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Thesis defences

PhD Oral Exam - Chang Su, Information and Systems Engineering

Characterizing Stress–Workload Dynamics in Pilot Training: A Theoretical, Neural, and Multimodal Approach


Date & time
Friday, November 28, 2025
10 a.m. – 1 p.m.
Cost

This event is free

Organization

School of Graduate Studies

Contact

Dolly Grewal

Where

Engineering, Computer Science and Visual Arts Integrated Complex
1515 Ste-Catherine St. W.
Room 3.309

Accessible location

Yes - See details

When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.

Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.

Abstract

Stress and workload are central to shaping human performance in aviation training, yet their dynamic interaction during staged practice has not been fully characterized. This dissertation proposes an integrated framework that combines theoretical, neural, and multimodal perspectives to investigate stress–workload dynamics.

First, it reviews established frameworks, including the stress–effort model and dual-system thinking, to clarify how stress and workload have been conceptualized in aviation decision-making and to highlight gaps in the use of physiological measures for assessment. Second, it examines neural mechanisms using electroencephalography (EEG) and functional connectivity, identifying large-scale brain network patterns that reflect workload differences across training demands and stages. These findings demonstrate how neural signatures can track the progression of cognitive effort in practice. Finally, it integrates subjective workload ratings, cardiovascular markers, and EEG features to trace stage-specific dynamics, revealing a decoupling between self-reports and physiological responses: perceived workload decreased while autonomic activation and neural demands remained high.

Together, these studies advance theoretical understanding of stress–workload dynamics in aviation training, introduce methodological innovations for multimodal workload assessment, and provide practical insights for the design of adaptive training strategies to support pilot performance.

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