Shige Peng

Character introduction

Shige Peng, graduated in the School of Physics at Shandong University in 1974 and he was awarded 3rd-phase doctor’s degree of 《Mathematics and Automatics》 at Paris IX in France. In 1986 he was awarded another doctor’s degree of 《Applied Mathematics》 at Provence University in France. Then he served as a post-doctor in Fudan University during 1988-1989. He was provided with French "leading research qualification" in 1992 and was elected as academician of Chinese Academy of Sciences in 2005. His seminal contributions in his scientific research are:
1. He is a founder of the theory of Backward Stochastic Differential Equations (BSDE): His 1990 paper, coauthored with Pardoux, is considered as a “founder paper” (see [F001]) .
2. He has established a nonlinear Feynman-Kac formula.How to generalize the classical Feynman-Kac formula to nonlinear situationswas a fundamental and longtime standing problem.
3. He has established general stochastic maximum principle in stochastic optimal control theory. This was considered as one of “two major advances in the last two decades”in this domain.
4. He has established and developeda powerful and elegant nonlinear expectationtheory: The first dynamic consistent nonlinear expectation in general sense was introduced by Peng (1997). This will provided a strong foundation for realizing his longtime objective of nonlinear probability theory.
Peng was invited to give series of lectures in Beijing University, Oxford University, Princeton University, Osaka University, Ecole Polytechnique de Paris, ETH, Institute of Henry Poincare.
Peng was invited to give Plenary lecture in ICM 2010. He was also invited to give Plenary lecture in the 8th ICIAM conference.
Peng’s research achievements let him obtain: Scientific and Technology Prize of Education Committee of China, 1994; National Natural Science Prize, 1995; Top Scientific and Technology Prize of Shandon, 2003; The first Su Buchin Applied Mathematics Prize, 2006; Prize for Scientific and Technological Progress of Ho Leung Ho Lee Foundation, 2007; TAN Kah Kee Science Award, 2008; Hua Loo-Keng Mathematics Award, 2011.Qiu Shi Science and Technology Prize, 2016.

Topic: Nonlinear Theory of Prediction

Abstract  In recent 20 years, the speed of developments of technology and science changes  becomes very high in large dada, real-time communications, propagation. A very interesting and challenging problem is: can we still apply the classical prediction theory and methodology to predict our future and make decisions base on the these predictions? Our recent fundamental research results indicates us that a the classical scientific prediction theory already becomes so fragile that we  need to have a dramatical changes. In fact, a nonlinear theory of mathematical expectations has been developed. Based on this new and strong robust. In this talk I give a brief but very illustrative introduction of this new and nonlinear theory of prediction.  
KEY WORDS: nonlinear expectation theory, worst case prevention, robust central limit theorem, maximal distribution, nonlinear Brownian motions, forward and backward calculus.  

REFERENCES
1.Nobel Lecture: Uncertainty Outside and Inside Economic Models, Journal of Political      Economy, 2014, vol. 122, no. 5
2.S. Peng, Nonlinear expectations and stochastic calculus under uncertainty, Springer 2019.
3.Peng,S.:G–Expectation,G–Brownian Motion and Related Stochastic Calculus of Itô’s type. In: Benth, et al. (eds.) The Abel Symposium 2005, Abel Symposia, pp. 541–567. Springer (2007)
4.Kolmogorov, A.N.: Foundations of the Theory of Probability. Chelsea (1956); 2nd edn.
5.Osnovnye poniatiya teorii veroyatnostei, “Nauka”, Moscow, 1974 (1933)

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