Faculty

Peihua Qiu is Dean’s Professor and Founding Chair of the Department of Biostatistics at the University of Florida. He received his PhD in statistics from the Department of Statistics at the University of Wisconsin at Madison in 1996. He then worked as a senior research consulting statistician for the Biostatistics Center at the Ohio State University during 1996-1998, and as an Assistant Professor (1998-2002), Associate Professor (2002-2007), and Full Professor (2007-2013) of the School of Statistics at the University of Minnesota during 1998-2013. He was recruited to the University of Florida to develop its new Department of Biostatistics in 2013. Qiu has made substantial contributions in the research areas of jump regression analysis, image processing, statistical process control, survival analysis, dynamic disease screening, and spatio-temporal disease surveillance. So far, he has published three books and over 170 research papers in refereed journals in these areas. He is an elected fellow of the American Association for the Advancement of Science (AAAS), an elected fellow of the American Statistical Association (ASA), an elected fellow of the American Society for Quality (ASQ), an elected fellow of the Institute of Mathematical Statistics (IMS), and an elected member of the International Statistical Institute (ISI). He served as associate editor for a number of top statistical journals, including Journal of the American Statistical Association, Biometrics, and Technometrics. He was the Editor-in-Chief of the flagship statistical journal Technometrics during 2014-2016, and the recipient of the Shewhart Medal from ASQ in 2024.

Rhonda Bacher is an Associate Professor of Biostatistics at the University of Florida. She leads the Bacher Group in developing relevant statistical methods and computational software addressing important challenges in genomics, epigenomics, and biomedical research. Her research group is dedicated to ensuring accessibility of their software and contributing to the larger research community through open-source platforms. In their collaborations with scientists and clinicians, they use statistical models and machine learning to better understand how molecular phenotypes change in response to environmental stressors, age, and disease.

The research interests of Dr. Brant are focused on the role of DNA methylation and chromatin structure in regulating gene expression and how perturbations in the epigenome can result in disease onset and progression. Dr. Brant received his doctorate degree from the University of Florida in the department of Biochemistry and Molecular Biology under the mentorship of Dr. Thomas P. Yang. In his current position as a Assistant Professor at the UF Health Cancer Center, Dr. Brant works to provide computational and bioinformatics support for cancer center members, and is developing new technologies for assaying chromatin structure.

Dr. Li Chen is a tenured associate professor in the Department of Biostatistics at University of Florida. He joined the department under the UF artificial intelligence initiative. Dr. Chen focuses on developing deep learning and statistical methods and software for analyzing large-scale multi-omics data, including but not limited to genetics, single-cell genomics and metagenomics. He is interested in applying the methods developed to study aging and cancer, disseminating software developed for public health researchers to use, and integrating multi-omics data with imaging and EHR data.

Somnath Datta received his undergraduate and master’s degrees in statistics from Indian Statistical Institute followed by a doctoral degree in Statistics and Probability from Michigan State University. He joined the Department of Biostatistics at University of Florida as a tenured full professor in July of 2015 under the preeminence initiative. Prior to that, he was Professor in the Statistics department at the University of Georgia and in the Bioinformatics & Biostatistics department at the University of Louisville. Over the years, he published over one hundred and eighty research papers in various peer reviewed Statistics & Biostatistics journals and delivered over 100 invited talks at various national and international conferences. He developed novel statistical methods for analyzing public health, dental and biomedical data. His collaborative research interests include bioinformatics, spinal cord injury research, plant pathology and informatics-based materials science research. His research projects have been supported by grants from the US National Institutes of Health, the National Science Foundation, and the National Security Agency. He is Elected Member of International Statistical Institute, Elected Fellow of American Statistical Association, and Elected Fellow of Institute of Mathematical Statistics. He has served as a director/co-director of over 25 doctoral dissertation committees.

