PeopleofSuperintelligence

Researcher

Jesse Gronsbell

Also known as Jessica Gronsbell, Jessica L. Gronsbell

Jesse Gronsbell is a biostatistician who develops statistical learning and inference methods for observational health data, including the use of AI-generated data. She earned a B.A. in applied mathematics at UC Berkeley and a Harvard PhD in biostatistics under Tianxi Cai, with a 2017 dissertation on machine learning for electronic medical records. After a postdoc at Stanford with Lu Tian and a data scientist job at Alphabet's Verily Life Sciences, she joined the University of Toronto's Department of Statistical Sciences in July 2020. In 2025 she gave a McMaster seminar on using predictions as data, and in August 2026 she taught a NISS short course on prediction-based inference. She is an associate professor of Statistical Sciences at Toronto and a faculty affiliate of the Vector Institute for Artificial Intelligence.

Badges

Timeline

  1. By 2017

    A Harvard biostatistics doctorate

    She earns a B.A. in applied mathematics at UC Berkeley and a PhD in biostatistics at Harvard, where Tianxi Cai advises her. Her 2017 dissertation, Robust and Efficient Machine Learning Methods for the Analysis of Electronic Medical Records Data, builds semi-supervised learning methods for finding patients with specific diseases in medical records.

  2. 2017–2018

    Semi-supervised model evaluation

    In November 2017, she and Tianxi Cai post a preprint on evaluating the performance of a binary classifier when only a small share of cases carry labels, motivated by phenotyping algorithms built from electronic medical records. The paper appears in the Journal of the Royal Statistical Society Series B in 2018 and is illustrated with two real electronic medical record studies.

  3. By 2020

    Stanford postdoc and Verily data scientist

    After her doctorate, she spends a year as a postdoc with Lu Tian in Stanford's Department of Biomedical Data Science. By 2020, she is a data scientist at Alphabet's Verily Life Sciences, on the mental health research and development team led by Menachem Fromer.

  4. July 2020

    Joining Toronto's statistics department

    She joins the University of Toronto's Department of Statistical Sciences in July 2020 as an assistant professor, working on statistical methods for electronic health records and mobile health data. She holds cross-appointments in Computer Science and Family & Community Medicine and is a faculty affiliate of the Vector Institute for Artificial Intelligence.

  5. April 2025

    Predictions as data at McMaster

    In April 2025, she gives a statistics seminar at McMaster University titled "Using predictions as data in biomedical research: Possibilities and pitfalls." The talk introduces a recently proposed method for bias correction when machine learning predictions complement costly gold-standard data.

  6. August 2026

    A short course on predicted data

    In August 2026, she is an instructor of the NISS virtual short course on prediction-based inference. The course covers methods that correct bias when AI and machine learning predictions replace measured variables, and it teaches the ipd R package.

  7. As of October 2026

    Associate professor and Vector affiliate

    She is an associate professor in Statistical Sciences at the University of Toronto and a faculty affiliate at the Vector Institute, where her research covers extreme missing data, measurement error, bias and fairness, and the use and implications of AI-generated data. She is an associate editor for Biometrics and the Journal of the American Statistical Association and is on sabbatical through July 2027.

Career

  1. Since 2020University of TorontoAssistant professor
  2. Since 2020Vector InstituteFaculty affiliate
  3. Until 2020GoogleData scientist
  4. Stanford UniversityPostdoc

Education

  1. 2017Harvard UniversityPhD in biostatistics
  2. University of California, BerkeleyB.A. in applied mathematics

From the biography.

  1. Of 943 people shaping AI who worked at Google, 446 work there nowIncludes Jesse Gronsbell. Our estimates of where the 943 people shaping AI who worked at Google and Google DeepMind work now: 446 at Google and 452 across 278 other organizations.
  2. 16% of AI career moves in the 2020s went from a university to a companyIncludes Jesse Gronsbell. We estimate that 16% of AI career moves in the 2020s went from a university to a company; 29% of moves starting at a university went to a company, and 76% ended the university role.
  3. The median h-index is 48 at universities and 14 at frontier AI labsIncludes University of Toronto. The median h-index is 48 at universities and 14 at frontier AI labs. We compare publishing careers, recent citations, dual appointments and job moves across 2,420 university researchers and 308 frontier-lab researchers.
  4. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other universityIncludes University of Toronto. The Massachusetts Institute of Technology trained or employed 44 of the 187 AI major-prize winners, more than any other university. We compare doctorate and 5+ year employment links, career timing and current workplaces for 187 major-prize and 1,111 best-paper winners.

Colleagues

People named in this biography, and people with dated positions at the same organization in the same years.

Sources and credits

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

  1. Robust and Efficient Machine Learning Methods for the Analysis of Electronic Medical Records Data dash.harvard.edu. Checked 21 October 2026.
  2. Jesse Gronsbell - About sites.google.com. Checked 21 October 2026.
  3. Jessica Gronsbell – IMPACT Program impactprogram.mit.edu. Checked 21 October 2026.
  4. Semi-Supervised Approaches to Efficient Evaluation of Model Prediction Performance arxiv.org. Checked 21 October 2026.
  5. Semi-supervised approaches to efficient evaluation of model prediction performance ideas.repec.org. Checked 21 October 2026.
  6. Q & A with Jesse Gronsbell, assistant professor, Department of Statistical Sciences at the University of Toronto ssc.ca. Checked 21 October 2026.
  7. A warm welcome to four new colleagues | Statistical Society of Canada ssc.ca. Checked 21 October 2026.
  8. Jesse Gronsbell | Health Data Methods | Statistical Horizons statisticalhorizons.com. Checked 21 October 2026.
  9. Statistics Seminar | Jesse Gronsbell | Using predictions as data in biomedical research: Possibilities and pitfalls math.mcmaster.ca. Checked 21 October 2026.
  10. NISS Virtual Short Course Series: Prediction-Based Inference: Methods & Applications niss.org. Checked 21 October 2026.
  11. Jesse Gronsbell - Vector Institute for Artificial Intelligence vectorinstitute.ai. Checked 21 October 2026.
  12. Jesse Gronsbell sites.google.com. Checked 21 October 2026.