Technical Skills & Methodologies

I specialize in a multi-modal approach to understanding human behavior, combining rigorous experimental design with advanced data analysis and physiological measurement. Below is a summary of my core competencies.

💡 See concrete applications of these skills in my Portfolio case studies.

🔬 Research & Experimental Design

  • User Research: End-to-end research planning, psychophysics, usability testing, survey design, A/B testing, user interviews.
  • Interaction Design Principles: Applying cognitive science principles to inform the design of intuitive and effective user interfaces, including adaptive systems that respond to user state.
  • Human Factors: Assessing user performance and cognitive load in dual-task and high-stress environments.
  • Experiment Programming: Designing and implementing precise behavioral and perceptual tasks using PsychToolbox (MATLAB) and web-based platforms (React/TypeScript).
  • Pre-registration & Open Science: Developing comprehensive pre-registered study designs with detailed hypotheses, exclusion criteria, and analysis plans. Implementing rigorous experimental protocols with Williams counterbalancing and equivalence testing.
  • Fitts’s Law & Human-Computer Interaction: Implementing ISO 9241-9 compliant Fitts’s Law paradigms for evaluating input modalities, with expertise in projected error calculation and throughput metrics.

💻 Programming & Data Science

  • Languages: R (Expert), MATLAB (Expert), TypeScript/JavaScript (Proficient), SQL (Proficient), Python (Familiar), Bash (Familiar).
  • Web Development: React 18, TypeScript, Vite, modern frontend development, event-driven architectures, real-time data synchronization, precise timing control (performance.now() for psychophysics).
  • Statistical Modeling: Linear Mixed-Effects Models (LMMs), Bayesian Analysis, Psychometric Function Fitting, Drift-Diffusion Modeling (DDM) with integration of physiological measures (pupillometry).
  • Machine Learning: XGBoost, Feature Engineering, Cross-Validation, Hyperparameter Tuning, Predictive Modeling, Real-time ML Pipelines, Model Calibration (Platt scaling), Anomaly Detection (Isolation Forest).
  • Data Analysis & Visualization (R): Tidyverse (dplyr, ggplot2), R Markdown, Shiny (Interactive Dashboards), gt Tables, Real-time Data Streaming.
  • Development & Version Control: Git, GitHub, Google Cloud Platform (GCP), Docker, CI/CD Workflows, Production Deployment (ShinyApps.io, Vercel, Netlify).

🧠 Physiological & Neuroimaging Methods

  • Pupillometry: Real-time analysis of pupil dilation as a biomarker for cognitive load and arousal. Computational modeling linking pupillometric dynamics with decision-making processes (DDM integration).
  • Electroencephalography (EEG): Collection, preprocessing, and analysis of EEG data, including sleep scoring.
  • Neuroimaging Analysis: Analyzing Diffusion MRI (dMRI) data using toolkits such as FSL, QSIPrep, and SPM12.
  • Gaze Tracking & Eye Movement Analysis: Implementing gaze-based input systems, physiologically-accurate gaze simulation, and analyzing eye movement patterns for cognitive load assessment.

⚡ Real-time Systems & Production Applications

  • Real-time Analytics: Multi-modal cognitive state monitoring systems with <1s latency, live data streaming, and interactive dashboards.
  • Production ML: End-to-end ML pipelines with causal feature engineering, model calibration, and deployment-ready applications.
  • Interactive Applications: Shiny dashboards with real-time updates, threshold policy sandboxes, and explainable AI interfaces.
  • Extended Reality (XR) Platforms: Building research-grade XR experimental platforms with adaptive modality systems, dual input methods (gaze and hand-tracking), real-time performance monitoring, and comprehensive data logging for cognitive load studies.
  • System Architecture: Docker containerization, CI/CD workflows, and scalable deployment strategies for research and clinical environments. Event-driven architectures with pub/sub systems for inter-component communication.

🏥 Applied Research & Industry Experience

  • Biomedical Engineering: Real-time analytics platforms, surgical performance monitoring, medical device data analysis.
  • Applied Psychology: Cognitive state prediction, performance optimization in high-stakes environments.
  • Human-Computer Interaction: Adaptive interface design, modality switching systems, cognitive load-aware UI interventions, and evaluation of input methods using psychophysical paradigms (Fitts’s Law).
  • Mixed-Methods Research: Combining behavioral, physiological, and self-report measures (e.g., NASA-TLX) for comprehensive insights into cognitive performance and user experience.

🛠️ Project Management & Writing

  • Project Management: Notion, Slack, Quire.
  • Scientific & Technical Writing: Quarto, LaTeX, Markdown (Obsidian), MS Office.
  • Languages: Persian (Native), English (Proficient), French (Basic).
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