Professional Biography Susmita Datta has received her PhD degree in Statistics from the University of Georgia, Athens, Georgia, USA followed by a postdoctoral training in Biostatistics from the Emory University. She has joined the Department of Biostatistics at the University of Florida in 2015 with a Preeminent hire as a tenured Full Professor. Prior to that, she was a Distinguished Scholar and a Tenured Full Professor at the University of Louisville and at the Georgia State University as a tenured Associate Professor. She is a fellow of the American Statistical Association (ASA), an elected member of the International Statistical Institute (ISI), and fellow of the American Association for the Advancement of Science (AAAS). She is one of the three elected members of the International Indian Statistical Association (IISA), elected RECOMB member of ENAR of Biometric Society and was the elected President of Caucus for Women in Statistics in 2013. Her research area includes Biostatistics and Bioinformatics/Computational Biology. Her research contributions spans all ‘omics’ related high dimensional data such as RNA-sequencing, Single Cell RNA sequencing, Spatial transcriptomics, and mass spectrometry data for proteiomics, lipidomics, metabolomics and multi-omics integration. In addition to that, her computing laboratory is involved in methodological and software development in clustering and classification techniques, statistical issues in population biology, systems biology, survival analysis, multi-state models and big data analytics. She has published a book on “Statistical Analysis of Proteomics, Metabolomics, and Lipidomics Data Using Mass Spectrometry” by Springer. Dr. Datta is widely (>140) published in peer reviewed journals. The National Science Foundation and the National Institutes of Health have continuously funded her work. Her constant involvement with Big and fat data made her interested in Data science. She has guided more than 47 students through their theses and dissertations. She promotes women in STEM fields.

Jonathan Fischer is a Clinical Assistant Professor in the Department of Biostatistics. He has experience teaching undergraduate and graduate students in probability, statistics, data science, and computational biology. His research interests generally lie in the development and application of methods for use with high-throughput sequencing data, particularly the transcriptomic variety. Dr. Fischer earned his PhD in Statistics in 2018 from the University of California, Berkeley, and received a BS in Physics and Mathematics from the College of William & Mary in 2013.

Steven Foti is a Clinical Assistant Professor in the Department of Biostatistics and Director of Graduate Studies. He received his PhD in Statistics Education in 2017 and his MS in Statistics in 2013, both from the University of Florida. Steven is originally from New York where he earned his BS in Applied Mathematics and Statistics and Physics from Clarkson University. He teaches Biostatistics courses in literacy, methods, and data visualization to graduate students in public health and medicine. His experience and interests are in statistics education, statistical literacy, and assessment.

John Kairalla is a Research Associate Professor and Associate Program Director of the Children’s Oncology Group, Statistics and Data Center-Gainesville in the Department of Biostatistics at the University of Florida. He received his PhD in Biostatistics from the University of North Carolina at Chapel Hill. His current research focus is in clinical trial design, development, monitoring, and analysis with applications in childhood cancer research with a focus on late phase pediatric Acute Lymphoblastic Leukemia (ALL) trials.

Dr. Ji-Hyun Lee is a Professor of Biostatistics in the Department of Biostatistics at the University of Florida and Associate Director for the Cancer Quantitative Sciences at the University of Florida Health Cancer Center (UFHCC). Her role at the UFHCC involves providing strategic leadership and direction, fostering rigorous and integrated research among Cancer Center scientists. Dr. Lee earned her master’s and doctorate in Biostatistics from the University of North Carolina at Chapel Hill. Her research focuses on the design and conduct of clinical trials, cluster/group randomized trials, methods for repeated measurements, and best statistical practices. She also serves on the scientific review and monitoring committee for UFHCC’s therapeutic clinical trials.

Dr. Lee is an elected Fellow of the American Statistical Association (ASA) and a certified professional statistician (PStat®) through the ASA. In 2023, she was elected as the 120th President of the ASA with her term as President-Elect beginning in 2024 and serving President in 2025. Since 2024, Dr. Lee has also served as Chief Statistical Advisor for Oncology at Nature Medicine.

Dr. Zhigang Li is an associate professor with tenure in the Department of Biostatistics at University of Florida. He joined the department as an associate professor in 2018 under the University preeminence initiative. His research interests include microbiome data analysis, mediation analysis, causal inference, high-dimensional data analysis, longitudinal data analysis, survival analysis, joint modeling of longitudinal data and survival in palliative care research. Dr. Li has been PI of multiple NIH grants including his ongoing R01 project “Mediation analysis methods for modeling human microbiome mediating disease-leading causal pathways in children”. Dr. Li loves collaboration with colleagues. He has many years of experience on collaborating with epidemiologists, children’s health experts, environmental health scientists, pediatricians, palliative care researchers, cancer researchers, psychologists, physicians, engineers, neurologists, radiologists, etc.

