Suprateek Kundu
Adjunct Assoc Professor
Adjunct Associate Professor
Faculty, Biostatistics and Bioinformatics
My research is focused on developing practical statistical methods and theory motivated by high-dimensional biomedical applications in epidemiology, neuroimaging, and -omics data. I work at the interface of statistics, machine learning, and computer science to develop efficient and scalable solutions to complex problems involving data from multiple sources and leveraging prior biological knowledge from existing databases or expert knowledge. Some key areas I currently focus on include high dimensional graphical models and variable selection. Applications include inferring brain networks using fMRI data as a function of clinical, demographic and genetic information, inferring dynamic brain networks which change over time, structural connectivity problems entailing analysis of complex diffusion MRI data, and integrative approaches for imaging genetics involving multimodal data. I also work on Deep Learning algorithms for solving non-linear biomedical problems. I am the Director of the Data Analytics and Biostatistics (DAB) core in the Department of Medicine (DOM), where I serve in a leadership role to establish collaborations.
For further details please visit: https://sites.google.com/view/suprateek/home
Contact Information
1518 Clifton Rd., NE ,
Atlanta , GA 30322-4201
Mailstop: 1518-002-3AA
Phone: 404-727-0931
Fax: (404)727-1370
Email: suprateek.kundu@emory.edu
Areas of Interest
- Genetics
- High Performance Computing
- Imaging
Education
- Ph.D. 2012, University of North Carolina at Chapel Hill
- M.S. 2008, Indian Statistical Institute, Kolkata
- B.S. 2006, Presidency College, India
Affiliations & Activities
Director, Data Analytics and Biostatistics Core, Department of Medicine, Emory University
Associate Editor, Biometrics
Scientific Organizing Committee, IISA 2019
Local Organizing Committee, Statistics in Medical Imaging Conference 2020, Emory University
Core Faculty member at The Center for Biomedical Imaging Statistics.
Core Faculty member at The Center for Visual and Neurocognitive Rehabilitation
Seminar Chair for Fall 2015
PhD Admissions Committee 2015-present
PhD Qualifying Exam Committee 2015-present
Emory Representative for Georgia Statistics Day 2015, 2016
Local Organizing Committee for Georgia Statistics Day 2017
Member of Education Committee, Emory (since Spring 2018)
Publications
- Kundu, S., Ming, J., Nocera, J., McGregor, K.M., 2021, Integrative Analysis for Population of Dynamic Networks with Covariates. , NeuroImage., ,
- Lukemire, J.D., Kundu, S., Pagnoni,G. and Guo, Y. , 2020, Bayesian Joint Modeling of Multiple Brain Functional Networks, Journal of the American Statistical Association, ,
- Kundu, S., Ming, J., Stevens, J., 2020, Dynamic Brain Functional Networks Guided By Anatomical Knowledge. , Brain Connectivity, ,
- Suprateek Kundu and Benjamin B. Risk, 2020, Scalable Bayesian matrix normal graphical models for brain functional network estimation, Biometrics, ,
- Kundu, S., Lukemire. J., Wang, Y., and Guo, Y, 2019, A Novel Joint Brain Network Analysis for Longitudinal Alzheimer's Disease Data, Scientific Reports 9, 19589 (2019) doi:10.1038/s41598-019-55818-z, ,
- Derek Hsu, Falgun H. Chokshi, Patricia A. Hudgins, Suprateek Kundu, Jonathan J Beitler, Mihir R. Patel, & Ashley H. Aiken, 2019, NI-RADS Performance on First Post-treatment FDG-PET/Contrast Enhanced CT in Head & Neck Squamous Cell Carcinoma to Predict Treatment Failure., Otolaryngology - Head and Neck Surgery., ,
