Subharup Guha,
Associate Professor
Accomplishments
Top Faculty Achiever
2016
·
University of Missouri
Faculty Fellowship Award
2014
·
Department of Statistics, University of Missouri
Craig Cooley Memorial Prize -for scholarly excellence and leadership qualities
2004
·
Department of Statistics, Ohio State University
Thomas and Jean Powers Teaching Award
2003
·
Department of Statistics, Ohio State University
Student Paper Competition Award
2002
·
ASA Statistical Computing and Graphics Sections
Teaching Profile
Courses Taught
2018-2024
PHC6937 Special Topics in Public Health
2020-2025
PHC7090 Advanced Biostatistical Methods I
2018-2020,2022
PHC7979 Advanced Research
2021
PHC6905 Independent Study
2021-2022
PHC7980 Research for Doctoral Dissertation
Research Profile
Subha Guha is an expert in statistical modeling for cancer genomics and computing for omics and microbiome datasets. As PI or co-investigator of research grants from NIH and NSF, he has developed novel models for integrative analyses of multi-domain, high-throughput biomedical studies. He has extensive experience with statistical computing and machine learning to efficiently implement these methodologies for high-dimensional data.
Open Researcher and Contributor ID (ORCID)
0000-0002-5524-1827
Areas of Interest
- Longitudinal Data Analysis
- Bayesian modeling
- Biostatistics
- Causal inference
- Clustering and classification
- Cognitive Neuroscience
- Computational methods for Big Data
- Connectomics
- Data Integration
- Development and testing of novel medical devices
- Generalized linear models
- Health disparities and vulnerable populations
- Hidden Markov models
- High-dimensional inference
- MCMC simulation
- Machine Learning
- Meta-analysis
- Microbiome data analysis
- Nonparametric Bayesian methods
- Observational studies
- Statistical computing
- Statistical methods
- Survival Analysis
- cancer genomics
Publications
Academic Articles
2024
Bayesian Inference for High Dimensional Cox Models with Gaussian and Diffused-Gamma Priors: A Case Study of Mortality in COVID-19 Patients Admitted to the ICU
Statistics in Biosciences.
16(1):221-249
[DOI] 10.1007/s12561-023-09395-5.
[PMID] 38651050.
2024
Causal Meta-Analysis by Integrating Multiple Observational Studies with Multivariate Outcomes
Biometrics.
80(3)
[DOI] 10.1093/biomtc/ujae070.
[PMID] 39073772.
2023
Nonparametric Bayes Differential Analysis of Multigroup DNA Methylation Data
Bayesian Analysis.
[DOI] 10.1214/23-BA1407.
2023
What is the probability of realizing a distribution from a stick-breaking process that falls outside an epsilon-ball on the base measure?
Bayesian Analysis.
81:352-353
2022
A novel approach to augment single-arm clinical studies with real-world data.
Journal of biopharmaceutical statistics.
32(1):141-157
[DOI] 10.1080/10543406.2021.2011902.
[PMID] 34958629.
2022
Predicting Phenotypes from Brain Connection Structure
Journal of the Royal Statistical Society Series C: Applied Statistics.
71(3):639-668
[DOI] 10.1111/rssc.12549.
2021
Metagenomic Geolocation Prediction Using an Adaptive Ensemble Classifier.
Frontiers in genetics.
12
[DOI] 10.3389/fgene.2021.642282.
[PMID] 33959149.
2020
A Bayesian Restoration of the Duality between Principal Components of a Distance Matrix and Operational Taxonomic Units in Microbiome Analyses
.
2020
Probabilistic Detection and Estimation of Conic Sections from Noisy Data
Journal of Computational and Graphical Statistics.
2020
Semiparametric Bayesian Markov Analysis of Personalized Benefit-Risk Assessment
Annals of Applied Statistics.
2019
A genomics-informed computational biology platform prospectively predicts treatment responses in AML and MDS patients.
Blood advances.
3(12):1837-1847
[DOI] 10.1182/bloodadvances.2018028316.
[PMID] 31208955.
2017
Semiparametric Bayesian Analysis of High-Dimensional Censored Outcome Data
.
194-204
2016
A Nonparametric Bayesian Technique for High-Dimensional Regression
.
