Quan Cai (Trent)


Department of Statistics
Texas A&M University
Email: qcai@stat.tamu.edu

Office: Blocker 461

Summary

  • Five years research and data-driven experience with statistical analysis, quantitative analysis and advanced analytics.
  • Familiar with R, Python, SQL, Linux, SAS, Matlab, Latex and MS Office Suite.
  • Self learned big data techniques such as Hadoop, Spark, Parallel Computing.
  • Experience with statistical analysis, longitudinal data, nonparametric models, design of experiment, causal inference, machine learning algorithms and predictive modeling.

    • Research Interest

  • Semiparametric Statistics
  • Nonparametric Statistics
  • Longitudinal Data Analysis
  • Causal Inference
  • Machine Learning

    • Education

  • Ph.D. of Statistics, Texas A&M University 2012 - 2017
      -Advisor: Prof. Suojin Wang
  • B.S. of Statistics, Department of Mathematics, Zhejiang University 2008-2012
      -Advisor: Prof. Zhengyan Lin

    Research Project

  • Inferences with Generalized Partially Linear Single-index Models for Longitudinal Data, Texas A&M University, College Station, TX, 2016-2017
  • Nonparametric Data-Driven Tools for Well Drilling Strategies in Shale Reservoirs, Texas A&M University, College Station, TX, 2016-2017
  • Partially Linear Single-index Models for Longitudinal Data (pdf), Texas A&M University, College Station, TX, 2014-2016
  • Propensity Score Matching for Measuring Asbestos Claims Costs, Liberty Mutual Insurance Group, Boston, MA, 2015
  • Chinese Earthquake Loss Distribution Estimation, Zhejiang University, Hangzhou, China, 2012

    • Experience

  • Advanced Analytics/Data Science Intern, Liberty Mutual Insurance Group, June 2015 - August 2015
  • Winner Team, Capital One Modeling Competititon, September 2014 - December 2014

    • Teaching

  • STAT 303-102, Statisical Methods (Syllabus), Summer 2017
  • STAT 303-503, Statisical Methods (Syllabus), Spring 2017
  • STAT 303 Old Exams

    Courses Taken

  • STAT 605 Advanced Topics in Computational Statistics
  • STAT 612 Theory of Linear Models
  • STAT 613 Advanced Theory of Statistical Inference
  • STAT 614 Statistical Applications in Probability
  • STAT 620 Statistical Large Sample Theory
  • STAT 632 Bayesian Statistics I
  • STAT 636 Machine Learning I
  • STAT 641 The Methods of Statistics
  • STAT 642 Experimental Design
  • STAT 647 Spatial Statistics
  • STAT 648 Applied Statistics and Data Analysis
  • STAT 684 Statistical Consulting
  • STAT 689 Special Topics in Large Scale Inference

    • Links

  • Statistical Graduate Student Association (SGSA)
  • The Ph.D. Grind
  • StatLib
  • Statistics Jobs
  • Abdrew Gelman's Blog
  • Radford Neal's Blog
  • Christian Robert's Blog
    The lastest update is on May. 20th, 2017.