Home | Press | Publications | Teaching | Students | Talks | Conferences | Bio

Selected Talks

Turning Machine Learning Research into Products for Industry, Keynote at AI Conference, Beijing

Scaling Computer Vision in the Cloud, Fermilab

MLlib and Distributing the Singular Value Decomposition, Stanford University

Dimension Independent Matrix Square, MMDS 2014, UC Berkeley

The Libraries of Spark, Keynote at Data Science Bootcamp

MLlib and All-Pairs Similarity, University of Maryland

Distributed Computing with Spark, University of Maryland

Distributing Matrix Computations with Spark MLlib, Spark Meetup

Distributed Computing with Spark, eBay, Bay Area ACM

Towards a Principled Theory of Clustering, Carnegie Mellon University

Matrix Factorization and Spark, Codeneuro, San Francisco

Apache Spark in Four Parts, Raytheon

Spark Camp: An Introduction to Apache Spark with Hands-on Tutorials, Strata 2015

Dimension Independent Matrix Square using MapReduce, McGill University

Distributed Machine Learning on Spark, Toronto Hadoop User Group

The Three Dimensions of Scalable Machine Learning, Boston Spark Meetup

Advanced Data Science, Spark Summit 2015

Advanced Data Science, Toronto Apache Spark User Group

Hard Core Data Science, Strata NY 2015

Video Lectures

Advanced Data Science, one day class [video] [slides]

Machine Learning on Spark, Keynote at San Francisco Bay ACM [video]

Dimension Independent Similarity Computation using MapReduce, MMDS 2014 [video]

Introduction to Distributed Computing with Spark, San Francisco Bay ACM [video]

A Uniqueness Theorem for Clustering, CMU Machine Learning Lunch 2009 [video]

Supervised Clustering, NIPS 2011 [video]

Matrix Computations on Spark, CodeNeuro 2014 [video]

Approximation Algorithms Lecture (CME 305 at Stanford) [video]