Involvement with National Institutes
The Fall of 2002 marked the opening of the Mathematical Biosciences Institute (MBI) at OSU, which was funded by a $10 million, five-year grant from the National Science Foundation (NSF). The successful proposal was developed by a team of faculty including Peter March, David Terman (Mathematics), and Doug Wolfe, Dennis Pearl (Statistics). The MBI was set up to promote interactions between statistical, mathematical, biological, and medical sciences through research and educational activities. Many Statistics Department faculty members were involved in the work of the MBI from 2002 to 2021 as directors, researchers, and mentors (See Section IV for more information on the MBI.)
Department faculty members have been involved with the work of a range of other national and international institutes; for example:
(a) Various faculty have visited SAMSI, the NSF-funded Statistical and Applied Mathematical Sciences Institute. Cressie co-led the SAMSI Program on Space-Time Analysis in Environmental Mapping, Epidemiology, and Climate Change which was held in 2009-2010, and Berliner, Calder, and Cressie all participated in the program. Shili Lin was invited to spend a semester at SAMSI to co-lead their 2014-2015 program on Beyond Bioinformatics: Statistical and Mathematical Challenges. In addition, Berliner and Cressie participated in the program on Data Assimilation in Geophysical Systems (2004-2005), and Cressie and Santner participated in the program on Complex Networks (2010-2011).
(b) In 2000, the Statistics Department (including OSU faculty members Berliner, Cressie, Goel, Raghavan, and Santner) participated in activities of the National Institute of Statistical Sciences (NISS).
(c) Berliner was Geophysical Statistics Project Leader at the National Center for Atmospheric Research (NCAR), 1995-1997.
(d) The Intergovernmental Panel on Climate Change (IPCC) shared the Nobel Peace Prize with Al Gore, in 2007. Mark Berliner was an active contributor to the Nobel Prize winning efforts of the IPCC.
(e) In 2011, the Department was selected to be a node of the NSF-funded Research Network for Mathematical Sciences: Statistical Methods for Atmospheric and Ocean Sciences. Calder was Director of the local node.
(f) Oksana Chkrebtii became one of the core faculty members for a $26 million NSF-funded multi-institutional Engineering Research Center led by colleagues at the Department of Materials Science Engineering aimed at advancing the revolution in material design and manufacturing (the 2023 HAMMER project).
(g) A number of faculty members have been invited to spend time at international research institutes, including: theOberwolfach Research Institute for Mathematics, Germany (Dean, MacEachern), the Isaac Newton Institute for Mathematical Sciences, UK, (Dean, MacEachern, Santner), Institut National de Recherche Agronomique, Avignon, France (Cressie).
Translational Data Analytics Institute
In 2014, the Translational Data Analytics Institute (TDAI) was established at OSU as part of an OSU data analytics initiative. TDAI brings together faculty and students with industry and community partners to create interdisciplinary, data-intensive solutions to grand challenges. The Statistics Department has been very active in the TDAI with Yoon Lee, Shili Lin, Desheng Liu, and Subhadeep Paul serving on the Leadership Team at various times, and Dena Asta serving as a core faculty member. Many members of the department have served as affiliated faculty for TDAI (including Chkrebtii, Craigmile, Hans, Herbei, Kaizar, Kubatko, Kurtek, MacEachern, Paganin, Peruggia, Turkmen,Vu, Xu, and Zhu).
Conferment of University Awards and Honorary Degrees to Statistics Department Candidates
One measure of the growth of the influence of the Department within the Ohio State community is its success in having multiple candidates granted OSU honorary degrees. Since 1999, these hae been awarded to Sir Adrian Smith (then Deputy Chair of the UK Statistics Authority) in 2015, and Professor Grace Wahba (University of Wisconsin) in 2022.
In 2011, Professor Gary G. Koch, University of North Carolina (UNC) at Chapel Hill, was awarded the Professional Achievement Award from The Ohio State University Alumni Association.
Major Research Programs in the Department
For several years during 1999-2024, the Department led the entire College of Biological, Mathematical and Physical Sciences (BMAPS) in increased research support. Some grants were for interdisciplinary projects and others were for core statistical research. Details of grants won by faculty and staff are given in the newsletters and the Department website. A sample of grant-supported research is highlighted here.
Spatial and Environmental Statistics: The Spatial Statistics & Environmental Statistics (SSES) program was established in 1999 with Noel Cressie as Director. The program held grants from the Environmental Protection Agency, the Office of Naval Research, NASA, and the American Chemistry Council. Interdisciplinary seminars were held including speakers from environmental science and engineering, the Byrd Polar research center, chemistry and many others. In 2014, Peter Craigmile became the SSES program director until 2015, when the formal SSES program was wound up. Spatio-temporal environmental statistics continues to be an important part of the department.
