Surya Tapas Tokdar | Scholars@Duke

Surya Tapas Tokdar
Associate Professor of Statistical Science

Current Appointments & Affiliations

Associate Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2016
Faculty Network Member of the Duke Institute for Brain Sciences, Duke Institute for Brain Sciences, University Institutes and Centers 2014

Contact Information

214 Old Chemistry, Durham, NC 27708
Box 90251, Durham, NC 27708-0251
tokdar@stat.duke.edu (919) 684-2152
Personal site

Background
Education, Training, & Certifications
- Ph.D., Purdue University 2006
Duke Appointment History
- Director or Graduate Studies in Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2016 - 2018
- Co-Director of Graduate Studies in the Department of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2013 - 2016
- Assistant Professor of Statistical Science, Statistical Science, Trinity College of Arts & Sciences 2009 - 2016
Recognition
In the News
- JUL 18, 2018
  
  Neurons Can Carry More Than One Signal at a Time
Awards & Honors
- Leonard J. Savage Dissertation Award (Theory & Methods). ISBA, ASA-SBSS and NBER/NSF Seminars on Bayesian Inference in Econometrics and Statistics. 2006
Research
Selected Grants
- Analyzing Dependent Extremes via Joint Quantile Regression awarded by National Science Foundation 2020 - 2023
- Spatial Information Codes awarded by National Institutes of Health 2017 - 2022
- Information in Limited-Capacity Neural Codes awarded by National Institutes of Health 2014 - 2019
- Understanding Regression Heterogeneity Through Joint Estimation of Conditional Quantiles awarded by National Science Foundation 2016 - 2019
- Bayesian Methods for Assessing Gene by Environment Interactions awarded by National Institutes of Health 2009 - 2015
External Relationships
- QuaEra Insights
Publications & Artistic Works
Selected Publications
- Academic Articles
  - Glynn, C., S. T. Tokdar, B. Howard, and D. L. Banks. “Bayesian analysis of dynamic linear topic models.” Bayesian Analysis 14, no. 1 (January 1, 2019): 53–80. https://doi.org/10.1214/18-BA1100.
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  - Caruso, Valeria C., Jeff T. Mohl, Christopher Glynn, Jungah Lee, Shawn M. Willett, Azeem Zaman, Akinori F. Ebihara, et al. “Single neurons may encode simultaneous stimuli by switching between activity patterns.” Nature Communications 9, no. 1 (July 13, 2018): 2715. https://doi.org/10.1038/s41467-018-05121-8.
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  - Burris, Kyle, Kelly Vittetoe, Benjamin Ramger, Sunith Suresh, Surya T. Tokdar, Jerome P. Reiter, and L Gregory Appelbaum. “Sensorimotor abilities predict on-field performance in professional baseball.” Scientific Reports 8, no. 1 (January 8, 2018): 116. https://doi.org/10.1038/s41598-017-18565-7.
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  - Klemish, David, Benjamin Ramger, Kelly Vittetoe, Jerome P. Reiter, Surya T. Tokdar, and Lawrence Gregory Appelbaum. “Visual abilities distinguish pitchers from hitters in professional baseball.” J Sports Sci 36, no. 2 (January 2018): 171–79. https://doi.org/10.1080/02640414.2017.1288296.
    Full Text Open Access Copy Link to Item
  - Yang, Y., and S. Tokdar. “Joint estimation of quantile planes over arbitrary predictor spaces.” Journal of the American Statistical Association 112, no. 519 (September 15, 2017): 1107–20. https://doi.org/10.1080/01621459.2016.1192545.
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  - Caruso, Valeria, Jeff Mohl, Christopher Glynn, Jungah Lee, Shawn Willett, Azeem Zaman, Akinori Ebihara, et al. “Evidence for time division multiplexing: Single neurons may encode simultaneous stimuli by switching between activity patterns,” February 9, 2017. https://doi.org/10.1101/107185.
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  - Montagna, S., and S. T. Tokdar. “Computer emulation with non-stationary Gaussian processes.” Siam/Asa Journal of Uncertainty Quantification 4 (2016): 26–47.
    Link to Item
  - Yang, Y., and S. T. Tokdar. “Minimax-optimal nonparametric regression in high dimensions.” Annals of Statistics 43, no. 2 (2015): 652–74. https://doi.org/10.1214/14-AOS1289.
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  - Pati, Debdeep, David B. Dunson, and Surya T. Tokdar. “Posterior consistency in conditional distribution estimation.” Journal of Multivariate Analysis 116 (April 2013): 456–72. https://doi.org/10.1016/j.jmva.2013.01.011.
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  - Banerjee, A., D. B. Dunson, and S. T. Tokdar. “Efficient Gaussian process regression for large datasets.” Biometrika 100, no. 1 (2013): 75–89. https://doi.org/10.1093/biomet/ass068.
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  - Shen, W., S. T. Tokdar, and S. Ghosal. “Adaptive Bayesian multivariate density estimation with Dirichlet mixtures.” Biometrika 100, no. 3 (2013): 623–40. https://doi.org/10.1093/biomet/ast015.
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  - Montagna, Silvia, Surya T. Tokdar, Brian Neelon, and David B. Dunson. “Bayesian latent factor regression for functional and longitudinal data.” Biometrics 68, no. 4 (December 2012): 1064–73. https://doi.org/10.1111/j.1541-0420.2012.01788.x.
