Entropy estimation and information theory form the bedrock of our understanding of uncertainty and complexity in both natural and engineered systems. At its core, entropy quantifies the ...

For the analysis of nonstationary categorical time series, a parsimonious and flexible class of models is proposed. These models are generalizations of regression models for stochastically independent ...

We propose a nonparametric estimation theory for the occupation density, the drift vector, and the diffusion matrix of multivariate diffusion processes. The estimators are sample analogues to ...

I am a Postdoctoral Researcher in the Department of Electrical Engineering at Princeton University working under the supervision of Professor H. Vincent Poor. In 2018 I was a Lecturer in the ...