A large amount of research related to environmental issues was accomplished during 1999-2024, including (a) work with Ohio State’s Byrd Polar Research Center and Department of Geological Sciences, on a physical statistical approach to the dynamics of ice streams funded in 2002 by the National Science Foundation (Berliner, Cressie), (b) a project, labelled “Sources to Biomarkers’’ (STB) to develop a hierarchical Bayesian modeling framework for analyzing pathways of exposure to toxic substances, funded in 2004 by the American Chemistry Council (Calder, Craigmile, Cressie, Santner, jointly with Battelle), (c) a land-use land-change study funded in 2006 by NASA (Calder and Shi, joint with Geography), (d) hierarchical statistical analysis of very large remote sensing data funded in 2008 and 2009 by NASA’s Jet Propulsion Laboratory (Cressie), (v) space-time models involving stochastic differential equations funded by NSF in 2014 (Craigmile, Herbei), (e) the analysis of large spatiotemporal datasets with application to quantitative models of human dynamics, funded in 2018 by NSF and the National Geospatial Intelligence Agency (Paul), (f) the study of dynamics of surface salinity in the ocean at resolutions finer than those of satellite observations, and its relationship to precipitation, funded in 2019 by NASA (Chkrebtii).
Bayesian Methodology: Methodological research in Bayesian parametric, semiparametric, and nonparametric methods, supported by NSF and NSA grants, has been undertaken by various faculty members in the last 25 years; for example: development of innovative Bayesian semiparametric methods for efficient and robust causal inference in the presence of effect heterogeneity in large observational datasets (Xu, MacEachern, Lu); improvement of data-driven modelling and decision-making in low-information settings (MacEachern, Lee, Xu, and collaborators); use of Bayesian methods for models that are only partially specified, as are many economic models (Peruggia, MacEachern, Forbes); dynamic visualization of varying prior and posterior in Bayesian analysis (Doss).
Funded by numerous grants from NASA, the Office of Naval Research, and NSF from 2003 to 2023, Berliner developed Bayesian physical-statistical modeling to combine scientific models and observations in complex settings. Applications included applications were in climate, climate change, glaciology, oceanography, Bayesian diffusion models, paleo-climate, sea surface and surface winds prediction.
Statistical and Machine Learning: One of the more recently identified areas of research in the Department is that of Statistical Learning. This research has been well-supported by the NSF. For example grants were awarded to: Tao Shi in 2013 for studying scalable spectral methods for statistical analysis; Yoonkyung Lee in 2015 for nonlinear dimension-reduction methods; Vince Vu in 2015 for statistical learning for high-dimensional relational data; Zhu in 2017 for developing statistical theory and computational tools to integrate multimodal data that will lead to the higher accuracy of learning, and enhance information storage, sorting and filtering; Lee and Zhu in 2020 to study the effect of data perturbation on general models in predictive settings for assessment of case influence and model sensitivity and to examine its link to model complexity.
Health and Life Sciences: Shili Lin was PI or co-PI on several grants supporting her research on statistical and computational methods for genetic and genomic data. These include funding received from NIH (2004, 2012, 2015) and from NSF (1999, 2003, 2010, 2012). In addition, Shili was co-PI on an NCI grant received 2004 on integrating genomic and epigenomic alterations in cancer and its microenvironment that was among the first six center grants awarded by the NCI Integrated Biology Program. Finally, Shili served as co-investigator on ten other grants from NIH and from the Bill & Melinda Gates Foundation.
In 2003, Hani Doss was co-PI on an NIH grant to investigate whether asthma and allergic condition biomarkers are related to glioblastoma risk, (with PI Schwartzbaum, College of Public Health). In 2009 and again in 2014, Joe Verducci and collaborators from Leadscope received NIH funding to develop web platforms for analyzing genomic data. In 2006, Verducci collaborated with researchers from the School of Pharmacy, the University of Idaho, and Battelle NW on a 5-year NSF grant to model genetic signaling patterns from the brain to the reproductive system of rainbow trout.
In 2014 Elly Kaizar received NIH Funding for the development of statistical methods to support a model pediatric traumatic-brain-injury data bank. The same year, Shili Lin won research funding to analyze metagenomic count data. An NSF grant was awarded to Laura Kubatko (with co-PI Andrea Wolfe, EEOB) in 2015 to use next-generation sequencing approaches to estimate phylogeny for up to 90% of Penstemon’s 280 + described species to investigate why this species-rich genus has diversified so rapidly across North America. In 2017, Peter Craigmile (together with co-investigators Megan Roberts and Amy Ferketich, College of Public Health) was awarded an exploratory/developmental research grant to evaluate how licensing-law strategies change neighborhood disparities in tobacco retailer density. In 2017, Kate Calder was the lead researcher for an OSU team conducting a first of-its-kind study of adolescent health in an urban environment. She was a Co-PI on NIH grants received in 2009 and 2011 to study aspects of adolescent psychological and behavioral health. In 2020, Jared Huling (with Jennifer Lundine, Speech and Hearing Science) was awarded a grant from the Eunice Kennedy Shriver National Institute of Child Health and Human Development todevelop a “functional status score” to represent a child’s functional mobility, self-care, and cognitive and communication status.
