About Me
I am an Assistant Professor in the Department of Computer Science at Middlebury College. I am teaching Introduction to Computing (CSCI 0145) in Fall 2023.
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.
Education
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
Publications
* denotes equal contribution
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 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
AACL-IJCNLP 2020
Experience
University of Michigan
Instructor
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.
IBM
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
Instructor
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.