- Kundu, S., and Suthaharan, S. , 2019, Privacy-Preserving Predictive Model Using Factor Analysis for Neuroscience Applications, IEEE 5th Intl Conference on Big Data Security on Cloud (BigDataSecurity), IEEE Intl Conference on High Performance and Smart Computing, (HPSC) and IEEE Intl Conference on Intelligent Data and Security (IDS), Washington, DC, USA, 2019, pp. 67-73. doi:10.1109/BigDataSecurity-HPSC-IDS.2019.00023 , ,
- Higgins, I.A., Guo, Y., Kundu, S., Choi, K.S. and Mayberg, H. , 2018, A Differential Degree Test for Comparing Brain Networks. , Human Brain Mapping, ,
- Li, Z.,Chang, C., Kundu, S., and Long, Q, 2018, Bayesian Generalized Biclustering Analysis via Adaptive Structured Shrinkage, Biostatistics, ,
- Kundu, S., Cheng, Y., Shin, M., Manyam, G., Mallick, B.K., Baladandayuthapani, V. , 2018, Bayesian Variable Selection with Structure Learning: Applications to Integrative Genomics, PLOS ONE 13(7): e0195070., ,
- Kundu, S., Mallick, B.K., and Baladandayuthapani, V., 2018, Efficient Bayesian Regularization for Graphical Model Selection, Bayesian Analysis. doi:10.1214/17-BA1086, ,
- Hanna TN, Kundu S, Singh K, Horný M, Wood D, Prater A, Duszak R. , 2018, Emergency Department Imaging Superusers. , Emergency Radiology. , ,
- Kundu, S., Ming, J., Pierce, J., McDowell, J., and Guo, Y., 2018, Estimating Dynamic Brain Functional Networks Using Multi-subject fMRI Data, NeuroImage, ,
- Higgins, I., Kundu,S., and Guo,Y., 2018, Integrative Analysis of Brain Functional Networks Based on Anatomical Knowledge, NeuroImage, Volume 181, Pages 263-278, ISSN 1053-8119., ,
- Falgun H. Chokshi, Nadja Kadom, Nishant Dwivedi, Suprateek Kundu, Ahmed Y. Moussa, Chadi Tannoury Tony Tannoury., 2018, Predicting Congenital Lumbar Spine Stenosis Using the Radiographic Cobb Angle: A Comparison of Imaging Measurement Techniques., Current Problems in Diagnostic Radiology., ,
- Solis-Lemus, C., Ma, X., Hotstetter II, M., Kundu, S. Pimental, D., Peng, Q. , 2018, Prediction of functional markers of mass cytometry data via deep learning. , Statistical Modeling in Biomedical Research - Contemporary Topics and Voices in the Field by Springer Nature. Edited by Yichuan Zhao and Ding-Geng Chen, ,
- Chang, C., Kundu, S., and Long, Q., 2018, Scalable Bayesian Variable Selection for Structured High Dimensional Data, Biometrics, doi: 10.1111/biom.12882. PubMed PMID: 29738602., ,
- Chokshi, F., Kang, J., Kundu, S., and Castillo, M., 2016, Bibliometric Analysis of Manuscript Title Characteristics Associated with Higher Citation Numbers: A Comparison of Three Major Radiology Journals, Current Problems in Diagnostic Radiology. , Accepted,
- Kundu, S. & Kang, J., 2016, Semi-parametric Bayes Graphical Models Incorporating Covariates for Imaging Genetics Applications, Stat (International Statistical Institute). 2016;5(1):322-337. , ,
- Kundu, S., & Dunson, D. , 2014, Bayesian Variable Selection in Semi-parametric Linear Models, Journal of the American Statistical Association, Theory & Methods 109, 437-447 , 109, 437-447
- Kundu, S., & Dunson, D. , 2014, Latent Factor Models for Density Estimation, Biometrika, 101, 641-654
- Gouskova, N.A., Kundu, S., Imrey, P.B., Fine, J.P., 2013, Number Needed to Treat for Time to Event Data with Competing Risks, Statistics in Medicine, 33, 181-192