Michael Shindler
I am a lecturer at the University of Southern California.
Office: SAL 204
I plan to be in or near my office the following weekly hours during the Fall semester:
 Monday 11:30  12:30
 Tuesday 10:30  12:00
 Wednesday 9:30  11:00
During these hours, courserelated material will have priority over other items. As always, I am happy to make private appointments to meet with students as needed.
To form my email address, concatenate my last name with [at] usc [dot] edu
My recent research focuses primarily on educational issues in computer science; in the past, my work touched on computations on large datasets, machine learning, approximation algorithms, streaming algorithms, and data mining.


Teaching
In Fall, I will be teaching:
 CSCI 170  Discrete Methods in Computer Science
 To acquire the textbook:
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 CSCI 356  Introduction to Computer Systems
 The textbook is Randal E. Bryant and David R. O’Hallaron, Computer Systems: A Programmer’s Perspective, Third Edition (CS:APP3e), Pearson, 2016.

Please make sure you have the Third Edition, not the Second Edition.
 CSCI 567  Machine Learning
 I am doing four discussions sections

Selected Papers
 Streaming kmeans on WellClusterable Data. With Vladimir Braverman, Adam Meyerson, Rafail Ostrovsky, Alan Roytman, and Brian Tagiku. In SODA, 2011. [ pdf ]
 Fast and Accurate kmeans for Large Datasets. With Adam Meyerson and Alex Wong. In NIPS, 2011. [ pdf ] [ code ]

Erdos Number
My Erdos number is 3:
 I coauthored Streaming kmeans on WellClusterable Data (SODA 2011) with Rafail Ostrovsky (and also with Vladimir Braverman, Adam Meyerson, Alan Roytman, and Brian Tagiku)
 Rafail Ostrovsky coauthored The lineararray conjecture in communication complexity is false (STOC 1996) with Nathan Linial (and also with Eyal Kushilevitz)
 Nathan Linial coauthored Extremal problems on permutations under cyclic equivalence (Discrete Math, 1987) with Paul Erdos (and also with Shlomo Moran)
I would like to thank the American Mathematical Society's collaboration distance calculator for providing me with an easy way to determine this.

Educational Background

PhD in Computer Science from UCLA, 2011
Advisor: Adam Meyerson

Master of Science in Computer Science from UCLA, 2008
Advisor: Adam Meyerson

Bachelor of Science in Information and Computer Science from UC Irvine, 2005.
