Ingi Páll Eiríksson

Skills

Human–AI interaction, explainable AI, calibrated trust and reliance, transparency controls, progressive disclosure, experimental design, user studies, usability testing, task analysis, cognitive walkthroughs, mixed-methods research, interview design, survey design, thematic analysis, behavioral data analysis, psychophysiology in HCI, respiration sensing and feature extraction, signal preprocessing and smoothing, time-series analysis, Python, Pandas, NumPy, SciPy, scikit-learn, Jupyter, statistical modeling, regression and GLM, mixed-effects models, ANOVA, effect size and power analysis, data visualization, Matplotlib, reproducible research, preregistration and open science, reliability and validity assessment, factor analysis, A/B testing, instrumentation and logging, user modeling, prototype design, rapid and high-fidelity prototyping, web-based experiment development, JavaScript/TypeScript, React, Tailwind CSS, ShadCN UI, SQL, PostgreSQL, Supabase, RESTful APIs, Git and version control, technical writing, academic writing and peer review, ethics and participant safety, IRB-style compliance, classroom teaching and communication, cross-functional collaboration, project planning and documentation.

About

I’m an HCI researcher with a strong interest in Human–AI interaction. I finished my MSc in Human-Computer Interaction at Utrecht University, graduating cum laude. In my thesis I looked at how breathing patterns reflect emotion during web tasks and combined a breathing sensor with self-reports. That project sharpened my experimental design and Python data skills and got me focused on trust, transparency, and calibrated reliance in AI-supported systems.

My background mixes psychology and computer science. I hold BS degrees in both from the University of Iceland with first class honors. That mix helps me frame questions about behavior and then build or evaluate the systems that answer them.

I have classroom experience from teaching at the primary level where I handled planning, parent communication, and introduced basic programming. It taught me to explain ideas clearly, stay organised, and work well with different stakeholders.

I’m most interested in Human–AI interaction, user modeling with physiological signals, and data-informed UX for learning and decision support. I have experience working with Python, Pandas, NumPy, Jupyter, SQL, and standard HCI methods from study design to usability testing. I like projects where I can move from a clear research question to a tested prototype and share results in a way a whole interdiciplanary team can understand.