Piotr Indyk
I am a Thomas D. and Virginia W. Cabot Professor in the Department of Electrical Engineering and Computer Science.
I am also a member of Theory of
Computation Group in
Computer Science and Artificial Intelligence Lab, Wireless@MIT, Big Data@CSAIL and MIFODS.
News:
MIT Institute for Foundations of Data Science (MIFODS) is organizing an overlay seminar.
Code:
Research Interests:
Highdimensional computational geometry (including approximate nearest neighbor search), data stream algorithms, sparse recovery, compressive sensing, machine learning.
Current students:
Past postdocs:
Past students:
Conference PCs and journal editorial boards:
 ICALP'17 (Program Committee Chair)
 SODA'15 (Program Committee Chair)
 SIAM Journal on Computing (20122014)
 IEEE Transactions on Signal Processing (20112013)
 SODA'11
(22nd ACMSIAM Symposium on Discrete Algorithms, San Francisco, CA)
 STOC'10 (42th ACM Symposium on Theory of Computing, Cambridge, MA)
 MADALGO 2007 Summer School on Data Stream Algorithms, Aarhus, Denmark.
 FOCS'07 (48th Annual Symposium on Foundations of Computer Science, Providence, RI)
 RANDOM'07, Princeton, NJ.
 ICALP'07 (34th International Colloquium on
Automata, Languages and Programming, Wroclaw, Poland)
 VLDB'07 (33rd International Conference on Very Large Data Bases, Vienna, Austria)
 STOC'06 (38th ACM Symposium on Theory of Computing, Seattle, WA)
 SIGMOD'06 (25th ACM SIGMOD International Conference on Management of Data, Chicago, IL)
 PODS'05
(24th ACM SIGMODSIGACTSIGART Symposium on Principles of Database Systems, Baltimore, MA)
 SODA'05
(16th ACMSIAM Symposium on Discrete Algorithms, Vancouver, Canada)
 KDD'04
(10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Seattle, WA)
 Workshop on Discrete Metric Spaces and Their Algorithmic Applications , Princeton, August 2023, 2003.
 Workshop on Approximate Nearest Neighbors Methods for Learning and Vision , at NIPS, Whistler, BC, Canada, December 2003.
 KDD'03
(9th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC)
 FOCS'02 (42nd Symposium on Foundations of Computer Science, Vancouver)
 SoCG'01
(17th ACM Symposium on Computational Geometry, Tufts U, Medford, MA)
Publications:
Here is a list of some of my papers.
Surveys, tutorials and talks:
 Recent Developments in the Sparse Fourier Transform , at ICASSP, 2015.
 Recent Developments in the Sparse Fourier Transform , at GlobalSIP, 2013.
 Sketching via Hashing: from Heavy Hitters to Compressive Sensing to Sparse Fourier Transform: slides and writeup, at PODS, 2013.
 Lectures on highdimensional near(est) neighbor search:
1
2
3
at MADALGO & CTIC Summer School on HIGHDIMENSIONAL GEOMETRIC COMPUTING, 2011.

Tutorial on Sparse Recovery Using Sparse Matrices, given at MMDS'10 and China Theory Week, 2010.

A survey on Sparse Recovery Using Sparse Matrices (with A. Gilbert), Proceedings of IEEE, 2010.

A talk on Sparse Recovery Using Sparse Matrices, given in various forms in various places.

A tutorial on Streaming, Sketching and Sublinear Space Algorithms, given at the 2009 Information Theory and Applications Workshop, San Diego, 2009.

A tutorial on Compressed Sensing (or Compressive Sampling or Linear Sketching), given at the
Workshop on Geometry and Algorithms, Princeton, 2008.
 A talk on Explicit constructions in highdimensional geometry, given at 2007 von Neumann Symposium on Sparse Representation and HighDimensional Geometry, Snowbird, 2007.
 An invited talk on Hashing, sketching and other randomized algorithms for highdimensional data", given at EMNLP'07
 Two lectures on algorithms for finding nearest neighbors in low and high dimensions, Summer School on Algorithmic Data Analysis, Helsinki, 2007.
 A tutorial on Lowdistortion embeddings and data structures, given at the Concentration Week on Metric Geometry and Geometric Embeddings of Discrete Metric Spaces, Texas A&M University, 2006.
 A talk on "NearOptimal Hashing Algorithms for Approximate Near(est) Neighbor Problem", given at MMDS'06: Workshop on Algorithms for Modern Massive Data Sets, Stanford, 2006.
 Approximation Algorithms for Embedding Problems, given at
Fast Manifold Learning Workshop, College of William and Mary, 2006.
 An invited talk on "Streaming Algorithms for Geometric Problems" at
CCCG'04,
FSTTCS'04 ,
FOCM'05 and
Sublinear Algorithms Workshop.
 A talk on Efficient Similarity Search in High Dimensions" that I gave at LEMS, Brown University, July 2004.
 An invited talk on "Embedded Stringology" at the Symposium on Combinatorial Pattern Matching (CPM 2004)".
 An invited talk on "Algorithmic Applications of LowDistortion Embeddings" at the Snowbird Learning Workshop 2004 .
 Two surveys for the upcoming 2nd edition of "CRC Handbook of Discrete and Computational Geometry":
"Nearest Neighbors in Highdimensional Spaces" and "Low Distortion Embeddings of Finite Metric Spaces" (with Jiri Matousek).
 An invited talk on Approximate Nearest Neighbor (Beyond the l_p norms) at the
International Workshop on Designing Tomorrow's CategoryLevel 3D Object Recognition Systems.

An invited talk
on "Approximate Algorithms for HighDimensional Geometric Problems" at the
DIMACS Workshop on Computational Geometry'02.

A tutorial at FOCS 2001 on "Algorithmic Aspects of Geometric Embeddings".

A short course on
"Nearest Neighbors and Other Problems in High Dimensional Computational Geometry" at AT&T during the summer of 1999.
Grad courses:
Fall 2017: Sketching Algorithms for Big Data (jointly with Jelani Nelson at Harvard).
Fall 2014: Algorithms and Signal Processing (6.893).
Spring 2013: Sublinear Algorithms (6.893).
Spring 2012: Geometric Computing (6.850).
Fall 2010: Sublinear Algorithms (6.896).
Spring 2009: Streaming Etc. (at Rice University).
Fall 2007: Sketching, Streaming, and Sublinear Space algorithms (6.895).
Spring 2007: Geometric Computation (6.850).
Fall 2006: Computational Biology, Too (6.895/6.085).
Fall 2005: Computational Biology (6.895/6.095).
Spring 2005: Geometric Computing (6.838) .
Fall 2003: Geometric Computing (6.838) .
Fall 2002: Algorithms for Massive Data Sets (6.897).
Fall 2001: Geometric Computation (6.838)
Fall 2000:
Algorithmic Aspects of Embeddings (6.978).
Projects:
Sparse Fourier Transform From Theory to Practice
Contact:
Piotr Indyk
MIT Computer Science and Artificial Intelligence Lab
Room G642
32 Vassar Street
Cambridge, Massachusetts 02139
Fax: (617) 2588682
email: indyk ατ theory.lcs.mit.edu