Dr. Liang is an assistant professor with the Artificial Intelligence Initiative in the Department of Biostatistics. He received his Ph.D. in statistics from the University of Wisconsin-Madison in 2018. After graduation, he briefly worked at Google as a data scientist and joined the Fred Hutchinson Cancer Research Center as a post-doctoral research fellow. Dr. Liang’s research interest focuses on treatment recommendations based on patient-level information, identifying signals from high-dimensional data, and other novel machine learning techniques with applications to biomarker identification, cancer surveillance, and digital health.

Dr. Tuo Lin is a Research Assistant Professor in the Department of Biostatistics at the University of Florida (UF), with a joint position in the Division of Quantitative Sciences at the University of Florida Health Cancer Center (UFHCC). He obtained his Ph.D. degree in Biostatistics from the University of California San Diego. Dr. Lin’s methodological research focuses on semiparametric theory and missing data, survey methodology, statistical learning, network models and neuroimaging data analysis, and their applications to biomedical and psychosocial research. In term of the collaborative research, he is interested in applying novel statistical methods and designs to cancer studies and clinical trials.

Dr. Longini received his Ph.D. in Biometry at the University of Minnesota in 1977. He began his career with the International Center for Medical Research and Training and the Universidad del Valle in Cali, Colombia, where he worked on tropical infectious disease problems and taught courses in biomathematics. Following that, he was a professor biostatistics at the University of Michigan, Emory University and the University of Washington. He currently is a professor of biostatistics at the University of Florida and Director of the Center for Statistical and Quantitative Infectious Diseases (CSQUID), the Emerging Pathogens Institute, at the University of Florida. His research interests are in the area of stochastic processes applied to epidemiological problems. He has specialized in the mathematical and statistical theory of epidemics–a process that involves constructing and analyzing mathematical models of disease transmission, disease progression and the analysis of infectious disease data based on these models. He works extensively in the design and analysis of vaccine and infectious disease prevention trials and observational studies. Dr. Longini has worked on the analysis of epidemics of COVID-19, Ebola, mpox, influenza, HIV, tuberculosis, cholera, dengue fever, and other infectious diseases. Dr. Longini is also working with the Department of Health and Human Services, the World Health Organization, the CDC and other public health organizations on mathematical and statistical models for the control of a possible bioterrorist attack with an infectious agent such as smallpox, and other natural infectious disease threats such as COVID-19, pandemic influenza or another coronavirus. Dr. Longini is author or coauthor of over 256 scientific papers and he has won a number of awards for excellence in research, including the Howard M. Temin Award in Epidemiology for “Scientific Excellence in the Fight against HIV/AIDS,” two CDC Statistical Science Awards for both “Best Theoretical and Applied Papers,” the CDC James H. Nakano Citation “for an outstanding scientific publications” the Science Magazine, one of the top 10 “Breakthrough of the Year” for 2015, Guinea Ebola ring vaccination trial, the Aspen Institute Italia Award for scientific research and collaboration between Italy and the United States, 2016, and the David A. Paulus Lifetime Achievement Award, College of Medicine, University of Florida. April 25, 2022. He is a Fellow of the American Statistical Association and a Fellow of the American Association for the Advancement of Science. Dr. Longini has Erdős number = 3.

Dr. Lou is a Research Professor in the Department of Biostatistics, the University of Florida and an Adjunct Professor in the Department of Mathematics and Statistics, the University of Arkansas at Little Rock. Dr. Lou earned his Ph.D. in of Statistical Genetics and Bioinformatics from Zhejiang University, China, in 1997. And then he was recruited as an Assistant Professor at Zhejiang University. He came to the U.S. for pursuing postdoctoral training in the Department of Statistics, the University of Florida, in 2002. He was an Assistant Professor at the University of Virginia, an Associate Professor at the University of Alabama at Birmingham, Tulane University, and the University of Arkansas for Medical Sciences, and a Professor at the University of Arkansas for Medical Sciences.

Dr. Lu’s research interests are primarily in statistical genetics and statistical/machine learning. One area of research is to develop statistical/machine learning methods (e.g., tree and deep learning) for high-dimensional data analyses (e.g., genetic data analysis). In parallel with statistical/machine learning research, he is also interested in developing and applying new statistical methods (e.g., U-statistics). In addition to developing new methods, he collaborates with other researchers to investigate various biomedical and public health research questions.

