News
Professor David Blei, with co-authors Matthew Hoffman and Francis Bach, was recognized with a Test of Time Award at NeurIPS, the world’s top machine learning conference, for scaling his topic modeling algorithm to billions of documents.
Professor David Blei, with co-authors Matthew Hoffman and Francis Bach, was recognized with a Test of Time Award at NeurIPS, the world’s top machine learning conference, for scaling his topic modeling algorithm to billions of documents.

Professor David Blei, with co-authors Matthew Hoffman and Francis Bach, was recognized with a Test of Time Award at NeurIPS, the world’s top machine learning conference, for scaling his topic modeling algorithm to billions of documents....

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Faculty and Distinguished Postdoctoral Fellow positions available starting Fall 2022
Faculty and Distinguished Postdoctoral Fellow positions available starting Fall 2022
Department of Statistics at Columbia University Faculty Positions Starting Fall 2022 Tenure-track Assistant Professor Liimited Term Assistant Professor Distinguished Postdoctoral Fellow Lecturer in Discipline Tenure-track Assistant Professor Position starting Fall 2022

Position Description:The Department of Statistics invites applications for a tenure-track Assistant Professor position to begin July 1, 2022....

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Congratulations to Tian Zheng on being awarded the 2020-2021 Lenfest Distinguished Faculty Award.
Congratulations to Tian Zheng on being awarded the 2020-2021 Lenfest Distinguished Faculty Award.

Congratulations to Tian Zheng on being awarded the 2020-2021 Lenfest Distinguished Faculty Award.

Each year the Lenfest Distinguished Faculty Awards honor the presence and the work of extraordinary faculty in Arts and Sciences....

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Congratulations to Cynthia Rush on being selected as one of the Fall 2021 junior faculty grants awardees.
Congratulations to Cynthia Rush on being selected as one of the Fall 2021 junior faculty grants awardees.

Congratulations to Cynthia Rush on being selected as one of the Fall 2021 junior faculty grants awardees.

The Provost’s Grants Program offers grant support to further the scholarship of outstanding junior faculty who contribute to the diversity goals of the University by their research, teaching, and mentoring activities....

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Congratulations to Anne van Delft on winning the 2021 Itô Prize
Congratulations to Anne van Delft on winning the 2021 Itô Prize

Congratulations to Anne van Delft on winning the 2021 Itô Prize for her paper entitled: “A note on quadratic forms of stationary functional time series under mild conditions” published in the journal Stochastic Processes and Applications....

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Department of Statistics is to participate in a new NIH DS-I Africa award to Columbia University.
Department of Statistics is to participate in a new NIH DS-I Africa award to Columbia University.

The Department of Statistics is proud to participate in a new NIH DS-I Africa award to Columbia University.

The National Institutes of Health is investing about $74.5 million over five years to advance data science, catalyze innovation, and spur health discoveries across Africa....

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Congratulations to Yixin Wang on being selected as one of the winners of the 2021 Blackwell-Rosenbluth Award.
Congratulations to Yixin Wang on being selected as one of the winners of the 2021 Blackwell-Rosenbluth Award.

Congratulations to Yixin Wang on being selected as one of the winners of the 2021 Blackwell-Rosenbluth Award.

The winners will present their work at the JB^3 webinar series on November 10 (Trevor, Daniel and Yixin) and 12 (Marta, Samuel and Dootika) at 1pm UTC hosted by Bocconi and Universidad Nacional Autónoma de México (UNAM), respectively....

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Introducing Diahmin Hawkins, Our 1st  Bridge to Ph.D. in STEM Scholar
Introducing Diahmin Hawkins, Our 1st  Bridge to Ph.D. in STEM Scholar

Introducing Diahmin Hawkins, Our 1st  Bridge to Ph.D. in STEM Scholar

A native of Birmingham, Alabama, Diahmin graduated Magna Cum Laude with a B.S....

