I am a PhD candidate in Computer Science and Engineering at the University of Michigan, where I am a part of the LIT research group, supervised by Dr. Rada Mihalcea.

My research interests include natural language processing, machine learning, and data science. Right now, I am working on a project exploring how computational techniques can be used to better understand and predict personality.


Data Science in Service of Performing Arts: Applying Machine Learning to Predicting Audience Preferences.

Abernethy, J., C. Anderson, C. Dai, J. Dryden, E. Schwartz, W. Shen, J. Stroud, L. Wendlandt, S. Yang, D. Zhang. Bloomberg Data for Good Exchange, 2016.

Data Acquisition Visualization Development for the MAJORANA DEMONSTRATOR.

Wendlandt, L., M. Howe, and J. Wilkerson. 2013 Fall Meeting of the APS Division of Nuclear Physics. Newport News, VA. 24 Oct 2013. Poster Presentation.


In addition to research, I enjoy teaching computer science. Selected relevant experience is listed below.

  • Graduate Student Instructor: EECS 281 - Data Structures and Algorithms (Fall 2015, Winter 2016)
  • Teaching Assistant: CS and Physics classes at Grove City College (Fall 2012 - Spring 2015)
  • Personal Tutor: One-on-one tutor for students struggling in CS (Fall 2013 - Spring 2015)


My vision is to see computer science become a more diverse field where women and other underrepresented minorities have the tools and opportunities needed to succeed. Towards that end, I am interested in exploring creative solutions to both recruit and retain women in technology.

One project I am involved in is CS KickStart, a week-long summer program designed to help women explore computer science. I was one of the original organizers who brought this program to UM in August 2015.

I am also involved in the Girls Encoded initiative at the University of Michigan. This umbrella organization raises funds and distributes them to promote a wide variety of activities aimed at increasing diversity.