistics (to appear).
- Parker, P.A., Holan, S.H., & Janicki, R. (2021+) Computationally Efficient Bayesian Unit-Level Models for Non-Gaussian Data Under Informative Sampling with Application to Estimation of Health Insurance Coverage. The Annals of Applied Statistics (to appear).
- Shuler, K., Verbanic, S., Chen. I.A., & Lee, J. (2021) A Bayesian Nonparametric Analysis for Zero Inflated Multivariate Count Data with Application to Microbiome Study. Journal of the Royal Statistical Society: Series C (Applied Statistics), 70 (4), 961-979.
- Richardson, R., Kottas, A., & Sanso, B. (2020) Spatiotemporal modelling using integro-difference equations with bivariate stable kernels. Journal of the Royal Statistical Society, Series B, 82, 1371-1392.
- Jia, Y., Kechagias, S., Livsey, J., Lund, R.B., & Pipiras, V. (2021) Latent Gaussian Count Time Series. Journal of the American Statistical Association, 1-28.
- Kunihama, T., Li, Z.R., Clark, S.J., & McCormick, T.H. (2020) Bayesian factor models for probabilistic cause of death assessment with verbal autopsies. The Annals of Applied Statistics, 14, 241-256.
- Pourmohamad, T., & Lee, H.K.H. (2020). The Statistical Filter Approach to Constrained Optimization. Technometrics, 62 (3), 303-312
- Cadonna, A., Kottas, A., & Prado, R. (2019) Bayesian spectral modeling for multiple time series. Journal of the American Statistical Association, 114, 1838-1853.
- Terenin, A., Dong, S., Draper, D. (2019) GPU-accelerated Gibbs sampling: a case study of the Horseshoe Probit model. Statistics and Computing, 29, 301-310.
Not surprisingly, faculty and students also regularly present their work at some of the top Statistics and Computer Science conferences in the world (the Joint Statistical Meetings, the ISBA World Meeting and the Conference on Neural Information Processing Systems) and academic departments across the world. We consider student participation in conferences and workshops an integral piece of their academic training and the faculty works to secure funding for their attendance.
UCSC's location next to Silicon Valley offers a number of research and employment opportunities to our students and faculty. Many of our faculty regularly consult and our students usually take summer internships in various Bay Area companies. Sometimes, work that starts as part of an internship becomes part of the student's dissertation, and students are often hired by the companies they intern for. You can learn more about some of these opportunities by reviewing our alumni page.
UCSC's location also facilitates interactions with other researchers from across the world. The Statistics Department hosts a weekly seminar series that brings in speakers from the across the world. The department also regularly hosts outside visitors from across the world for short and medium term stays. You can see upcoming seminars and events on the Department's webpage. Students are encouraged to interact with speakers and visitors and often serve as hosts for meals and other events. Finally, the our faculty regularly organizes conferences and events that bring visibility to the campus and the programs. For example, our faculty has been organizing a series of NSF/CBMS summer conferences over the last 10 years; you can see details for the most recent here.
Opportunities for Interdisciplinary Collaborations
The research carried out by our students and faculty is highly interdisciplinary. We collaborate with computer scientists, mathematicians, physicists, social scientists, ecologists, biologists and medical doctors to develop novel methodology that advances our ability to make decisions on the basis of data in the context high-impact, real-life applications. In addition, our faculty and students are also affiliated with a number of institutes and centers on campus:
- The Data, Discovery and Decisions (D3) Research Center, which provides a platform for collaboration between industry and academia in the emerging field of data science.
- The Center for Analytical Finance (CAFIN), a collaboration between faculty in the Economics and Statistics departments that aims at producing cutting edge research with practical applications in the area of finance and financial markets.
- The UC Santa Cruz TRIPODS project, which brings together researchers from mathematics, statistics, and computer science to develop a unified theory of data science applied to uncertain and heterogeneous graph and network data.
- The Center for Statistical Analysis in the Social Sciences (CSASS), whose mission is to facilitate the use and training of statistical, psychometric, and computational methods in social science research.
- Global and Community Health (GCH), within the UC Santa Cruz Institute for Social Transformation, whose mission is to develop research-based solutions to urgent problems in the world.
In addition, our faculty maintains a close relationship with various National Laboratories, Federal Agencies, and International Agencies, including Lawrence Livermore National Lab (LLNL), Los Alamos National Lab (LANL), Sandia National Lab (SNL), National Oceanic and Atmospheric Administration (NOAA), UN Inter-Agency Group for Child Mortality Estimation, and WHO Verbal Autopsy Reference Group.