Michael Sipser

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Michael Fredric Sipser (born September 17, 1954) is a theoretical computer scientist who has made early contributions to computational complexity theory. He is a professor of Applied Mathematics and Dean of Science at the Massachusetts Institute of Technology.


Sipser was born and raised in Brooklyn, New York and moved to Oswego, New York when he was 12 years old. He earned his BA in mathematics from Cornell University in 1974 and his PhD in engineering from the University of California at Berkeley in 1980 under the direction of Manuel Blum.[1]

He joined MIT's Laboratory for Computer Science as a research associate in 1979 and became an MIT professor the following year. From 2004 until 2014, he served as head of the MIT Mathematics department. He was appointed Dean of the MIT School of Science in 2014.[2] He is a fellow of the American Academy of Arts and Sciences.[3]

Scientific career[edit]

Sipser specializes in algorithms and complexity theory, specifically efficient error correcting codes, interactive proof systems, randomness, quantum computation, and establishing the inherent computational difficulty of problems. He introduced the method of probabilistic restriction for proving super-polynomial lower bounds on circuit complexity in a paper joint with Merrick Furst and James Saxe.[4] Their result was later improved to be an exponential lower bound by Andrew Yao and Johan Håstad.[5]

In an early derandomization theorem, Sipser showed that BPP is contained in the polynomial hierarchy,[6] subsequently improved by Peter Gács and Clemens Lautemann to form what is now known as the Sipser-Gàcs-Lautemann theorem. Sipser also established a connection between expander graphs and derandomization.[7] He and his PhD student Daniel Spielman introduced expander codes, an application of expander graphs.[8] With fellow graduate student David Lichtenstein, Sipser proved that Go is PSPACE hard.[9]

In quantum computation theory, he introduced the adiabatic algorithm jointly with Edward Farhi, Jeffrey Goldstone, and Samuel Gutmann.[10]

Sipser has long been interested in the P versus NP problem. In 1975, he wagered an ounce of gold with Leonard Adleman that the problem would be solved with a proof that P≠NP by the end of the 20th century. Sipser sent Adleman an American gold eagle coin in 2000 because the problem remained (and remains) unsolved.[11]

Notable books[edit]

Sipser is the author of Introduction to the Theory of Computation,[12] a textbook for theoretical computer science.

Personal life[edit]

Sipser lives in Cambridge, Massachusetts with his wife, Ina, and has two children: a daughter, Rachel, who graduated from New York University, and a younger son, Aaron, who is an undergraduate at MIT.[1]


  1. ^ a b Trafton, Anne, "Michael Sipser named dean of the School of Science: Sipser has served as interim dean since Marc Kastner’s departure", MIT News Office, June 5, 2014
  2. ^ MIT Mathematics | People Directory
  3. ^ "Membership". American Academy of Arts and Sciences. Retrieved 23 September 2014. 
  4. ^ Furst, Merrick; Saxe, James B.; Sipser, Michael (1984-12-01). "Parity, circuits, and the polynomial-time hierarchy". Mathematical systems theory 17 (1): 13–27. doi:10.1007/BF01744431. ISSN 0025-5661. 
  5. ^ "Research Vignette: Hard Problems All The Way Up | Simons Institute for the Theory of Computing". simons.berkeley.edu. Retrieved 2015-09-17. 
  6. ^ Sipser, Michael (1983). "A complexity theoretic approach to randomness". Proceedings of the 15th ACM Symposium on Theory of Computing. 
  7. ^ Sipser, Michael (1986). "Expanders, Randomness, or Time versus Space". Proceedings of the Conference on Structure in Complexity. 
  8. ^ Sipser, Michael; Spielman, Daniel (1996). "Expander Codes" (PDF). IEEE Transactions on Information Theory 42 (6): 1710–1722. 
  9. ^ Lichtenstein, David; Sipser, Michael (1980-04-01). "GO Is Polynomial-Space Hard". J. ACM 27 (2): 393–401. doi:10.1145/322186.322201. ISSN 0004-5411. 
  10. ^ Farhi, Edward; Goldstone, Jeffrey; Gutmann, Sam; Sipser, Michael (2000-01-28). "Quantum Computation by Adiabatic Evolution". arXiv:quant-ph/0001106. 
  11. ^ Pavlus, John (2012-01-01). "Machines of the Infinite". Scientific American 307 (3). doi:10.1038/scientificamerican0912-66. 
  12. ^ Sipser, Michael. Introduction to the Theory of Computation (3 ed.). Cengage Learning. ISBN 978-1133187790. 

External links[edit]