Qianqian Fang

This paper develops an LLM interface for scientific simulations, achieving high accuracy and reproducibility in converting natural language descriptions to structured inputs for photon transport simulations.

NeuroCaptain v2 enables interactive 3D fNIRS optode design and registration with improved cross-subject placement consistency.

This paper introduces NeuroNavigatAR, an AR tool using facial landmarks and machine learning to improve headgear placement consistency in fNIRS and EEG studies.

The paper develops an open-source software pipeline to create 3-D printable neuroimaging head caps with anatomical landmarks for improved probe placement in functional neuroimaging studies.

The paper evaluates diffusion approximation (DA) accuracy in brain models by comparing it to mesh-based Monte Carlo (MMC) solutions, leading to updated CSF optical property recommendations.

The paper improves fNIRS analysis by developing a surface-based meshing pipeline for creating high-quality brain models, showing significant improvements in accuracy over existing methods.

The paper updates the Lead-DBS pipeline for DBS imaging and connectomics, demonstrating its application on clinical data and comparing preprocessing strategies.