Skills
Research Methods
Statistics & Modeling
Programming
XR / HCI
Detailed methodology notes for technical reviewers below
This page describes how the Research program is implemented—methods, workflow, and computation—not a generic résumé. The dissertation toolkit fills the sections below; XR and interaction methods are grouped at the end as adjacent work.
Core research methods
Psychophysics
Design and analysis of auditory and visual same–different discrimination (and related tasks) under load; linking physical effort to sensitivity, bias, and dynamics.
Pupillometry
Preprocessing and quality control (blinks, artifacts, valid samples); window-specific validity; gap-aware handling of missing samples.
Interpretation
Pupil measures inform arousal and effort hypotheses; behavior and formal models remain primary for inference (aligned with Research).
Experimental design and data collection
Handgrip dual-task paradigm
Concurrent physical effort (graded isometric grip) with cognitive and perceptual tasks, including same–different discrimination and memory components as required.
Within-subject structure and preregistration
Factorial and repeated-measures layouts; counterbalancing of orders and conditions. Where studies are preregistered, analyses follow registered hypotheses, exclusions, and plans.
Lab implementation
MATLAB and PsychToolbox for stimulus delivery and responses; calibration and exclusion rules documented in materials.
Modeling and statistical inference
Psychometric function modeling
Separate effects on perceptual evidence versus criterion under physical effort and load.
Mixed-effects models
LMMs and GLMMs in R (lme4, emmeans) for repeated measures and individual differences, aligned with the dual-task roadmap.
Hierarchical Bayesian Wiener DDM (dissertation)
Trial-level decomposition (drift rate, boundaries, non-decision time); implemented with brms and Stan (CmdStan-class) workflows. Scope and caveats—non-decision time constrained by design; pupil–parameter links exploratory—are stated on Research.
Model scrutiny
Sensitivity analyses, alternative specifications, model comparison, and interval- or equivalence-style reasoning where relevant.
The XR case study uses hierarchical Bayesian LBA in PyMC for verification-phase RTs after target entry. That framework is separate from the dissertation Wiener DDM and is not interchangeable with it.
Programming and research computing
R
tidyverse, ggplot2; mixed models; brms and Stan interfaces; Quarto for analyses and this site.
MATLAB
PsychToolbox for experiment control.
Version control
Git and GitHub for versioned scripts and reproducible layout.
Scientific communication and reproducibility
Reproducible reports
Quarto and R Markdown (legacy) so tables and figures rebuild from code.
Writing and rigor
LaTeX for manuscripts; exploratory versus confirmatory reporting kept distinct where both apply.
Traceability
README notes, pinned dependencies where used, and QC logs for pupillometry and behavioral pipelines.
Additional and adjacent methods
Hand versus gaze interaction (portfolio / preprint)
arXiv:2603.15991 · case study. Adjacent to the dissertation; adds HCI- and XR-relevant breadth.
- Web task: React and TypeScript; remote sessions; display calibration and session checks across devices.
- Design: ISO 9241-9–style multidirectional tapping; Fitts difficulty and throughput; Williams block counterbalancing; NASA-TLX workload.
- Gaze proxy: physiologically informed gaze simulation (latency, jitter, saccadic suppression) for gaze versus hand comparison without lab eye-tracking.
- Policy-triggered adaptive UI: declutter (gaze) and width inflation (hand). In the analyzed data, only declutter executed and was evaluable (modest timeout reduction; slips still dominated gaze errors). Hand width inflation was not evaluable—targets did not scale in the UI (integration bug); that policy is not validated here.
- LBA fits: Python and PyMC for verification-phase RTs only—see the note under Modeling above.
Other secondary experience: surgeon dashboard (R Shiny, XGBoost); EEG thesis; imaging collaborations under Publications; SST role on About.
Languages
Persian — Native English — Professional French — Basic