Laura Biester

Assistant Professor of Computer Science

About Me

I am an Assistant Professor in the Department of Computer Science at Middlebury College. I am teaching Natural Language Processing (CSCI 0457) in Spring 2024.

My research interests are at the intersection of Natural Language Processing (NLP) and Computational Social Science. My Ph.D. thesis focused on modeling change in language over time for individuals with depression, primarily using social media data. I have also done work on perspectivism in NLP, bias in language, and Clinical NLP.

I completed my Ph.D. in 2023 at the University of Michigan, and earned my B.A. in computer science from Carleton College in 2016. I have also spent time in industry, including a summer as an intern IBM Research working on Clinical NLP and two years as a full-time software engineer at Pinterest working on database systems.


University of Michigan

Computer Science and Engineering, PhD

August 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, Ethics for AI and Robotics (audit)

Carleton College

Computer Science, BA

June 2016

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


* denotes equal contribution

Temporal Arcs of Mental Health: Patterns Behind Changes in Depression over Time

Laura Biester, James W. Pennebaker, Rada Mihalcea

ACII 2023 Late Breaking Results

Lexical Measurement of Teaching Qualities

Laura Biester, Ian Stewart, Laura Hirshfield, Rada Mihalcea, and Sara Pozzi

ASEE 2023 (Educational Research and Methods Division)

Improving Mental Health Classifier Generalization with Pre-Diagnosis Data

Yujian Liu*, Laura Biester*, Rada Mihalcea

ICWSM 2023

We Are in This Together: Quantifying Community Subjective Wellbeing and Resilience

MeiXing Dong, Ruixuan Sun*, Laura Biester*, Rada Mihalcea

ICWSM 2023

Emotional and Cognitive Changes Surrounding Online Depression Identity Claims

Laura Biester, James W. Pennebaker, Rada Mihalcea

PLOS ONE (2022)

Analyzing the Effects of Annotator Gender Across NLP Tasks

Laura Biester, Vanita Sharma, Ashkan Kazemi, Naihao Deng, Steven Wilson, Rada Mihalcea

NLPerspectives Workshop at LREC 2022

IBM @ TREC Clinical Trials Track 2021

Laura Biester, Venkata Joopudi, Bhrarath Dandala

Proceedings of the Thirtieth Text REtrieval Conference (TREC 2021)

Understanding the Impact of COVID-19 on Online Mental Health Forums

Laura Biester, Katie Matton, Janarthanan Rajendran, Emily Mower Provost, Rada Mihalcea

ACM Transactions on Management Information Systems: Special Issue on Using AI and DATA Science to Handle Pandemic and Related Disruptions (2021)

Building Location Embeddings from Physical Trajectories and Textual Representations

Laura Biester, Carmen Banea, Rada Mihalcea


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

Laura Biester*, Katie Matton*, Janarthanan Rajendran, Emily Mower Provost, Rada Mihalcea

NLP COVID-19 Workshop @ EMNLP 2020


University of Michigan


Winter 2022

Primary instructor for EECS 183, Elementary Programming Concepts. Responsibilities include bi-weekly lectures, office hours, updating assignments, grading, and writing exams.

University of Michigan

Engineering Teaching Consultant (ETC)

Fall 2021 - Winter 2023

Worked in the Center for Research on Learning and Teaching (CRLT) as a ETC. Responsibilities included leading learning cohorts of 20 students as part of the graduate student instructor/instructional aid training (GSI/IA), one-on-one consultations with GSIs/IAs, and conducting midterm student feedback sessions.


Research Intern

Summer 2021

Worked on the EMRA (electronic medical records analysis) team on the TREC 2021 Clinical Trials Track challenge. My project involved matching patient descriptions to clinical trials using deep learning.

University of Michigan


Fall 2019, Fall 2020

Primary instructor for EECS 198 (now EECS 110), Discover Computer Science. Responsibilities include weekly lectures, grading, curriculum/assignment design, and managing a team of two undergraduate teaching assistants.


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.