Laura Biester

Computer Science PhD Candidate

About Me

I am a third-year PhD Student at the University of Michigan, where I work with Dr. Rada Mihalcea on natural language processing and computational social science. I am interested in gaining a better understanding of people through language data and AI for social good.

After completing my PhD, I hope to stay in academia as a faculty member.

Before I was a graduate student, I spent two years at Pinterest as a software engineer, and earned my BA in computer science from Carleton College in 2016.

Education

University of Michigan

Computer Science and Engineering, PhD

Expected 2023

Advised by Dr. Rada Mihalcea
Research Area: natural language processing and computational social science

University of Michigan

Computer Science and Engineering, MS

May 2020

Coursework: Advanced Artificial Intelligence, Advanced Database Systems, Microarchitecture, Natural Language Processing, Psychology of Language, Research Seminar in Science, Tech and Public Policy

Carleton College

Computer Science, BA

June 2016

Elective Coursework: Artificial Intelligence, Computational Models of Cognition, Natural Language Processing, Operating Systems, Parallel and Distributed Computing

Publications

Building Location Embeddings from Physical Trajectories and Textual Representations

Laura Biester, Carmen Banea, Rada Mihalcea

AACL-IJCNLP 2020

Quantifying the Effects of COVID-19 on Mental Health Support Forums

Laura Biester*, Katie Matton*, Janarthanan Rajendran, Emily Mower Provost, Rada Mihalcea (* = equal contribution)

NLP COVID-19 Workshop @ EMNLP 2020

Experience

University of Michigan

Instructor

Fall 2019, Fall 2020

Primary instructor for EECS 198, Discover Computer Science. Responsibilities include weekly lectures, grading, curriculum/assignment design, and managing a team of two undergraduate teaching assistants.

Pinterest

Software Engineer

August 2016 - August 2018

Worked primarily on large scale storage systems on top of MySQL and HBase. Projects include an inconsistency detection framework for distributed graph databases, and sharding strategies/implementation for advertiser data.

Carleton College

Computer Science Grader

Spring 2016

Graded three assignments per week for 30 students in Mathematics of Computer Science, the introductory discrete mathematics course for computer science majors.

Carleton College

Computer Science Prefect

Spring 2014, Winter 2015, Spring 2015, Fall 2015, Winter 2016

Spent three terms as a prefect for Mathematics of Computer Science and two terms as a prefect for Data Structures. Responsibilities included preparing worksheets and leading twice-weekly study sessions for 10-40 students (depending on the class), in addition to providing 1-1 tutoring for students as requested.