From big data to Artificial Intelligent (AI)
"Big data is the mine of gold, and AI is the modern mining machinery." Guang describes himself as a gold miner piloting the modern machines. When viewing his research projects, Guang thinks that some are fun, some are meaningful, and some are interruptive. He thinks that at this emergent stage of AI, a good researcher needs to be creative, bold, and brave. There is a saying that Guang likes the most: Go Big or Go Home.
From Mathematics to Machine Learning (ML)
Guang’s math research involves stochastics differential equations, stochastic control, stochastic approximation and optimization, finance, and numerics. At GE, he uses ML, deep learning, and statistics to solve problems in aviation, transportation, power, finance, etc. His current research interest is in Deep Learning, Computer Vision, and the applications in 'human world' problems as well as 'machine world' problems.
"It's like doing chemistry experiment. Pour 5 terabyte of industrial data, add 8 state-of-the-art models, place 10 drops of busiess acumen, stir it up carefully, and something magic and fun may happen."
Bao, L., Zhao, G. and Jin, Z., 2018. A new equilibrium trading model with asymmetric information
Yin, G., Zhao, G. and Xi, F., 2011. Mean-Field models involving continuous-state-dependent random switching: Nonnegativity constraints, moment bounds, and two-time-scale limits. Taiwanese Journal of Mathematics, 15(4), pp.1783-1805.
Yin, G., Zhao, G. and Wu, F., 2012. Regularization and stabilization of randomly switching dynamic systems. SIAM Journal on Applied Mathematics, 72(5), pp.1361-1382.