MSc by Research at Trinity College Dublin studying how AI coaching shapes motivation, physiology, and neural engagement during high-effort exercise. Now seeking commercial roles in pharma, med-tech, and health technology where scientific credibility, communication, and athlete-grade resilience translate into real impact.
I'm a neuroscience and physiology graduate from Trinity College Dublin, completing an MSc by Research at the intersection of human performance, AI coaching, and physiological measurement.
I've authored a 60-page literature review on AI in sport and exercise performance — one of the first systematic analyses of this emerging field — and recently completed a 37-participant pilot study with novel findings on how digital coaching reproduces the effects of live human encouragement.
My background spans laboratory research, undergraduate teaching to cohorts of 200+, and a career as an Irish international squash player. I'm now looking to apply that scientific foundation in a commercial healthcare environment — where evidence-based communication, relationship-building, and a high-performance mindset create direct impact.
As part of my MSc by Research, I designed and executed a within-subject pilot study comparing live human coaching, standardised digital voice coaching, and an instructions-only control across three high-effort exercise tasks.
To my knowledge, no published study has directly compared live human coaching, standardised digital voice coaching, and an instructions-only control within a single within-subject design across multiple high-effort exercise tasks. The study used multimodal physiological measurement including HRV, EMG, RPE, and Wingate sprint power output.
Presenting complex physiological and neuroscience data clearly to clinical, student, and non-expert audiences across cohorts of 200+.
HRV, EDA, ECG, EEG, EMG, lactate sampling — both laboratory and field-based protocols.
Experimental design, SPSS, R, MATLAB, mixed-effects models, repeated-measures analysis.
Teaching 200+ undergraduates · supervising capstone projects · participant management · ethics committee liaison.
Deep understanding of AI health technology, wearables, digital coaching, and the human performance market.
Irish international squash player — resilience, focus, and target-driven competitive experience under pressure.
Background. Verbal encouragement is a well-established acute modulator of physical performance, yet it remains unclear whether AI-delivered digital coaching can reproduce these effects under matched, controlled conditions. This pilot was designed as the first direct, within-subject test of that question across multiple exercise modalities.
Methods. Thirty-seven healthy adults (21F · 16M, aged 18–30) completed three high-effort tasks — isometric wall sit, maximal handgrip, and a 30-second Wingate sprint — under three counterbalanced coaching conditions: live human encouragement, a standardised digital AI voice (script, intonation, and delivery timing matched to the human condition), and an instructions-only control. Multimodal physiological data were captured continuously: heart-rate variability (HRV), electrodermal activity (EDA), surface EMG, perceived exertion (RPE), and Wingate peak and mean relative power. Motivation and affect were captured via validated post-task self-report.
Findings. Both coached conditions significantly outperformed control. Wall-sit endurance increased by ~21% under coaching versus control (p<.001), and Wingate peak relative power improved across coached conditions. Critically, digital and human coaching were statistically indistinguishable on the primary performance and motivational outcomes — to my knowledge the first within-subject evidence that standardised AI voice coaching can reproduce the acute performance signature of live human encouragement across multiple exercise tasks.
Significance. The findings establish a mechanistic foothold for scalable, evidence-based AI coaching in sport, rehabilitation, and digital health — settings where consistent, high-quality verbal support is logistically constrained but performance outcomes matter clinically.
Status. Manuscript in preparation; selected for presentation at the FENS Forum, Barcelona (July 2026). Conducted at Trinity College Dublin under the supervision of Prof. Áine Kelly (Physiology) and Dr Giovanni Di Liberto (Computer Science & AI).
First-Class Honours (72%), Trinity College Dublin (2025). Independent experimental design, ethics approval, participant recruitment, SPSS analysis, and 60-page dissertation.
I'm actively exploring commercial roles in pharma, med-tech, and health technology — open to opportunities in Dublin, London, and across Europe.
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