Xinyi Xu was part of an interdisciplinary and multi-institutional group of scientists that was awarded a 5-year National Cancer Institute (NCI) grant in 2022 for investigating longitudinal relationships between environmental factors, colon and rectum cancer prognosis, and survival. Jennifer Sinnott was part of an interdisciplinary team from Statistics and the College of Public Health that was awarded $2.4 million R37 MERIT Award from the National Cancer Institute (NCI) in 2022 to study the results of cancer treatment and, in particular, on understanding why Black women do not receive treatment in line with national recommendations as frequently as do White women.
Jason Hsu’s research in multiple comparisons over many years has impacted biopharmaceutical statistical practice. In addition, he has provided multiple comparisons codes which are incorporated into the software SAS, JMP, and Minitab.
Statistics, Psychology and Marketing: In 2005, the NSF awarded a team of faculty (Dean, MacEachern, Peruggia, Browne, from Statistics, Van Zandt from Psychology, Otter and Allenby from Marketing) one of the first interdisciplinary grants to develop new models of consumer decision making. Joint seminars were held and research teams of faculty and students worked on a wide range of projects spanning the three departments.
In 1999, Verducci collaborated with three faculty from Psychology on a 5-year NIH grant to study grief in teenagers following a parental death. In 2002 Peruggia and Van Zandt received funding from the NSF Division of Social and Economic Sciences for research on Bayesian analysis of chronometric data and, with Craigmile in 2010, they received NSF funding for modeling trends, dependence, and tail structure in sequential response time data. Research on human behavior includes a 2014 NSF grant awarded to Craigmile, Peruggia, and Van Zandt to study new methods for analysis of human performance and a 2022 research pilot award to Peruggia, Addy, and Kunkel for developing quantitative methods for the evaluation of virtual reality experiences.
Engineering and Physics: Goel (Statistics) and McCord (Civil and Environmental Engineering and Geodetic Sciences) co-led a project awarded in 2003 by the National Consortium on Remote Sensing in Transportation-Flow for combining information from satellite and airborne imagery with ground-based data for improved estimation of traffic volumes on a specific highway segment on a typical day and over the entire highway network during a time period. Pratola (Statistics) was part of an interdisciplinary and multi-institutional 2020 NSF grant for bringing statistical methodology to important problems at the frontier of nuclear physics.
Computer Experiments and Computational Efficiency: Santner has received continuous funding from the Hospital for Special Surgery and the Cornell University Biomechanics Program for statistical analysis of knee wear, together with an NIH grant in 2014 for the design of meniscal substitutes via an integrated experimental, computational and statistical approach.
NSF grants were awarded to Santner, Dean and Hans in 2013 for studying complex experiments and high-input simulators, to Vu in 2019 for discovering hidden commonalities between disparate methods for extracting information from data, and to Zhang in 2023 to develop inference tools for accurate risk control in computational acceleration for U-statistics, and network method-of-moments. An NSF grant was awarded to Peruggia in 2006 to study computational issues in model elaboration, diagnostics, and estimation. In 2016, Santner and collaborators received an NSF grant for innovations in statistical modeling, prediction, and design for computer experiments.
Network Analysis: NSF funding was awarded to Calder in 2012 for work on Bayesian methods for socio-spatial point patterns and networks, and to Sivakoff in 2014 (with Parthasarathy, CSE) to study sampling and inference on network analysis.
Crime: Beginning 2007, Calder collaborated with researchers from the Criminal Justice Research Center at OSU to study the patterns and potential causes of spatial variability in crime rates within and across major U.S. cities, receiving an NSF grant in 2008. Craigmile and Stasny, with co-authors, worked on a project to impute missing data in the Uniform Crime Reports, funded by the ASA Committee on Law and Justice Statistics/Bureau of Justice Statistics.
Data Analytics: In 2017, Sivakoff and Kurtek became co-principal investigators on an interdisciplinary grant dealing with the geometric and topological aspects of complex data from mathematical, statistical and algorithmic perspectives. The grant was awarded to Ohio State through the NSF's Transdisciplinary Research in Principles of Data Science Phase I (TRIPODS) Program.