Michael Sipser

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Michael Sipser
MIT-Science Sipser Michael.jpg
Born
Michael Fredric Sipser

(1954-09-17) September 17, 1954 (age 70)
Brooklyn, New York
Nationality American
Alma mater
Awards
Scientific career
Fields
Institutions MIT
Thesis Nondeterminism and the Size of Two-Way Finite Automata  (1980)
Doctoral advisor Manuel Blum
Doctoral students
Website math.mit.edu/~sipser/

Michael Fredric Sipser (born September 17, 1954) is an American theoretical computer scientist who has made early contributions to computational complexity theory. He is a professor of applied mathematics and was the dean of science at the Massachusetts Institute of Technology.

Contents

Biography

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] [2]

He joined MIT's Laboratory for Computer Science as a research associate in 1979 and then was a Research Staff Member at IBM Research in San Jose. In 1980, he joined the MIT faculty. He spent the 1985–1986 academic year on the faculty of the University of California at Berkeley and then returned to MIT. From 2004 until 2014, he served as head of the MIT Mathematics department. He was appointed Interim Dean of the MIT School of Science in 2013 and Dean in 2014. [3] He served as Dean until 2020, when he was followed by Nergis Mavalvala. [4] He is a fellow of the American Academy of Arts and Sciences. [5] In 2015 he was elected as a fellow of the American Mathematical Society "for contributions to complexity theory and for leadership and service to the mathematical community." [6] He was elected as an ACM Fellow in 2017. [7]

Scientific career

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 B. Saxe. [8] Their result was later improved to be an exponential lower bound by Andrew Yao and Johan Håstad. [9]

In an early derandomization theorem, Sipser showed that BPP is contained in the polynomial hierarchy, [10] subsequently improved by Peter Gács and Clemens Lautemann to form what is now known as the Sipser-Gács-Lautemann theorem. Sipser also established a connection between expander graphs and derandomization. [11] He and his PhD student Daniel Spielman introduced expander codes, an application of expander graphs. [12] With fellow graduate student David Lichtenstein, Sipser proved that Go is PSPACE hard. [13]

In quantum computation theory, he introduced the adiabatic algorithm jointly with Edward Farhi, Jeffrey Goldstone, and Samuel Gutmann. [14]

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. [15]

Notable books

Sipser is the author of Introduction to the Theory of Computation , [16] a textbook for theoretical computer science.

Personal life

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 graduated from MIT. [1]

Related Research Articles

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<span class="mw-page-title-main">Quantum computing</span> Technology that uses quantum mechanics

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<span class="mw-page-title-main">Leonard Adleman</span> American computer scientist

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<span class="mw-page-title-main">Manuel Blum</span> Venezuelan computer scientist

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In quantum computing, a quantum algorithm is an algorithm that runs on a realistic model of quantum computation, the most commonly used model being the quantum circuit model of computation. A classical algorithm is a finite sequence of instructions, or a step-by-step procedure for solving a problem, where each step or instruction can be performed on a classical computer. Similarly, a quantum algorithm is a step-by-step procedure, where each of the steps can be performed on a quantum computer. Although all classical algorithms can also be performed on a quantum computer, the term quantum algorithm is generally reserved for algorithms that seem inherently quantum, or use some essential feature of quantum computation such as quantum superposition or quantum entanglement.

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In computational complexity theory, an Arthur–Merlin protocol, introduced by Babai (1985), is an interactive proof system in which the verifier's coin tosses are constrained to be public. Goldwasser & Sipser (1986) proved that all (formal) languages with interactive proofs of arbitrary length with private coins also have interactive proofs with public coins.

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In computational complexity theory, the Sipser–Lautemann theorem or Sipser–Gács–Lautemann theorem states that bounded-error probabilistic polynomial (BPP) time is contained in the polynomial time hierarchy, and more specifically Σ2 ∩ Π2.

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References

  1. 1 2 "Michael Sipser named dean of the School of Science". MIT News | Massachusetts Institute of Technology. 2014-06-05. Retrieved 2024-09-20.
  2. ↑ Michael Sipser at the Mathematics Genealogy Project
  3. ↑ MIT Mathematics | People Directory Archived 2008-12-18 at the Wayback Machine
  4. ↑ "School of Science | MIT History" . Retrieved 2020-08-25.
  5. ↑ "Membership". American Academy of Arts and Sciences. Retrieved 23 September 2014.
  6. ↑ 2016 Class of the Fellows of the AMS, American Mathematical Society , retrieved 2015-11-16.
  7. ↑ ACM Recognizes 2017 Fellows for Making Transformative Contributions and Advancing Technology in the Digital Age, Association for Computing Machinery, December 11, 2017, retrieved 2017-11-13
  8. ↑ Furst, Merrick; Saxe, James B.; Sipser, Michael (1984). "Parity, circuits, and the polynomial-time hierarchy". Mathematical Systems Theory. 17 (1): 13–27. doi:10.1007/BF01744431. MR   0738749. S2CID   14677270.
  9. ↑ "Research Vignette: Hard Problems All The Way Up | Simons Institute for the Theory of Computing". simons.berkeley.edu. 30 July 2015. Retrieved 2015-09-17.
  10. ↑ Sipser, Michael (1983). "A complexity theoretic approach to randomness". Proceedings of the 15th ACM Symposium on Theory of Computing.
  11. ↑ Sipser, Michael (1986). "Expanders, randomness, or time versus space". Structure in Complexity Theory: Proceedings of the Conference held at the University of California, Berkeley, June 2-5, 1986. Lecture Notes in Computer Science. Vol. 223. pp. 325–329. doi:10.1007/3-540-16486-3_108. ISBN   978-3-540-16486-9.
  12. ↑ Sipser, Michael; Spielman, Daniel (1996). "Expander Codes" (PDF). IEEE Transactions on Information Theory. 42 (6): 1710–1722. doi:10.1109/18.556667.
  13. ↑ 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. S2CID   29498352.
  14. ↑ Farhi, Edward; Goldstone, Jeffrey; Gutmann, Sam; Sipser, Michael (2000-01-28). "Quantum Computation by Adiabatic Evolution". arXiv: quant-ph/0001106 .
  15. ↑ Pavlus, John (2012-01-01). "Machines of the Infinite". Scientific American. 307 (3): 66–71. Bibcode:2012SciAm.307c..66P. doi:10.1038/scientificamerican0912-66. PMID   22928263.
  16. ↑ Sipser, Michael (2012-06-27). Introduction to the Theory of Computation (3 ed.). Cengage Learning. ISBN   978-1133187790.
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