Research Scientist at thebridge · Human–AI decision-making
I translate behavioral and physiological evidence into product decisions by combining psychophysics, pupillometry, Bayesian modeling, and working prototypes to understand where performance breaks and what an interface should do next.
Industry experience
Current work on human–agent collaboration, with prior experience supporting research operations behind surgical-safety technology.
Research Scientist, Research & Experiment Lead
Research Assistant I
Education
A research foundation spanning perception, cognition, quantitative methods, and human behavior.
Neurotree profile (academic genealogy)
PhD, Psychology & Cognitive Neuroscience
UC Riverside · Expected 2026
MSc, Psychology
Queen's University · 2020
Hon. BSc, Biological Sciences & Psychology
York University · 2017
Selected work
Each case study shows the question, method, tradeoff, and product implication, not just the final artifact.
01 · XR interaction / remote testbed
99.2% of gaze errors were slips; hand input reached 5.15 bits/s.
Built a remote testbed, compared hand and simulated gaze with Fitts' law and NASA-TLX, then modeled failure dynamics with a Bayesian LBA. The gaze condition was simulated, not evaluated in a headset.
02 · Human factors / proof of concept
Targeted ≤0.6 alerts/min with calibrated state probabilities.
Prototyped a training dashboard that turns pupil, HRV, and grip features into instructional thresholds. All validation used synthetic sessions; clinical effectiveness remains untested.
03 · Research roadmap / in progress
Separating evidence quality, response caution, and motor strain.
A staged dissertation program connecting psychophysics, pupillometry, drift-diffusion modeling, and grip-force signals. Industry applications shown in the case study are concepts, not deployed systems.
04 · Foundational research / NSERC
60+ participants across behavioral and EEG measures.
Led a master's thesis from study design through analysis. The findings come from a controlled research sample and should not be read as a general product-effectiveness claim.
Technical toolkit
I work across evaluation, measurement, inference, and implementation so the research question survives contact with the product.
Start a conversation
I am open to Research Scientist, Quantitative UXR, and Human Factors opportunities, especially with teams building adaptive, safety-critical, or immersive systems. Authorized to work in the U.S. without sponsorship.