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Congratulations to Daiki Tagami on winning the 2022 Columbia College Leadership and Excellence Award (LEA) for Innovation & Enhancement
Congratulations to Daiki Tagami on winning the 2022 Columbia College Leadership and Excellence Award (LEA) for Innovation & Enhancement

Daiki Tagami Wins the 2022 Columbia College Leadership and Excellence Award (LEA) for Innovation & Enhancement

Daiki’s selection as an honoree is a testament to the outstanding impact he’s had on his peers, the campus, and other communities he has served....

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Congratulations to Zhiliang Ying on being selected as one of the 2021 AERA Fellows
Congratulations to Zhiliang Ying on being selected as one of the 2021 AERA Fellows

Dr. Zhiliang Ying is an internationally renowned statistician whose scholarship has shaped the application of statistics to educational and psychological measurement....

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In Memoriam | Y. S. Chow (1924 - 2022)
In Memoriam | Y. S. Chow (1924 – 2022)

Yuan Shih Chow (1924–2022)

Yuan Shih Chow, Professor Emeritus of Statistics at Columbia University, passed away on March 3, 2022 in his hometown in Hubei, China....

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Congratulations to Alejandra Quintos on winning the audience’s favorite at the Three-Minute Thesis (3MT) competition.
Congratulations to Alejandra Quintos on winning the audience’s favorite at the Three-Minute Thesis (3MT) competition.

Congratulations to Alejandra Quintos on winning the audience’s favorite at the Three-Minute Thesis (3MT) competition.

GSAS doctoral student Alejandra Quintos, a sixth-year PhD candidate in Statistics, won Audience Choice for her presentation Using Mathematics to Help Impoverished Women, via Microlending....

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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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Recent Faculty Publications

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).
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).
Robust estimation of superhedging prices. The Annals of Statistics, 49(1), 508-530
Obłój, J., & Wiesel, J. (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)
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).
Revisiting colocalization via optimal transport. Nature Computational Science, 1(3), 177-178.
Wang, S., & Yuan, M. (2021).
From Decoupling and Self-Normalization to Machine Learning
Victor H. de la Pena
Stabilized Sparse Online Learning for Sparse Data
Yuting Ma, Tian Zheng
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.
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
Asset pricing with general transaction costs: Theory and numerics. Mathematical Finance, 31(2), 595-648.
Gonon, L., Muhle‐Karbe, J., & Shi, X. (2021).
An asymptotic rate for the LASSO loss. In International Conference on Artificial Intelligence and Statistics (pp. 3664-3673). PMLR.
Rush, C. (2020, June).
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).
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).
A Proxy Variable View of Shared Confounding. In International Conference on Machine Learning (pp. 10697-10707). PMLR.
Wang, Y., & Blei, D. (2021, July).
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).
High-frequency analysis of parabolic stochastic PDEs. The Annals of Statistics, 48(2), 1143-1167.
Chong, C. (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).
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).
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).
Self-Tuning Bandits over Unknown Covariate-Shifts. In Algorithmic Learning Theory (pp. 1114-1156). PMLR.
Suk, J., & Kpotufe, S. (2021, March).
Credit Risk, Liquidity, and Bubbles. International Review of Finance, 20(3), 737-746.
Jarrow, R., & Protter, P. (2020).
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).
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).
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).
Joint estimation of parameters in Ising model. The Annals of Statistics, 48(2), 785-810.
Ghosal, P., & Mukherjee, S. (2020).
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).
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).
Boosted Sparse Non-linear Distance Metric Learning
Yuting Ma and Tian Zheng
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