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  - Martin, R., and S. T. Tokdar. “A nonparametric empirical Bayes framework for large-scale multiple testing.” Biostatistics 13, no. 3 (2012): 427–39. https://doi.org/10.1093/biostatistics/kxr039.
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  - Tokdar, S. T., and J. B. Kadaney. “Simultaneous linear quantile regression: A semiparametric bayesian approach.” Bayesian Analysis 7, no. 1 (2012): 51–72. https://doi.org/10.1214/12-BA702.
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  - Tokdar, S. T., I. Grossmann, J. B. Kadane, A. S. Charest, and M. J. Small. “Impact of beliefs about atlantic tropical cyclone detection on conclusions about trends in tropical cyclone numbers.” Bayesian Analysis 6, no. 4 (December 1, 2011): 547–72. https://doi.org/10.1214/11-BA621.
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  - Bisi, A., M. Dada, and S. Tokdar. “A censored-data multiperiod inventory problem with newsvendor demand distributions.” Manufacturing and Service Operations Management 13, no. 4 (September 1, 2011): 525–33. https://doi.org/10.1287/msom.1110.0340.
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  - Martin, R., and S. T. Tokdar. “Semiparametric inference in mixture models with predictive recursion marginal likelihood.” Biometrika 98, no. 3 (September 1, 2011): 567–82. https://doi.org/10.1093/biomet/asr030.
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  - Tokdar, S. T., Y. M. Zhu, and J. K. Ghosh. “Bayesian density regression with logistic Gaussian process and subspace projection.” Bayesian Analysis 5, no. 2 (December 1, 2010): 319–44. https://doi.org/10.1214/10-BA605.
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  - Tokdar, Surya, Peiyi Xi, Ryan C. Kelly, and Robert E. Kass. “Detection of bursts in extracellular spike trains using hidden semi-Markov point process models.” Journal of Computational Neuroscience 29, no. 1–2 (August 2010): 203–12. https://doi.org/10.1007/s10827-009-0182-2.
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  - Tokdar, S. T., and R. E. Kass. “Importance sampling: A review.” Wiley Interdisciplinary Reviews: Computational Statistics 2, no. 1 (2010): 54–60. https://doi.org/10.1002/wics.56.
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  - Tokdar, S. T., M. Ryan, and J. K. Ghosh. “Consistency of a recursive estimate of mixingdistributions.” Annals of Statistics 37, no. 5 A (October 1, 2009): 2502–22. https://doi.org/10.1214/08-AOS639.
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  - Martin, R., and S. T. Tokdar. “Asymptotic properties of predictive recursion: Robustness and rate of convergence.” Electronic Journal of Statistics 3 (January 1, 2009): 1455–72. https://doi.org/10.1214/09-EJS458.
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  - Bogdan, Małgorzata, Jayanta K. Ghosh, and Surya T. Tokdar. “A comparison of the Benjamini-Hochberg procedure with some Bayesian rules for multiple testing,” 2008, 211–30. https://doi.org/10.1214/193940307000000158.
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  - Bogdan, M., J. K. Ghosh, A. Ochman, and S. T. Tokdar. “On the empirical bayes approach to the problem of multiple testing.” Quality and Reliability Engineering International 23, no. 6 (October 1, 2007): 727–39. https://doi.org/10.1002/qre.876.
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  - Tokdar, S. T. “Towards a faster implementation of density estimation with logistic gaussian process priors.” Journal of Computational and Graphical Statistics 16, no. 3 (September 1, 2007): 633–55. https://doi.org/10.1198/106186007X210206.
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  - Tokdar, S. T., and J. K. Ghosh. “Posterior consistency of logistic Gaussian process priors in density estimation.” Journal of Statistical Planning and Inference 137, no. 1 (January 1, 2007): 34–42. https://doi.org/10.1016/j.jspi.2005.09.005.
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  - Tokdar, S. T. “Posterior consistency of dirichlet location-scale mixture of normals in density estimation and regression.” Sankhya: The Indian Journal of Statistics 68, no. 1 (February 1, 2006): 90–110.
- Book Sections
  - Cunningham, E., S. T. Tokdar, and J. S. Clark. “A vignette on model-based quantile regression: Analysing excess zero response.” In Flexible Bayesian Regression Modelling, 27–64, 2019. https://doi.org/10.1016/B978-0-12-815862-3.00008-1.
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  - Ghosh, J. K., and S. T. Tokdar. “Convergence and consistency of Newton’s algorithm for estimating mixing distribution.” In Frontiers in Statistics: Dedicated to Peter John Bickel in Honor of His 65th Birthday, 429–43, 2006. https://doi.org/10.1142/9781860948886_0019.
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Teaching & Mentoring
Recent Courses

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Education, Training, & Certifications

Duke Appointment History

In the News

Awards & Honors

Selected Grants

External Relationships

Selected Publications

Academic Articles

Book Sections

Recent Courses