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Recent Faculty Publications

Before data analysis: Additional recommendations for designing experiments to learn about the world.
Andrew Gelman (2023).
Pathfinder: Parallel quasi-Newton variational inference.
Andrew Gelman (2022).
Toward a taxonomy of trust for probabilistic machine learning. Science Advances, 9(7), eabn3999.
Broderick, T., Gelman, A., Meager, R., Smith, A. L., & Zheng, T. (2023).
Taylor's law of fluctuation scaling for semivariances and higher moments of heavy tailed data, (PNAS November 16,2021)
Brown, M., Cohen, J.E., Tang, C-F., & Yam, S.C.P. (2021).
Privacy-preserving parametric inference: a case for robust statistics. Journal of the American Statistical Association, 116(534), 969-983.
Avella-Medina, M. (2021).
Heavy-tailed distributions, correlations, kurtosis, and Taylor’s law of fluctuation scaling. Proceedings of the Royal Society A 476:20200610.
J. E. Cohen, Richard A. Davis, Gennady Samorodnitsky (2020).
Robust estimation of superhedging prices. The Annals of Statistics, 49(1), 508-530
Obłój, J., & Wiesel, J. (2021).
Estimating causal effects in studies of human brain function: New models, methods and estimands. The annals of applied statistics, 14(1), 452.
Sobel, M. E., & Lindquist, M. A. (2020).
A note on the Screaming Toes game. arXiv preprint arXiv:2006.04805.
Tavaré, S. (2020).
Testing for stationarity of functional time series in the frequency domain. The Annals of Statistics, 48(5), 2505-2547.
Aue, A., & Van Delft, A. (2020).
Distinguishing cause from effect using quantiles: Bivariate quantile causal discovery. In International Conference on Machine Learning (pp. 9311-9323). PMLR.
Tagasovska, N., Chavez-Demoulin, V., & Vatter, T. (2020, November).
Large‐scale, image‐based tree species mapping in a tropical forest using artificial perceptual learning. Methods in Ecology and Evolution, 12(4), 608-618.
Tang, C., Uriarte, M., Jin, H., C Morton, D., & Zheng, T. (2021).
Optimal stopping and worker selection in crowdsourcing: An adaptive sequential probability ratio test framework. Statistica Sinica, 31(1), 519-546.
Li, X., Chen, Y., Chen, X., Liu, J., & Ying, Z. (2021)
Revisiting colocalization via optimal transport. Nature Computational Science, 1(3), 177-178.
Wang, S., & Yuan, M. (2021).
Multivariate rank-based distribution-free nonparametric testing using measure transportation. Journal of the American Statistical Association, (just-accepted), 1-45.
Deb, N., & Sen, B. (2021).
From Decoupling and Self-Normalization to Machine Learning
Victor H. de la Pena
Capacity-Achieving Sparse Superposition Codes via Approximate Message Passing Decoding
Cynthia Rush, Adam Greig, Ramji Venkataramanan
Slice Sampling on Hamiltonian Trajectories
John P. Cunningham, Benjamin Bloem-Reddy
Feature Augmentation via Nonparametrics and Selection (FANS) in High Dimensional Classification
Fan, J., Feng, Y., Jiang, J. and Tong, X.
Asset pricing with general transaction costs: Theory and numerics. Mathematical Finance, 31(2), 595-648.
Gonon, L., Muhle‐Karbe, J., & Shi, X. (2021).
Convergence to the mean-field game limit: a case study. The Annals of Applied Probability, 30(1), 259-286.
Nutz, M., San Martin, J., & Tan, X. (2020).
An asymptotic rate for the LASSO loss. In International Conference on Artificial Intelligence and Statistics (pp. 3664-3673). PMLR.
Rush, C. (2020, June).
Credit Risk, Liquidity, and Bubbles. International Review of Finance, 20(3), 737-746.
Jarrow, R., & Protter, P. (2020).
Neural clustering processes. In International Conference on Machine Learning (pp. 7455-7465). PMLR.
Pakman, A., Wang, Y., Mitelut, C., Lee, J., & Paninski, L. (2020, November).
Joint estimation of parameters in Ising model. The Annals of Statistics, 48(2), 785-810.
Ghosal, P., & Mukherjee, S. (2020).
Latent feature extraction for process data via multidimensional scaling. psychometrika, 85(2), 378-397.
Tang, X., Wang, Z., He, Q., Liu, J., & Ying, Z. (2020).
An Interaction-based Convolutional Neural Network (ICNN) Towards Better Understanding of COVID-19 X-ray Images. arXiv preprint arXiv:2106.06911.
Lo, S. H., & Yin, Y. (2021).
An adaptable generalization of Hotelling’s $ T^{2} $ test in high dimension. The Annals of Statistics, 48(3), 1815-1847.
Li, H., Aue, A., Paul, D., Peng, J., & Wang, P. (2020).
Self-Tuning Bandits over Unknown Covariate-Shifts. In Algorithmic Learning Theory (pp. 1114-1156). PMLR.
Suk, J., & Kpotufe, S. (2021, March).
A Joint MLE Approach to Large-Scale Structured Latent Attribute Analysis. Journal of the American Statistical Association, (just-accepted), 1-39.
Gu, Y., & Xu, G. (2021).
Bayesian statistics and modelling. Nature Reviews Methods Primers, 1(1), 1-26.
van de Schoot, R., Depaoli, S., King, R., Kramer, B., Märtens, K., Tadesse, M. G., ... & Yau, C. (2021).
On the bias and variance of odds ratio, relative risk and false discovery proportion. Communications in Statistics-Theory and Methods, 1-31.
Pang, G., Alemayehu, D., de la Peña, V., & Klass, M. J. (2020).
The continuous categorical: a novel simplex-valued exponential family. In International Conference on Machine Learning (pp. 3637-3647). PMLR.
Gordon-Rodriguez, E., Loaiza-Ganem, G., & Cunningham, J. (2020, November).
High-frequency analysis of parabolic stochastic PDEs. The Annals of Statistics, 48(2), 1143-1167.
Chong, C. (2020).
Count time series: A methodological review. Journal of the American Statistical Association, 1-15.
Davis, R. A., Fokianos, K., Holan, S. H., Joe, H., Livsey, J., Lund, R., ... & Ravishanker, N. (2021).
A Proxy Variable View of Shared Confounding. In International Conference on Machine Learning (pp. 10697-10707). PMLR.
Wang, Y., & Blei, D. (2021, July).
Topic-adjusted visibility metric for scientific articles. Ann. Appl. Stat. 10 (2016), no. 1, 1--31.
Linda S. L. Tan, Aik Hui Chan, and Tian Zheng
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