10:3374-3424
2015
A Hidden Markov Model for Detecting Differentially Expressed Genes from RNA-Seq Data
Annals of Applied Statistics.
9:901-925
2015
Nonparametric Variable Selection, Clustering and Prediction for Large Biological Datasets
.
2014
Bayesian disease classification using copy number data.
Cancer informatics.
13(Suppl 2):83-91
[DOI] 10.4137/CIN.S13785.
[PMID] 25336897.
2011
Discussion of Sampling schemes for generalized linear Dirichlet process random e_ects models by Kyung, Gill and Casella
Statistical Methods and Applications.
20:291-293
2010
Bayesian Hidden Markov Modeling of Array CGH Data
Journal of the American Statistical Association.
103(482):485-497
[DOI] 10.1198/016214507000000923.
[PMID] 22375091.
2010
Parametric and Semiparametric Hypotheses in the Linear Model
.
39:165-180
2010
Posterior Simulation in Countable Mixture Models for Large Datasets
Journal of the American Statistical Association.
105:775-786
2009
Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates
Journal of Computational and Graphical Statistics.
18:818-837
2008
Bayesian Hidden Markov Modeling of Array CGH Data.
Journal of the American Statistical Association.
103(482):485-497
[PMID] 22375091.
2008
Posterior Simulation in the Generalized Linear Mixed Model with Semiparametric Random Effects
Journal of Computational and Graphical Statistics.
17:410-425
2006
Generalized Post-stratification and Importance Sampling for Subsampled Markov Chain Monte Carlo Estimation
Journal of the American Statistical Association.
101:1175-1184
2006
Mixture Cure Survival Models with Dependent Censoring
Journal of the Royal Statistical Society Series B-Statistical Methodology.
69:285-306
2005
Spatio-temporal Analysis of Ischemic Heart Disease in NSW, Australia
Environmental and Ecological Statistics.
12:427-448
2004
Benchmark Estimation for Markov Chain Monte Carlo Samples
Journal of Computational and Graphical Statistics.
13:683-701
2003
Discussion of A theory of statistical models for Monte Carlo integration by Kong, McCullagh, Nicolae, Tan and Meng
Journal of the Royal Statistical Society Series B-Statistical Methodology.
65
Grants
Jun 2024
ACTIVE
Biomechanics Contributions to Symptoms and Joint Health in Individuals with Rotator Cuff Tears
Role: Co-Investigator
Funding: NATL INST OF HLTH NIAMS
Jun 2023
ACTIVE
The Boston Lung Cancer Survivor Cohort
Role: Principal Investigator
Funding: HARVARD TH CHAN SCHOOL OF PUBLIC HEALTH
via NATL INST OF HLTH NCI
May 2023
ACTIVE
Nervous system influences on recovery from painful rotator cuff tears
Role: Co-Investigator
Funding: NATL INST OF HLTH NIAMS
Sep 2022
ACTIVE
Detecting racial disparities in cancer survival by integrating multiple high-dimensional observational studies
Role: Principal Investigator
Funding: UNIV OF MICHIGAN
via NATL INST OF HLTH NCI
Sep 2020
– Sep 2023
Improving Sexually Transmitted Infection Screening and Treatment among People Living with or at Risk for HIV
Role: Project Manager
Funding: RUTGERS STATE UNIV
via US HLTH RESOURCES AND SERV ADMN HIV/AIDS
Sep 2018
– Aug 2020
New Bayesian Nonparametric Paradigms of Personalized Medicine for Lung Cancer
Role: Principal Investigator
Funding: NATL SCIENCE FOU
Education
Postdoctoral Research Fellow
2004-2007
·
Harvard School of Public Health
Ph.D. in Statistics
1999-2004
·
Ohio State University
M.Sc. (5-Year Integrated) in Statistics
1992-1997
·
Indian Institute of Technology, Kanpur, India
Contact Details
Phones:
- Business:
- (352) 294-5921
Emails:
- Business:
- s.guha@ufl.edu
Addresses:
- Business Mailing:
-
PO BOX 117450
GAINESVILLE FL 326110001 - Business Street:
-
2004 MOWRY RD., CTRB, RM. 5225
GAINESVILLE FL 32610