Zhen-bang Wang

PhD Student

Statistics, GMU

Biography

I am a Ph.D. student in the GMU Statistics Department. I am fortunate to be advised by Martin Slawski. Previously, I studied mathematics at Jiangsu University and Arcadia Univeristy where I worked with Ned Wolff on effective sample size of clustered data. I studied statistics at Rutgers University where I worked with John Kolassa on saddlepoint approximation.

Interests

Record Linkage
High-dimensional statistics
Machine Learning
Deep Learning

Education

PhD in Statistics, Present

George Mason University
MSc in Statistics, 2018

Rutgers University
BSc in Mathematics, 2016

Jiangsu University and Arcadia University

Current Research

Regularization for Shuffled Data Problems via Exponential Family Priors on the Permutation Group

In the analysis of data sets consisting of pairs $(X_i,Y_i)$, a tacit assumption is that each pair corresponds to the same observation …

Aug 25, 2021

Regression with linked data sets subject to linkage error

Data are often collected from multiple heterogeneous sources and are combined subsequently. In combing data, record linkage is an …

Feb 28, 2021

Estimation in generalized linear models based on linked data contaminated by mismatch error

Identification of matching records in multiple files can be a challenging and error-prone task. Linkage error can considerably affect …

Oct 1, 2020

Project

Mask Region-Based Convolutional Neural Network(R-CNN) for Object Detection

Detect Kangaroo within photos.

Dec 23, 2020

Convolutional Neural Network (CNN) for Sentiment Analysis

Classify Movie Reviews as Positive or Negative.

Dec 5, 2020

Global CO2 Prediction with Fixed Rank Kriging

Make prediction for Global CO2.

Dec 9, 2019

Tesla Stock Market Price Predictions with Long Short-Term Memory (LSTM)

Predict Stock Price Using LSTM.

Jun 16, 2019

Misc

While I am not doing statistics, I am learning fingerstyle guitar and playing guitar cover for pop songs.

Here are some links of my guitar covers:

I also enjoy cooking.

Here are some recepie links I tried by myself:

I enjoy taking notes while learning.

Here are some notes written in latex: