Scholar
Jack Gallifant
Google Scholar ID: SlLz8KoAAAAJ
AIM @ Harvard-MGB
Citations & Impact
Citations
854
H-index
14
i10-index
19
Publications
20
Co-authors
38
list available
Publications
Resume (English only)
Academic Achievements
- Published in venues including NeurIPS, EMNLP, Nature Medicine, and The Lancet Digital Health; co-authored the TRIPOD-LLM reporting guideline; developed benchmarks for clinical AI; delivered multiple international talks, including a TED talk.
Research Experience
- Postdoctoral Research Associate at Harvard Medical School / Brigham & Women's Hospital (2024 - Present), developed and deployed the first end-to-end agentic adverse event reporting system, built comprehensive benchmarks for LLM robustness evaluation; Postdoctoral Research Associate at Massachusetts Institute of Technology (2023 - 2024), coordinated international research teams on AI governance, redefined evaluation metrics for machine learning under class imbalance; Honorary Clinical Data Scientist at NHS - Guy's and St Thomas' Trust (2022 - 2024), quantified miscalibration harm in the National Early Warning Score due to pulse oximetry bias; Foundation Doctor at NHS - Imperial College Healthcare Trust (2021 - 2023), provided frontline care and designed a surgical outcome dashboard.
Education
- PhD in AI for Oncology & Healthcare at Maastricht University (2024 - 2026), supervised by Prof. Hugo J.W.L. Aerts; MSc in Human and Applied Physiology from King's College London (2019 - 2020).
Background
- AI researcher and engineer focused on robustness, interpretability, and agentic systems. Former NHS physician now building and evaluating AI for healthcare and beyond.
Miscellany
- Exploring applications of agentic systems in healthcare and biotech, with a focus on agentic interaction environments, reinforcement learning tooling, and methods that can accelerate healthcare delivery and enable continual knowledge creation.
