PeopleofSuperintelligence

Researcher

Kaitlyn Zhou

Kaitlyn Zhou is an AI researcher whose work examines how language models shape human trust and reliance. She studied computer science and human centered design and engineering at the University of Washington, received the College of Engineering Dean's Medal in 2018, and served on its Board of Regents. At Stanford, she earned a computer science PhD advised by Dan Jurafsky. Her papers examine model uncertainty, human reliance, non-adopter needs, reasoning instructions, and voice-cloning effects on listeners. As of October 2026, she is an assistant professor of Information Science at Cornell and a senior AI researcher at Together AI.

Works
38

Publication numbers from OpenAlex, as of 27 October 2026. Citations and h-index are hidden because this OpenAlex record may be incomplete or mix in other authors.

Timeline

  1. 2018

    The College of Engineering medal

    In 2018, she is a senior at the University of Washington, studying computer science and human centered design and engineering. She receives the College of Engineering's Dean's Medal for Academic Excellence.

  2. 2018

    The UW Board of Regents

    In 2018, Washington governor Jay Inslee appoints her to the University of Washington Board of Regents.

  3. 2022

    Deconstructing NLG Evaluation

    In 2022, she coauthors Deconstructing NLG Evaluation, a mixed-method study that combines interviews and a survey to examine practitioners' goals, assumptions, practices, and constraints in natural language generation evaluation.

  4. 2023

    Navigating the Grey Area

    In 2023, she coauthors Navigating the Grey Area, which tests 50 epistemic markers in question answering and finds that model accuracy varies by more than 80% across markers. The study also finds that high-certainty expressions reduce accuracy by 7% compared with low-certainty expressions.

  5. By 2024

    Research summers and funding

    By 2024, she spends research summers at Microsoft Research and the Allen Institute for Artificial Intelligence. She secures funding from IBM and Microsoft and a Stanford Graduate Fellowship.

  6. 2024–2025

    Relying on the Unreliable

    In 2024, she is a final-year PhD candidate in computer science at Stanford, advised by Dan Jurafsky. Her ACL paper Relying on the Unreliable finds that confident model responses have an average error rate of 47% and that users rely heavily on answers whether or not they signal certainty. By 2025, she holds a computer science PhD from Stanford.

  7. 2025

    REL-A.I. measures reliance

    In 2025, she coauthors REL-A.I., an interaction-centered method for measuring human reliance on LLM responses. Across nine user studies with 450 participants, the study finds that emphatic polite openings make users perceive LLMs as more competent and rely 30% more on their answers. The paper receives the NAACL Best Paper Runner-Up award.

  8. 2026

    Non-adopter and ReasonIF papers

    In 2026, she coauthors Attention to Non-Adopters and ReasonIF, both accepted to Findings of ACL 2026. The first argues that LLM development should include non-adopters' needs; the second introduces a benchmark for instruction following throughout model reasoning and reports that the highest score across tested open-source reasoning models remains below 0.25.

  9. 2026

    Voice cloning as style transfer

    In 2026, she coauthors the NeurIPS paper Voice "Cloning" is Style Transfer. The study finds that voice-cloning systems apply style transfer to source voices. Human annotators rate the cloned voices as more authoritative and report greater trust in them than in the source voices.

  10. As of October 2026

    Cornell and Together AI roles

    She joins Cornell's Department of Information Science as an assistant professor in 2026 and holds a field appointment in Computer Science. As of October 2026, she is also a senior AI researcher at Together AI.

Career

  1. Since 2026Cornell UniversityAssistant Professor of Information Science; field appointment in Computer Science
  2. NowTogether AISenior AI Researcher
  3. From 2018University of WashingtonRegent

Education

  1. University of WashingtonBachelor's degree studies in Computer Science and Human Centered Design and Engineering
  2. Stanford UniversityPhD in Computer Science

From the biography.

Checked career sources: risingstars-eecs.mit.edu, cs.cornell.edu, aclanthology.org, cs.cornell.edu, katezhou.github.io.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

Photo: We have no published photo of Kaitlyn Zhou yet. Send us a free-licensed photo.

  1. Allen School and HCDE senior Kaitlyn Zhou awarded College of Engineering Dean’s Medal news.cs.washington.edu. Checked 27 October 2026.
  2. Kaitlyn Zhou | MIT EECS Rising Stars risingstars-eecs.mit.edu. Checked 27 October 2026.
  3. Kaitlyn Zhou | Department of Computer Science | Cornell Bowers cs.cornell.edu. Checked 27 October 2026.
  4. Kaitlyn Zhou - ACL Anthology aclanthology.org. Checked 27 October 2026.
  5. Cornell Bowers welcomes five new faculty members cs.cornell.edu. Checked 27 October 2026.
  6. Kaitlyn Zhou | Home katezhou.github.io. Checked 27 October 2026.
  7. REL-A.I.: An Interaction-Centered Approach To Measuring Human-LM Reliance - ACL Anthology aclanthology.org. Checked 27 October 2026.
  8. Attention to Non-Adopters arxiv.org. Checked 27 October 2026.
  9. ReasonIF: Large Reasoning Models Fail to Follow Instructions During Reasoning arxiv.org. Checked 27 October 2026.
  10. Voice "Cloning" is Style Transfer arxiv.org. Checked 27 October 2026.