Talks/Slides

This page includes only some of the selected talks and is updated infrequently.

Videos

Reliable Statistical Inference for High-Dimensional Models, IMS Tweedie Award Lecture, 2020. [Slides], [Link to talk]

Analysis of two-layer neural networks via displacement convexity, Kavli Institute, UC Santa Barbara, 2019

Flexible Framework for Hypothesis Testing in High-Dimensions, Simons Institute for Theory of Computing, 2018.

Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions, Google Research, New York, 2018.

Reasoning about Uncertainty in High-dimensional Data Analysis, University of Washington, Seattle, 2014.

Precise Tradeoffs in Adversarial Training for Linear Regression

Statistical Inference for High-Dimensional Models

Analysis of two-layer neural networks via displacement convexity

Rough Landscapes: From Physics to Algorithms, Kavli Institute for Theoretical Physics, 2019 (invited)
Wilks seminar in Statistics, Princeton ORFE, 2019 (invited)
“Sparsity, Randomness, and Optimization” Session at the AMS Sectional Meeting, University of Hawaii, 2019 (invited)
International Conference on Continuous Optimization (ICCOPT), Berlin, Germany, 2019 (invited)
INFORMS Annual Meeting, Seattle, WA, 2019 (invited)
Invited talk at Institute for Outlier Research (iORB) mini-conference, USC Marshall, December 2019.

A Flexible Framework for Hypothesis Testing in High-Dimensions

Simons Institute for the Theory of Computing (Foundations of Data Science Program), 2018 (invited)
Information Theory and Applications Workshop (ITA), 2018 (invited)
Conference on Information Sciences and Systems (CISS), Princeton, 2018 (invited)

Dynamic Incentive-Aware Learning: Robust Pricing in Contextual Auctions

Invited talk at ISE seminar, University of Southern California, October 2020
Invited talk at IEOR/DRO seminar, Columbia University, October 2020
Conference on Neural Information Processing Systems, Vancouver, Canada, 2019 [Slides]
INFORMS Annual Meeting, Seattle, WA, 2019 (invited)
Simons Institute for the Theory of Computing (Foundations of Data Science Program), 2018 (invited)
Google Research, New York, 2018 (invited)
MIT Stochastics and Statistics Seminar, 2018 (invited)

Dynamic Pricing in High-dimensions

Online Control of False Discovery Rate

10th International Conference on Multiple Comparison Procedures, 2017 (invited)
Probability and Statistics seminar, Math Department, University of Southern California, Jan 2017
INFORMS Annual Meeting, Nashville, TN, Nov 2016 (invited)
Joint Statistical Meetings, Seattle, Aug 2015 (invited)
Statistical Learning and Data Science Conference, University of North Carolina, Chapel Hill, June 2016 (invited).

Phase Transitions in Semidefinite Programming

CommNetS Seminar, Electrical Engineering Department, University of Southern California, Jan 2016 (invited)

Extracting Biomedical Relationships from Unstructured Documents

Debiasing the Lasso: Optimal Sample Size for Gaussian Designs [Slides]

Symposium on Sparse Modeling and Its Applications, UCLA, Statistics department, Oct 2015 (invited)

Nearly Optimal Sample Size in Hypothesis Testing for High-Dimensional Regression [Slides]

AIM workshop on Inference in High-Dimensional Regression, Palo Alto, 2015 (invited)
Allerton Conference on Communication, Control, and Computing, 2013

Reasoning about Uncertainty in High-Dimensional Statistics [Slides]

AIM workshop on Inference in High-Dimensional Regression, Palo Alto, Jan 2015 (invited talk)
UC Berkeley, NCD Seminar, Nov 2014 (invited)
Massachusetts Institute of Technology (MIT), Mar 2014 (invited)
University of California, Los Angeles (UCLA), Mar 2014 (invited)
Princeton University, Feb 2014 (invited)
University of California, San Diego (UCSD), Feb 2014 (invited)
University of Washington, Feb 2014 (invited)
Microsoft Research, NYC, Feb 2014 (invited)
Wharton School of the University of Pennsylvania, Feb 2014 (invited)
Yale University, Feb 2014 (invited)
University of Southern California (USC), Jan 2014 (invited)
Microsoft Research, Silicon Valley, Jan 2014 (invited)
ISE seminar, University of Illinois at Urbana-Champaign, 2013 (invited)
INFORMS annual meeting, Minneapolis, MN, 2013 (invited)

Learning Linear Bayesian Networks with Latent Variables [Slides]

Information-Theoretically Optimal Compressed Sensing via Spatial Coupling and Approximate Message Passing [Slides]

IEEE Int. Symposium on Information Theory (ISIT), 2012
Asilomar Conference on Signals, Systems, and Computers (invited), 2012
Communications/ICWS seminar, University of illinois at Urbana-Champaign (invited), 2013
Information Theory Forum, Stanford, 2013
University of Southern California (USC), Jan 2014 (invited talk)

Subsampling at Information Theoretically Optimal Rates [Slides]

Minimax Risk of Truncated Series Estimators over Symmetric Convex Polytopes [Slides]

Localization from Incomplete Noisy Distance Measurements [Slides] [Video]