My Teaching Vision



My teaching vision is simple: teach with verve, enthusiasm, be yourself, and most importantly be humble and kind. My teaching mission is to inspire students to be impactful in what they love to do most (and this may not be statistics, computer science, or machine learning). For undergraduates, I want to show them the powerful nature that lies within the statistical core and its connections with social sciences and other disciplines. For graduate students and postdoctoral students, I want to emphasize the connection between the foundations of statistics and how these relate to modern and applied topics today that also have impacts beyond statistics often in the social sciences, medical research, human rights, or public policy. I strive to be a mentor to students and impower them to be independent researchers and make their own contributions and impact in society.

I am exploring new ways of adding technology into the classroom, but in meaningful ways. This semester through my preditive modeling and data mining course, I'm having students submit everything through git and bitbucket. I'm excited to see how this works from my perspective, the perspective of the TAs, and especially if the students like this new experiment (and how to improve this idea for future classes). For preparation, I'm including some ideas on how to implement this in your own course (please note this is in very early stages).

Version control (git) in the classroom

Use git.



Teaching


STA 325 Data Mining and Machine Learning

Duke University
Instructor, Fall 2017.



STA 360/602: Bayesian Methods and Modern Statistics

Duke University
Instructor, Spring 2017.


STA 794: Modern Advancements in Record Linkage

Duke University
Instructor, Fall 2016.



Teaching Bayes: The Essential Parts

ISBA World Meeting 2016
Invited Short Course (3 lectures), Course Materials .


STA 360/601: Bayesian Methods and Modern Statistics

Duke University
Instructor, Spring 2016.


STA 521: Predictive Modeling

Duke University
Instructor, Fall 2015.


Introduction to Privacy and Confidentiality

University of Paris Dauphine
Short course for professional Master's program November 2014.


Stat 36-464: Applied Multivariate Statistics

Carnegie Mellon University
Revised entire course and Instructor, Spring 2014.


Stat 36-786: Theoretical Bayesian Statistics

Carnegie Mellon University
Developed entire course and Instructor, Spring 2013.


Stat 36-78y: Applied Bayesian Statistics

Carnegie Mellon University
Developed entire course and Instructor, Spring 2013.


STA 4930: Introduction to Bayesian Statistics (Honors).

University of Florida
Developed entire course and Instructor. Spring 2011.


MTHSC 203: Elementary Statistical Inference

Clemson University
Lecturer. Fall 2006, Spring 2007 .


6.Stat 3024: Introduction to Statistics II

University of Florida
Teaching Assistant. Spring 2008.


MTHSC 203: Elementary Statistical Inference

Clemson University
Teaching Assistant Spring 2006 .


MTHSC 104: Precalculus and Introductory Differential Calculus

Clemson University
Teaching Assistant Fall 2005

A Tutorial on JAGS

Univeristy of Florida
Fall 2009
.