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 semester:

  • Monday 8:45 - 10:15 am (holidays and week one excepted)
  • Tuesday 9:00 - 11:00 am
  • Wednesday 2:30 - 4:00 pm
During these hours, course-related 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.

Picture of Michael Shindler


This semester, Spring 2016, I am teaching the following courses. If you are enrolled in the course, you should have access to both Blackboard and Piazza. If you do not, please contact me by email ASAP.
  • CSCI 356 -- Piazza -- Introduction to Computer Systems
  • CSCI 170 -- Piazza -- Discrete Methods in Computer Science

Selected Papers

  • Streaming k-means on Well-Clusterable Data. With Vladimir Braverman, Adam Meyerson, Rafail Ostrovsky, Alan Roytman, and Brian Tagiku. In SODA, 2011. [ pdf ]
  • Fast and Accurate k-means for Large Datasets. With Adam Meyerson and Alex Wong. In NIPS, 2011. [ pdf ] [ code ]

Erdos Number

My Erdos number is 3:
  • I co-authored Streaming k-means on Well-Clusterable Data (SODA 2011) with Rafail Ostrovsky (and also with Vladimir Braverman, Adam Meyerson, Alan Roytman, and Brian Tagiku)
  • Rafail Ostrovsky co-authored The linear-array conjecture in communication complexity is false (STOC 1996) with Nathan Linial (and also with Eyal Kushilevitz)
  • Nathan Linial co-authored 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.