标题: 2000 姚期智 [打印本页] 作者: shiyi18 时间: 2022-4-17 16:35 标题: 2000 姚期智 Andrew C Yao
BIRTH:
1946, Shanghai, China
EDUCATION:
B.S. (Physics, National University of Taiwan, 1967); A.M. (Physics, Harvard University, 1969); Ph.D. (Physics, Harvard University, 1972); Ph.D. (Computer Science, University of Illinois Urbana-Champaign, 1975).
EXPERIENCE:
Assistant Professor (Mathematics Department, Massachusetts Institute of Technology, 1975-1976); Assistant Professor (Computer Science Department, Stanford University, 1976-1981); Professor (Computer Science Division, University of California, Berkeley, 1981-1982); Professor (Computer Science Department, Stanford University, 1982-1986); William and Edna Macaleer Professor of Engineering and Applied Science, (Princeton University, 1986-2004); Professor (Center for Advanced Study, Tsinghua University, from 2004); Director, Institute for Theoretical Computer Science, Tsinghua University, from 2004); Distinguished Professor-At-Large (The Chinese University of Hong Kong, from 2005).
HONORS AND AWARDS:
George Polya Prize (1987); Guggenheim Fellowship (1991); Fellow, Association for Computing Machinery (1995); Donald E. Knuth Prize (1996); Member, US National Academy of Sciences (1998), and American Academy of Arts and Sciences (2000), Academia Sinica (2000); A.M. Turing Award (2000); Pan Wen-Yuan Research Award (2003); Honorary Doctor of Science (City University of Hong Kong, 2003); Fellow, American Association for the Advancement of Science (2003); Honorary Doctor of Engineering (Hong Kong University of Science and Technology, 2004); Foreign Member, Chinese Academy of Sciences (2004); Alumni Award for Distinguished Service, College of Engineering, University of Illinois (2004); Honorary Doctor of Science (Chinese University of Hong Kong, 2006); Honorary Doctor of Mathematics (University of Waterloo, 2009); Fellow, International Association for Cryptologic Research (2010).
ANDREW CHI-CHIH YAO DL Author Profile link
China – 2000
CITATION
In recognition of his fundamental contributions to the theory of computation, including the complexity-based theory of pseudorandom number generation, cryptography, and communication complexity.
SHORT ANNOTATED
BIBLIOGRAPHY
RESEARCH
SUBJECTS
Andrew Chi-Chih Yao was born in Shanghai, China, on December 24, 1946. After moving with his family to Hong Kong for two years he immigrated to Taiwan. In 1967 he received a B.S. in Physics from the National University of Taiwan. He then started graduate studies in Physics at Harvard University, where he received an A.M. in 1969 and a Ph.D. in 1972 under the supervision of Sheldon Glashow, winner of the 1979 Nobel Prize in Physics. He subsequently entered the Ph.D. program in Computer Science at the University of Illinois Urbana-Champaign, and received his degree just two years later, in 1975. Yao completed his dissertation, A Study of Concrete Computational Complexity, under the supervision of Chung Laung Liu.
After a year as an Assistant Professor in the Mathematics Department at MIT, Yao joined the Computer Science Department at Stanford University as an Assistant Professor in 1976. Over the next five years there he made a number of fundamental contributions to the theory of algorithms.
His 1977 paper “Probabilistic computations: toward a unified measure of complexity,” [1] introduced what is now known as Yao’s min-max principle, which uses von Neumann’s minimax theorem from game theory to relate average-case complexity for deterministic algorithms to worst-case complexity for randomized algorithms. Yao proved that the expected running time of any randomized algorithm on worst-case input is equal to the average-case running time of any deterministic algorithm for the worst-case distribution of inputs. Yao’s principle has become a fundamental technique for reasoning about randomized algorithms and complexity, and has also been applied in areas such as property testing and learning theory.
Around this time Yao also made fundamental contributions to the theory of data structures. His 1978 paper, “Should tables be sorted?” [2] introduced the cell-probe model, an abstract model of data structures where the cost of a computation is measured by the total number of memory accesses. This model has been widely used in creating lower bound proofs of algorithms.
Yao spent a year as a Professor in the Computer Science Division of the University of California, Berkeley, and subsequently returned to Stanford as a full Professor in 1982. During the early 1980’s, Yao produced a number of papers which had a lasting impact on the foundations of cryptography, computer security, computational complexity and randomized computation. This work was significant not only for results obtained, but also for the introduction of problems, models and techniques which are now considered fundamental in their respective areas.
His 1981 paper with Danny Dolev, “On the security of public-key protocols,” [8] introduced a formal model for symbolic reasoning about security protocols. Since its introduction, this “Dolev-Yao model” has been the starting point for most work done on symbolic security, including recent work on the security of complexity-based cryptography, This continues to be an active area of research. Yao also made significant contributions to cryptography and complexity-based approaches to security. In 1982 he published “Theory and applications of trapdoor functions” [7] and “Protocols for secure computations” [5]. These works, which were introduced at the same conference, stand as seminal contributions in cryptography and secure computation.
