Seyed Yahya Shirazi, Ph.D.

How integrating Claude Code into academic research workflows led to an 8x increase in output, and a 10-week course to help other researchers do the same.

A VLM-based image annotation system for the Annotation Garden ecosystem, providing collaborative annotation capabilities for static image datasets, starting with the Natural Scene Dataset (NSD).

The Annotation Garden Initiative (AGI) establishes an open infrastructure for collaborative, multi-layered annotation of stimuli used in neuroscience research, building on BIDS and HED standards.

Young and older adults show fundamentally different patterns of brain-muscle communication during perturbed recumbent stepping, revealing an age-related shift from flexible, error-driven control to a more constrained, stability-focused approach.

LSL synchronizes data across devices on LANs for neurophysiological research, offering easy, reliable multi-device integration and supporting diverse programming languages.

Comprehensive guide to digital signal processing techniques for ring-based wearable biosensors, covering theoretical foundations, filtering methods, and real-time implementation strategies.

A guide to health-specific evaluation metrics and frameworks for AI systems, focusing on clinical validity, FDA regulatory considerations, bias detection, safety evaluation, and practical implementation strategies.

A guide to statistical methods for evaluating models, including power analysis, mixed-effects models, bootstrap confidence intervals, multiple comparison corrections, and effect size calculations.

A guide to evaluating large language models (LLMs) using automatic metrics, LLM-as-judge paradigms, human-in-the-loop strategies, and domain-specific considerations.

A comprehensive guide to designing and implementing human evaluation frameworks and psychometric principles for AI systems, with practical algorithms and code snippets.

Interactive dashboard analyzing citation patterns and research impact of NEMAR (NeuroElectroMagnetic Archive and Tools Resource) datasets, featuring network analysis, temporal trends, and research theme identification.

This dashboard provides comprehensive insights into the Healthy Brain Network (HBN) EEG dataset, featuring demographics, task availability, and mental health correlations across all releases.

A comprehensive guide to building interactive dashboards in Hugo static sites using Chart.js, with best practices for data management and visualization.

Hyser is an open-access high-density surface EMG dataset with 256-channel recordings from 20 subjects performing hand gestures and finger force tasks, designed for neural interface and prosthetic control research.

A comprehensive guide to integrating Mermaid diagrams in Hugo static sites using partials, with practical examples and deployment strategies.

This paper challenges the misleading assumption that EEG channels reflect only local cortical activity by using ultrahigh-density ECoG data to demonstrate how cortical activity projects broadly across the scalp surface through volume conduction.

A guide to Python's built-in venv module with comparisons to Conda for research computing workflows

A guide to setting up and managing git-annex with Backblaze B2 storage for large files.

A unified framework for standardizing sensor placement across different sensing modalities and applications, providing precise anatomical landmarks, coordinate systems, and placement protocols with defined precision levels.

This paper presents the HBN-EEG dataset, a comprehensive and analysis-ready collection of high-density EEG recordings from the Healthy Brain Network project, formatted in BIDS with annotated behavioral and task-condition events, aimed at supporting EEG an…

HBN-EEG is a curated collection of high-resolution EEG data from over 3,000 participants aged 5-21 years, formatted in BIDS and annotated with Hierarchical Event Descriptors (HED).

Older adults use fewer muscles to drive a stepper during a seated locomotor task, demonstrating greater co-contraction and similar motor errors compared to young adults.

Innovative EEG system with dual electrodes and advanced signal processing for high-quality, noise-reduced biosignal capture and enhanced user comfort.

This paper shows, for the first time, that using a non-parametric functional muscle network can reliably characterize fatigue-related changes in synergistic muscle coordination and distribution of neural drive at the peripheral level.

Analysis of re-referencing methods for high-density EEG recordings and their impact on source estimation accuracy.

Muscle connectivity network based on information theory quantifies the role of sensory information on motor performance.

This paper shows, for the first time, that the functional muscle network can robustly differentiate vocal tasks, while classic muscle activation assessment fails to differentiate.

Investigating the role of sensory feedback in assistive motor control during desk cycling activities for improved user experience and rehabilitation outcomes.

We show that seated locomotor tasks can elicit perturbation-related cortical dynamics similar to walking.

This paper examines the reliability of EEG electrode digitizing methods using five different techniques, and the potential impact of digitization reliability on source estimation uncertainty.

This paper shows how fiducial mismarking can affect EEG source estimation. 2019 9th International IEEE/EMBS Conference on Neural Engineering (NER)