Model behavior
- Psychophysics & signal detection
- Bayesian DDM / LBA
- Mixed-effects models
- ML, calibration & SHAP
Available Summer / Fall 2026
Research Scientist · Quantitative UXR · Human Factors
Designing better human-machine interaction
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.
Selected work
Research that changes what a system does
Each case study shows the question, method, tradeoff, and product implication, not just the final artifact.
01 · XR interaction / remote testbed
Why gaze produced more selection errors
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
Designing alerts around cognitive risk
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
Locating the failure point in dual-task performance
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
Testing whether brief meditation changes memory
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
Methods selected for the decision
I work across measurement, inference, and implementation so the research question survives contact with the product.
Measure latent state
- Pupillometry & eye tracking
- Grip-force & tremor analysis
- EEG & psychophysiology
- Artifact control & QC
Make it testable
- React / TypeScript systems
- R Shiny dashboards
- Python, R, PyMC & Stan
- Reproducible workflows
Start a conversation
Need rigorous research that ships?
I am exploring Research Scientist, Quantitative UXR, and Human Factors roles for Summer / Fall 2026, especially with teams building adaptive, safety-critical, or immersive systems.