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I am a clinician-researcher specialising in measuring human cognitive and psychological states in real-world, safety-critical environments. My PhD (Surgical Sabermetrics, University of Edinburgh) established the feasibility of continuous multimodal physiological monitoring (electrodermal activity, heart rate variability, fNIRS) as a measure of cognitive load in live surgery, across 16 surgeons and 72 operative cases. I designed and led every stage: study design, NHS research ethics and GDPR-compliant data governance, sensor deployment in live theatres, and custom Python and R analysis pipelines for signal decomposition, trend analysis, and multi-person physiological synchrony. This work sits at the intersection the role describes: rigorous behavioural experimentation where data quality and participant wellbeing must be balanced in demanding settings. Recruiting and instrumenting surgeons mid-workflow, where patient safety is paramount, demanded the same ethical care and methodological discipline as human-AI interaction studies. I also have growing expertise in AI safety in healthcare. I contributed to the CIEHF Digital and AI in Healthcare working group white paper, and through my consultancy I advise on evidence design and clinician-centred validation for AI-enabled and human-state health technologies. I hold an MBChB, and a PGCert in Clinical Human Factors and Patient Safety, giving me a systems-level understanding of how technology shapes human performance, error, and wellbeing. I have a track record of dissemination through peer-reviewed publications, conference talks, and policy-facing work, plus experience supervising junior researchers and coordinating international collaborations. I would bring to AISI deep expertise in measuring how humans are affected by the systems they work with, psychologically and physiologically, and the technical fluency to apply this within an AI evaluation programme.
University of Edinburgh
Medical Infomatics · Surgical Data Science for Behavioural Science
August 3, 2021 – June 29, 2026
University of Edinburgh
Patient Safety and Clinical Human Factors
August 4, 2020 – May 31, 2021
Royal College of Surgeons of Edinburgh
Membership of the Royal College of Surgeons
April 7, 2015 – Present
University of Glasgow
MBChB · Medicine
September 6, 2011 – June 2, 2014
University of St Andrews
Medicine
September 2, 2008 – Present
Cultural Fit Analysis
The candidate's profile shows a strong cultural fit for a research scientist role, particularly within an AI Safety Institute. Their interdisciplinary background, combining medicine, human factors, and emerging data science/AI skills, is highly valuable. The extensive collaboration with various institutions (e.g., University of Sheffield, Harvard University, US Air Force, Scottish Rugby Union) and active participation in professional bodies demonstrate a collaborative and outward-looking approach. The focus on 'AI safety' and 'responsible AI deployment' directly aligns with the mission of an AI Safety Institute. The breadth of their research interests, from cognitive load to sleep quality and surgical performance, indicates intellectual curiosity and adaptability.
Soft Skills & Operational Fit
The candidate demonstrates strong dedication and a collaborative spirit through extensive committee work and multi-author publications. Their commitment to advancing surgical education, wellbeing, and patient safety aligns with a proactive and responsible work attitude. The focus on human factors and AI safety suggests a thoughtful and ethical approach to research, which is crucial for AI safety institutes. The candidate's ability to manage a PhD while maintaining clinical roles and contributing to numerous projects indicates excellent time management and resilience.