Dr. Arlene Naranjo is a Research Associate Professor in the Department of Biostatistics and Associate Program Director of the Children’s Oncology Group (COG) Statistics & Data Center (SDC) at the University of Florida. As lead statistician for neuroblastoma with the COG SDC, Dr. Naranjo is responsible for designing future studies, performing sample size and power calculations, monitoring open studies, and analyzing results from pediatric clinical trials. Her research interests include clinical trials design & analysis, survival analysis, longitudinal data analysis, and hierarchical linear models. Dr. Naranjo helped develop and currently co-teaches the graduate-level course Design and Conduct of Clinical Trials.

Robert Parker is a Clinical Assistant Professor in the Department of Biostatistic. He received his PHD in Statistics in 2017 from the University of Florida, his MS in Mathematics from Mississippi State University in 2012, and his BS in Mathematics from Millsaps College. Robert teach Biostatistics courses to both undergraduate and graduate students in public health and medicine. His research interests lie mainly in the areas of probability theory, Bayesian methods, and statistical methods for analyzing non-Euclidean data.

I am an assistant professor in Department of Biostatistics, University of Florida and an affiliated member in the UF Artificial Intelligence Academic Initiative. Before that, I was an Postdoctoral associate at Duke University. My primary focus is on data science and in developing innovative statistical modeling frameworks and corresponding inference methodology motivated by complex applications with strong theoretical support. I received my PhD from NC State.

I am interested to develop cool statistical methods with substantial theoretical support in non-parametric/High dimensional modeling, Machine learning, manifold learning, graphical modeling, complex structure learning motivated by a variety of applications for example brain imaging, nutritional epidemiology, image precessing, time-series analysis etc. Since most of my works are in Bayes paradigm, it is also often of great interest to develop flexible prior distributions to study complex spaces with theoretical support and develop computational algorithms that are scalable and highly efficient.

We focus on developing new methods for clinical trials.

Software: Fisher’s exact approach for post hoc analysis of a chi-squared test Post hoc test, Fisher test, Exact test.

https://adaptivedesignstrial.shinyapps.io/posthoc/

Lixia Wang is a Clinical Assistant Professor and Director of the Online MS Program in the Department of Biostatistics. She received her PhD in Mathematics from the Chinese Academy of Sciences. She has a MS from Fudan University in Probability and Mathematical Statistics as well as a MS in Statistical Computing (Data Mining Track) from the University of Central Florida, and a BS in Computational Mathematics from Wuhan University. She had been teaching statistics and mathematics at Hubei University of Automotive Technology, Beijing University of Posts and Telecommunications, University of Central Florida, and Rollins College, respectively before joining the University of Florida. Her research interests include applications of statistics in public health and medicine, mathematical epidemiology, the history of mathematics and statistics, and statistics education.

Dr. Feifei Xiao is an Associate Professor in the Department of Biostatistics with the Artificial Intelligence Initiative. Dr. Xiao’s research mainly focuses on the development and application of powerful and efficient statistical methods for high throughput genetics and genomics data, driven by the challenges arising from the modern biotechnologies such as next-generation sequencing and single cell sequencing. Dr. Xiao is interested in exploring the advantages of machine learning methods and approaches in public health related outcomes, especially in handling high throughput data. Dr. Xiao works on the next generation chromosomal copy number variation detection, integrative analysis of ‘omics’ data (such as SNP, methylation and expression data), and neuroimaging genetic data analysis.

Dr. Wei Xue is a Research Assistant Professor with the biostatistics department with a shared research assignment. She is a valuable member of the Children’s Oncology Group (COG), the world’s largest NIH/NCI sponsored clinical trials organization devoted exclusively to childhood and adolescent cancer research. Dr. Xue is the lead statistician on Soft Tissue Sarcoma (STS) Committees. She provides statistical support in all aspects of COG clinical trials in STS area by developing protocols, monitoring ongoing trials, conducting statistical analysis, and reporting and uploading research documents. Additionally, she is a member of the Biostatistics, Epidemiology and Research Design (BERD) group. A team of researchers who provide a central location for investigators to seek research design and analysis support through the UF Clinical and Translational science Institute (CTSI).