Resource Hub
Learn, Build, Experiment, and Collaborate
Our resources are intended for students, researchers, and collaborators
interested in brain–computer interfaces, multimodal artificial
intelligence, virtual reality, physiological sensing, human-centered
systems, and related application areas.
Datasets
Software
Tutorials
Reading Lists
Research Protocols
Student Guides
Data
Datasets
Curated datasets and benchmark collections related to EEG,
eye tracking, physiological sensing, emotion recognition,
human behavior, virtual reality, and multimodal learning.
EEG
Eye Tracking
Physiology
Multimodal Data
Development
Software & Code
Research prototypes, reusable code, signal-processing pipelines,
machine-learning baselines, experimental utilities, and software
components developed for laboratory studies.
Python
Machine Learning
Signal Processing
Open Source
Experimental Research
Protocols & Templates
Example experimental workflows, study-design templates,
data-collection checklists, participant forms, and documentation
structures for human-centered research.
Study Design
Data Collection
Reproducibility
Research Ethics
Learning
Tutorials & Technical Guides
Introductory and advanced guides covering EEG analysis,
multimodal fusion, virtual reality experiments, machine learning,
explainable AI, and research software workflows.
BCI
VR
AI
Data Analysis
Academic Development
Reading Lists
Selected papers, books, surveys, and foundational references
organized around the laboratory’s six research programs and
interdisciplinary application areas.
Foundational Papers
Surveys
Research Methods
Emerging Topics
Student Support
Student Research Guides
Practical guidance for starting a research project, selecting a topic,
reviewing literature, planning experiments, building prototypes,
evaluating results, and preparing scientific publications.
Project Planning
Thesis Preparation
Scientific Writing
Research Careers
Pathway 01
Brain Signals & BCI
Begin with basic neuroscience, EEG signal characteristics,
preprocessing, feature extraction, experimental design, and
classical machine-learning baselines.
Pathway 02
Multimodal AI
Learn how to synchronize, represent, fuse, and interpret data from
multiple sources such as EEG, gaze, physiology, behavior, speech,
and environmental sensors.
Pathway 03
Immersive Research
Explore virtual-reality development, interaction design,
experimental control, eye tracking, behavioral logging, and
physiological sensing in immersive environments.
Growing Collection
More Resources Are Coming
This resource hub is under active development. Future updates may
include downloadable datasets, code repositories, course materials,
experiment templates, recommended software stacks, laboratory
documentation, and curated research roadmaps.
Materials will be added gradually as they are reviewed, documented,
and prepared for public or educational use.
Contribute
Help Build the Resource Library
Students and collaborators may contribute tutorials, reusable code,
literature summaries, experimental tools, benchmark results, and
documentation that can support future research across the laboratory.
Contact the Lab