EDUCATION

Cornell University — Ph.D. in Information Science
Ithaca, NY

  • GPA: 4.00 / 4.00
  • Microsoft Azure Cloud Computing Grant ($18,700)
  • Outstanding Teaching Award

Cornell University — M.S. in Information Science
Ithaca, NY, 2024

  • GPA: 4.00 / 4.00

RESEARCH & PROFESSIONAL EXPERIENCE

Allen Institute for Artificial Intelligence — PhD Research Intern, Semantic Scholar
Seattle, WA | June 2025 – Present

  • Developed a query reformulation system that increases Asta’s recall of scientific information in the output by 50%.
  • Created the Query Reformulation Benchmark to evaluate query reformulation methods by augmenting thousands of pairs of underspecified and refined user queries with few-shot learning.
  • Designing a user study to test the usefulness and relevance of our system’s suggested query reformulations.

Cornell University — LLM & AI Research Scientist
Ithaca, NY | Aug 2021 – Present

  • Designed LongQAEval, a framework for the evaluation of long-from LLM outputs; when prompted with my framework LLM-as-judge agreement with experts increases by 24%, reaching expert-level agreement.
  • Identified unmet user needs in 15,000+ posts and 300,000+ comments from endometriosis online communities with fine-tuned DistilBERT models and few-shot learning.
  • Leveraged causal inference to demonstrate that readers have no strong preference for character gender in a randomized survey experiment with 3,000 participants.

Cornell University — Teaching Assistant, Data Science and Machine Learning
Ithaca, NY | Jan 2024 – Dec 2024

  • Taught weekly sections on data science, machine learning (ML), and natural language processing (NLP).
  • Delivered lectures on social media analysis with NLP and statistical techniques for causal effect estimation.
  • Curated a class activity on preprocessing large raw census data and applying ML to predict social outcomes.

NYC Health + Hospitals — Data Science Intern
New York City, NY | Jun 2023 – Aug 2023
Funded by the Siegel Family Endowment PiTech PhD Impact Fellowship

  • Identified three alerts frequently overridden by nurses by analyzing around 3,000,000 clinical interruptive alerts.
  • Demonstrated that revising alert criteria can reduce unnecessary alerts by up to 94%, while improving alert design can decrease overridden alerts by up to 64%, through data analysis and statistical testing.
  • Prompted hospital leadership to implement organization-wide routine alert revisions by presenting findings to administration and informatics experts.

PUBLICATIONS (in order of relevance to my current research goals)

LongQAEval: Designing Reliable Evaluations of Long-Form Clinical QA under Resource Constraints
Federica Bologna, Tiffany Pan, Matthew Wilkens, Yue Guo, Lucy Lu Wang
Submitted to ACL ARR

Endometriosis Online Communities: A Quantitative Analysis
Federica Bologna, Rosamond Thalken, Kristen Pepin, Matthew Wilkens
Journal of Medical Internet Research (2025)

Revising BPA triggers and inclusion criteria helps reduce nurses’ fatigue
Federica Bologna, Anand Reddy, David Silvestri, Michael Bouton
Poster at the American Medical Informatics Association (AMIA) Annual Symposium (2025)

Endometriosis Online Communities: How Machine Learning Can Help Physicians Understand What Patients Are Discussing Online
Kristen Pepin, Federica Bologna, Rosamond Thalken, Matthew Wilkens
Journal of Minimally Invasive Gynecology (2024)

Causal Effect of Character Gender on Readers’ Preferences
Federica Bologna, Ian Lundberg, Matthew Wilkens
Computational Humanities Research (2025)

Stylometric Analysis of the Poems Attributed to an Unknown Male Author in Veronica Franco’s Terze Rime
Giulia Andreoni, Federica Bologna, Marilyn Migiel
Early Modern Women: An Interdisciplinary Journal (Forthcoming)

Do open citations give insights on the qualitative peer-review evaluation in research assessments? An analysis of the Italian National Scientific Qualification
Federica Bologna, Angelo Di Iorio, Silvio Peroni, and Francesco Poggi
Scientometrics (2022)

Open bibliographic data and the Italian National Scientific Qualification: measuring coverage of academic fields
Federica Bologna, Angelo Di Iorio, Silvio Peroni, and Francesco Poggi
Quantitative Science Studies (2022)

A Computational Approach to Urban Space in Science Fiction
Federica Bologna
The Journal of Cultural Analytics (2020)

SKILLS & INTERESTS

Programming Languages: Python, R, Bash, SQL
Methods: NLP, Data Science, Statistical Testing, Causal Inference, Interviews, Surveys
Interests: poetry fanatic (Meadowlands is a favorite), aspiring gym rat, anime binge-watcher (Frieren at the moment)

POSTERS & PRESENTATIONS

Revising BPA triggers and inclusion criteria helps reduce nurses’ fatigue Poster at the American Medical Informatics Association (AMIA) Annual Symposium (2025)

What is Happening in Endometriosis Online Communities? Main Stage Presentation at the 2023 Global Congress of the American Association of Gynecologic Laparoscopists (AAGL)

Support and Relationship Patterns in Endometriosis Narratives Long Presentation at DH2022

Analyzing Urban Space’s Presence in Science Fiction Using Token Counts
Federica Bologna Presentation at University of Naples “L’Orientale” Graduate Conference 2020

TEACHING EXPERIENCE

Fall 2025 — Graduate TA, INFO 2950: Introduction to Data Science, Cornell University
Fall 2024 — Graduate TA, INFO 3350: Text Mining for History and Literature, Cornell University
Spring 2024 — Graduate TA, INFO 3370: Studying Social Inequality with Data Science, Cornell University
Spring 2023 — Graduate TA, INFO 3370: Studying Social Inequality with Data Science, Cornell University
Spring 2022 — Graduate TA, INFO 3350: Text Mining for History and Literature, Cornell University

HONORS, AWARDS & SCHOLARSHIPS

2024 — Microsoft Azure Cloud Computing Grant, Cornell University
2023 — Outstanding Teaching Award, Cornell University
2023 — Siegel Family Endowment PiTech PhD Impact Fellow, Cornell University
2019 — M.A. Thesis Research Abroad Scholarship, University of Bologna, Italy
2017 — Overseas Study Abroad Scholarship, University of Bologna, Italy