Michael Fredric Sipser was born on September 17, 1954. He is an American computer scientist who studied how computers solve problems and how long it takes them to do so. He is a professor of applied mathematics and previously served as the dean of science at the Massachusetts Institute of Technology.
Biography
Michael Sipser was born and raised in Brooklyn, New York. When he was 12 years old, he moved to Oswego, New York. His grandparents were Jewish immigrants from Eastern Europe, and his father was a professor of mathematics at SUNY Oneonta. He received his BA in mathematics from Cornell University in 1974 and his PhD in engineering from the University of California at Berkeley in 1980. His PhD advisor was Manuel Blum.
In 1979, he began working as a research associate at MIT's Laboratory for Computer Science. Later, he worked as a Research Staff Member at IBM Research in San Jose, California. In 1980, he became a professor at MIT. He taught at the University of California at Berkeley during the 1985–1986 academic year before returning to MIT. From 2004 to 2014, he led the MIT Mathematics department. In 2013, he was named Interim Dean of the MIT School of Science and became Dean in 2014. He held this position until 2020, when Nergis Mavalvala took over.
Sipser is a fellow of the American Academy of Arts and Sciences. In 2015, he was elected a fellow of the American Mathematical Society for his work in complexity theory and for his leadership in the mathematical community. He was also named an ACM Fellow in 2017.
Scientific career
Michael Sipser focuses on computer science topics such as algorithms, complexity theory, efficient error-correcting codes, interactive proof systems, randomness, quantum computation, and the difficulty of solving problems. He developed a method called probabilistic restriction to show that certain problems require very complex solutions in a paper he wrote with Merrick Furst and James B. Saxe. Later, Andrew Yao and Johan Håstad improved this result to show even higher complexity limits.
In an early study about reducing randomness in computing, Sipser proved that a class of problems called BPP is part of the polynomial hierarchy. This idea was later refined by Peter Gács and Clemens Lautemann, forming the Sipser–Gács–Lautemann theorem. Sipser also connected expander graphs to reducing randomness in algorithms. He and his PhD student Daniel Spielman created expander codes, which use expander graphs. With another graduate student, David Lichtenstein, Sipser showed that the game Go is as hard as the PSPACE class of problems.
In quantum computing, Sipser helped develop the adiabatic algorithm with Edward Farhi, Jeffrey Goldstone, and Samuel Gutmann.
Sipser has studied the P versus NP problem for many years. In 1975, he bet an ounce of gold with Leonard Adleman that a proof showing P ≠ NP would be found by the end of the 20th century. In 2000, Sipser sent Adleman an American Gold Eagle coin because the problem remained unsolved.
Notable books
Michael Sipser wrote a book called Introduction to the Theory of Computation. This book is about the study of how computers work and solve problems.
Personal life
Sipser lives in Cambridge, Massachusetts, with his wife, Ina. He has two children: a daughter named Rachel, who graduated from New York University, and a younger son named Aaron, who graduated from MIT.