 High Performance Linear System Solvers with Focus on Graph Laplacians
 ITCS at SUFE, (June 2017, slides).
 NSF Algorithms in the Field PI meeting (Mar 2017).
 CSE 2017 (Feb 2017, titled "High Performance Solvers for Linear Systems in Graph Laplacians").
 Determinant Preserving Sparsification of SDDM Matrices with Applications to Counting and Sampling Spanning Trees
 Nanjing University, (May 2017, slides),
 Shanghai University of Finance and Economics, ITCS Seminar (May 2017).
 Resparsification of Graphs
 AlmostLinearTime Algorithms for Markov Chains and New Spectral Primitives for Directed Graphs
 Duke University Algorithms Seminar (Nov 2016, slides),
 UT Austin CS Theory Seminar (Oct 2016, titled "Directed Spectral Sparsification and Laplacian Solvers in Almost Linear Time").
 Parallel Graph Algorithms
 5th Workshop on Advances in Distributed Graph Algorithms (DISC 2016 workshop) (Sep 2016, slides).
 Algorithm Frameworks Based on Adaptive Sampling
 Banff International Research Station Workshop on Algebraic and Spectral Graph Theory (Aug 2016, slides),
 Park City Mathematics Institute Summer Session (July 2016),
 Shanghai Theory Day (June 2016),
 UC San Diego Workshop on Big Graphs (Jan 2016, titled "Algorithm Frameowrks Based on Structure Preserving Sampling"),
 UC Berkeley AMPLab Seminar (Oct 2015, titled "Algorithm Frameowrks Based on Structure Preserving Sampling"),
 Georgia Tech ARC Colloquium (Aug 2015, titled "Algorithm Frameowrks Based on Structure Preserving Sampling"),
 Carnegie Mellon University (May 2015, titled "Sampling: an Algorithmic Perspective").
 L_{p} Row Sampling by Lewis Weights
 NII Shonan Meeting (July 2016, slides),
 Georgia Tech ISYE Statstics Seminar (Sep 2015),
 IBM TJ Watson (Dec 2014),
 Simons Institute (Dec 2014, video).
 Sparsified Matrix Algorithms for Graph Laplacians
 Shanghai University of Finance and Economics, ITCS Seminar (June 2016, slides),
 UC Irvine Applied & Computational Mathematics Seminar (Mar 2016, titled "Sparsified Cholesky and Multigrid Solvers for Connection Laplacians"),
 Georgia Tech ACO Student Seminar (Jan 2016, titled "Sparsified Cholesky and Multigrid Solvers for Connection Laplacians"),
 Massachusetts Institute of Technology (Feb 2015, titled "Sampling from Gaussian Graphical Models via Spectral Sparsification" slides),
 Simons Institute (Oct 2014, titled "An Efficient Parallel Solver for SDD Linear Systems", slides, video),
 STOC 2014 (June 2014, titled "An Efficient Parallel Solver for SDD Linear Systems"),
 University of Waterloo (Jan 2014, titled "An Efficient Parallel Solver for SDD Linear Systems").
 Approximate Undirected Maximum Flows in O(m polylog(n)) Time
 SODA 2016 (Jan 2016),
 ISMP 2015 (July 2015),
 Brown University (Apr 2015, slides),
 Simons Institute (Dec 2014, video, titled "CutApproximators, Approximating Undirected Max Flows, and Recursion").

Multifaceted Algorithm Design
 University of WisconsinMadison (Mar 2015, slides),
 University of Toronto (Mar 2015),
 Simon Fraser University (Mar 2015),
 Duke University (Feb 2015),
 Georgia Institute of Technology (Feb 2015),
 University of Iowa (Jan 2015),
 University of Waterloo (Jan 2015),
 Tel Aviv University (Jan 2015).

Uniform Sampling for Matrix Approximation
 ITCS 2015 (Jan 2015, slides),
 FOCS 2013 (Oct 2013, titled "Iterative Row Sampling"),
 Brown University (Sep 2013, titled "Iterative Row Sampling",
slides),
 Massachusetts Institute of Technology (Sep 2013, titled "Iterative Row Sampling"),
 Carnegie Mellon University (Oct 2012, Feb 2013, titled "Iterative Approaches to Row Sampling").

Solving SDD Linear Systems in Nearly mlog^{1/2}n Time
 Massachusetts Institute of Technology (Sep 2014, slides),
 Carnegie Mellon University (April 2014, titled "Preconditioning in Expectation", slides).

Algorithm Design Using Spectral Graph Theory
 MaxPlanckInstitut für Informatik (July 2014, slides),
 ICERM, Brown University (April 2014, titled "Efficient Solvers for Linear Systems in Graph Laplacians"),
 University of Waterloo (Feb 2014),
 Microsoft Research New England (Nov 2013),
 thesis defense (Aug 2013),
 Microsoft Research Sillicon Valley (Jan 2013,
titled "Fast Regression Algorithms Using Spectral Graph Theory",
slides),
 Microsoft Research Redmond (Jan 2013,
titled "Fast Regression Algorithms Using Spectral Graph Theory"),
 Yale University (Sep 2012, titled "Image Processing Using Spectral Graph Theory"),
 Aarhus University (Aug 2012),
 University of Washington (Aug 2012),
 IBM TJ Watson (June 2012),
 Carnegie Mellon University (Dec 2011),
 University of Toronto (Nov 2011),
 Brown University (Nov 2011).

Approaching Optimality for Solving SDD Linear Systems
 Microsoft Research New England (Nov 2010, slides),
 University of Waterloo (Nov 2010),
 FOCS 2010 (Oct 2010),
 Carnegie Mellon University (Mar 2010, Oct 2010),