If you happen to look at my presentation slides or papers and see some typos or have questions, feel free to email me. I am very interested to know about them.:)
Quick links:
Presentation slides on my research:
 Modewise methods for tensor dimension reduction, Online Asymptotic Geometric Analysis Seminar, 06/2020, video of the talk
 Sketching for Motzkin's method, Asilomar conference, 11/2019
 Iterative linear solvers and random matrices: Block Gaussian sketch and project method, SOCAMS, 02/2019
 Constructive regularization of the random matrix norm, GeorgiaTech, 03/2019
 Regularization of the random matrix norm: local and global obstructions, NYU, 03/2017
 Coverings of random ellipsoids, and invertibility of matrices with i.i.d. heavytailed entries, AMS, 03/2016
Invited research talks:
 June 2020
 Online Asymptotic Geometric Analysis Seminar, List of abstracts
 April 2020
 Graduate Seminar California State University Channel Islands, online
 November 2019
 Combinatorics and Probability seminar, UCIrvine, CA Abstract
 November 2019
 Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA
 October 2019
 Probability seminar, Stanford, CA Abstract
 October 2019
 Probability seminar, USC, CA List of abstract
 March 2019
 Highdimensional seminar, GeorgiaTech, Atlanta, GA Abstract
 March 2019
 University of Alberta, Edmonton, Canada
 February 2019
 Southern California Applied Mathematics Symposium, Caltech, Pasadena, CA List of abstracts
 September 2018
 Structural Inference in HighDimensional Models worksop, HSE, Moscow, Russia Abstract
 August 2018
 SUMIFRAS workshop, TAMU University, College Station, TX Abstract
 June 2017
 Probability seminar, UniversiteParisEst MarnelaVallee, France Abstract
 June 2017
 Probability seminar, University of Alberta, Edmonton, Canada
 May 2017
 Probability seminar, Universite Paris Diderot, France Abstract
 March 2017
 MIC seminar, Center for Data Science, NYU, New York Abstract
 June 2016
 CMS Summer Sectional Meeting University of Alberta, Edmonton, Canada Abstract
 March 2016
 AMS Spring Southeastern Sectional Meeting University of Georgia, Athens, GA Abstract
Expository Machine Learning talks at Berkeley Lab:
In July and August 2017 I led an introductory learning seminar in Machine Learning at Berkeley Lab.
The majority of the material that we covered was based on the slides and literature for this Stanford
class.
Some additional materials I prepared for the convenience of presentation:
 Unsupervised learning techniques: beyond clustering and PCA

Slides
 Regularizations in linear regression: ridge, lasso, bridge, elastic net etc

Handwritten notes
Random matrices reading seminar at UCLA:
Since January 2019, I coorganize Random matrices reading seminar with Palina Salanevich.
Topics included:
 Uncertainty principles on graphs (Winter term 2019)
 Mathematics of neural networks (Spring term 2019)
 Delocalization of eigenvectors of random matrices and graphs (Fall 2019, Reading list)
Some (old) expository talks:
 (January 2017) Structured Random Matrices tutorial (on Ramon van Handel's survey)
 Analysis/Probability Learning Seminar,
abstracts: Part 1 and
Part 2
 (September 2016) Matrix regularizing effects of Gaussian perturbations
 On Aizenman, Peled, Schenker, Shamis and Sodin's paper. Analysis/Probability Learning Seminar,
abstract
 (October 2015) Geometric random walks
 Short exposition of Santosh Vempala survey. Student Analysis Seminar,
abstract
 (March 2015) The smallest singular value of random rectangular matrices with no moment assumptions on entries
 On Konstantin Tikhomirov's paper.
Analysis/Probability Learning Seminar,
abstract
 (March 2015) Small ball probabilities and an introduction to the LittlewoodOfford problem
 Student Analysis Seminar,
abstract
 (November 2014) Cube slicings in R^n
 Student Analysis Seminar,
abstract
Geometric analysis reading seminar at UMichigan:
During 2014 and 2015, I gave several of talks on Geometric analysis reading seminar
(topics included: contact points and John's theorem; Milman's quotient of subspace theorem
and BourgainMilman inequality; Paourisâ€™ deviation inequality, BanachMazur distance to the cube estimates)