The first of these papers addresses the then newly-emerging field of public-key cryptography from a theoretical perspective, lays the foundation for a theory of computational randomness, and initiates a study of its relationship to computational hardness. Yao provides a definition of pseudorandom number generator which is based on computational complexity, and proposes a definition of “perfect”—in current terminology, “pseudorandom”—probability distribution ensembles. (An ensemble is perfect if it cannot be distinguished from a truly random ensemble by any feasible distinguisher, where such distinguishers are formalized using the notion of a polynomial time randomized algorithm.) Yao relates his notion of pseudorandomness to the idea of a statistical test, a notion already used in the study of pseudorandom number generators, and shows that one particular test, known as the next-bit test, is adequate for characterizing pseudorandomness. Having defined perfect ensembles, Yao then defined a pseudorandom number generator as an efficient randomized algorithm which uses a limited number of truly random bits in order to output a sample from a perfect distribution whose size is polynomial in the number of random bits used.
The next fundamental contribution of the paper addresses the question of what computational assumptions are adequate for the existence of pseudorandom number generators. Advances in public-key cryptography indicated that secure encryption could be based on the assumed hardness of certain computational problems such as quadratic residuosity, or problems related to factoring integers. Yao asked whether one could make a general assumption about computational hardness which could be used to obtain pseudorandomness and hence, through standard techniques, cryptographic security. For this he formalized the notion of a one-way function that is easy to compute but hard to invert for a large fraction of inputs. He proved that one-way functions with certain properties may be used to construct pseudorandom number generators. This inspired a series of important results that refined Yao’s work, and it continues to be an area of active research. The contributions of this paper to pseudorandomness form an essential component of modern cryptography. In addition, the paper proposes a new field of computational information theory which refines Shannon’s theory by taking computational resources into account. Yao gives a definition of computational entropy, and uses it to give a characterization of encryption security. This definition of entropy is now important in areas such as leakage-resilient cryptography.
The second paper introduces a new paradigm for secure function evaluation, and introduces the famous “Millionaires’ Problem”. Yao gives a protocol which allows two parties, each holding a number, to determine who has the larger number without revealing the actual values. The Millionaires’ Problem is a two-party instance of a more general class of secure multiparty computation problems which are now essential to the study of secure cryptographic protocols. With the advent of wide-scale distributed computing and the ubiquity of cryptographic protocols, Yao’s contributions in this area have had a significant impact on networked computing.
In the 1980’s, Professor Yao introduced models and techniques whose ramifications are still being felt in research in complexity, computational randomness, cryptography, and security. Some of his most influential ideas were disseminated in lectures building on his published results. One example is the XOR-lemma, which uses computational hardness to produce pseudorandomness. Yao addressed whether the hardness of a problem may be amplified by combining multiple instances of the problem, in this case through the use of the bitwise exclusive-OR operation. While interesting in its own right, the XOR-lemma is an essential technique in the area of derandomization, which seeks generic methods for eliminating the need for randomness in the efficient solution of algorithmic problems. More generally, it helps determine whether certain classes of problems that are solved efficiently with randomization can instead be solved deterministically.
A second example is the garbled circuit technique, an important tool in secure multiparty computation which was used implicitly by Yao in his 1982 secure computation paper as well as in a 1986 paper “How to generate and exchange secrets” [6]. Recent advances in computing power have made the garbled circuit technique practical for large-scale computational problems, for example in privacy-preserving matching in DNA databases.
In 1986, Yao moved to Princeton University, where he became the William and Edna Macaleer Professor of Engineering and Applied Science. During this period he continued his work on the foundations of cryptography. He also built on previous work in areas such as decision tree and communication complexity. Yao made substantial contributions to the theory of lower bounds for algebraic decision trees, an area he established in a 1982 Journal of Algorithms paper [9] co-authored with J.M. Steele. This work exploited deep relationships between algebraic decision trees and mathematical results in algebraic geometry. He also investigated the use of randomization in decision trees. Professor Yao introduced the theory of communication complexity in a 1979 paper “Some complexity questions related to distributive computing” [3]. In his 1993 paper, “Quantum circuit complexity”[4] he extended communication complexity to quantum computing. Starting in the 1990’s, Professor Yao began to work extensively on quantum computing, communication and information theory. He continues to make significant contributions in these areas.
Andrew Yao became a Professor in the Center for Advanced Study and Director of the Institute for Theoretical Computer Science at Tsinghua University, Beijing, in 2004. Since 2005 he has also been Distinguished Professor-at-Large of the Chinese University of Hong Kong. His recent contributions include work in security protocols, universally composable secure computation, quantum computing, and the theory of algorithms.
Yao is active in graduate supervision, and has mentored over twenty Ph.D. students. He is married to Professor Frances Yao, a computer scientist and leading researcher in computational geometry, algorithms and cryptography.
工作经验。
助理教授（麻省理工学院数学系，1975-1976）；助理教授（斯坦福大学计算机科学系，1976-1981）；教授（加州大学伯克利分校计算机科学部，1981-1982）；教授（斯坦福大学计算机科学系，1982-1986）。William and Edna Macaleer工程和应用科学教授，（普林斯顿大学，1986-2004）；教授（清华大学高级研究中心，2004年起）；清华大学理论计算机科学研究所主任，2004年起）；特聘教授（香港中文大学，2005起）。
他在1977年发表的论文 "Probabilistic computations: toward a unified measure of complexity," [1]介绍了现在已知的姚氏最小-最大原则，该原则使用冯-诺伊曼博弈论中的最小-最大定理，将确定性算法的平均情况下的复杂性与随机算法的最坏情况下的复杂性联系起来。姚期智证明，任何随机算法在最坏情况下的预期运行时间都等于任何确定性算法在最坏情况下的平均运行时间。姚期智的原理已成为推理随机算法和复杂性的基本技术，并被应用于属性测试和学习理论等领域。
