 About Me: I am currently a Research Associate in the Dept. of Applied Math at the Univ. of Washington, Seattle. I received my PhD (Oct. 2014 - Jun. 2018) at UCSB, under the supervision of Distinguished Professor Jean-Pierre Fouque. Prior to joining UW in the Fall 2018, I was holding a position as Visiting Assistant Professor (Aug. 2018-Sep. 2018) in the Dept. of Statistics and Applied Probability at UCSB. Research with Publications: Core Research: Discrete Probabilistic Analysis in Big Data and Machine Learning Theoretical: Probability, Financial Math, Stochastic Control and Statistical Inference Statistical Physics, Random Graph, Weakly Interacting Particle System, Reconstruction on Network, Mean Field Games, Nonlinear Option Pricing, Nonlinear Dynamical System, Bayesian Analysis. Theoretical & Empirical: Machine Learning and Data Mining Bayesian Structural Time Series, Data Mining, Feature Selection and Dimension Reduction, Deep Learning. Selected Publications: Deep Learning and Data Science: Classification on Deep Network Large Degree Asymptotics and the Reconstruction Threshold of the Asymmetric Binary Channels, with W. Liu, Journal of Statistical Physics, March 2019, Volume 174, Issue 6, pp 1161–1188. Bayesian Machine Learning on Time Series (top Machine Learning journal) Multivariate Bayesian Structural Time Series Model, with J. Qiu et al., Journal of Machine Learning Research, 19(68):1−33, 2018. Network Science (top Artificial Intelligence journal) Evolution of Regional Innovation with Spatial Knowledge Spillovers: Convergence or Divergence?, with J. Qiu et al., Networks and Spatial Economics, accept with minor revision, 2019. Math Finance Uncertain Volatility Models with Stochastic Bounds, with J. P. Fouque, SIAM Journal on Financial Mathematics, 9(4), 1175–1207, 2018. Membership: American Economics Association Institute of Operations Research and Management Sciences SIAM (Financial Mathematics and Engineering; Data Mining and Analytics) |