Abstract: Nonlinear optimization stems from calculus and becomes an independent subject due to the proposition of Karush-Kuhn-Tucker optimality conditions. The ever-growing realm of industrial applications and the vast demand from AI development are driving nonlinear optimization research in new and exciting directions. In this talk, I shall address some recent advances on nonlinear optimization, mainly on unconstrained optimization, constrained optimization, optimization with least constraint violation and minimax optimization.

Biography: Yu-Hong Dai is a Full Professor in the Academy of Mathematics and Systems Science (AMSS), Chinese Academy of Sciences. He received the B.Sc. degree in applied mathematics from the Beijing Institute of Technology in 1992, and received the Ph.D. degree in nonlinear programming from the Institute of Computational Mathematics and Scientific/Engineering Computing, Chinese Academy of Sciences in 1997. He is now the president of Operations Research Society of China (ORSC) and the chief editor of Operations Research Transactions (in Chinese). He is also the director of the Center for Optimization and Applications (COA) of AMSS. His research interests include continuous optimization, integer programming and various optimization applications. He received Shiing-Shen Chern Mathematics Award, Feng Kang Scientific Computing Award, Xiao Shutie Applied Mathematics Award, Second Prize of the National Natural Science of China (Rank 2), and the Tenth Science and Technology Award for Chinese Youth. He also won the China National Funds for Distinguished Young Scientists and a Best Paper Award on the 2011 International Conference on Communications.