Puti Wen 温菩提
Neuroimaging Scientist | Research Infrastructure | MRI Analysis & Clinical Imaging Tools
Abu Dhabi, UAE pw1246@nyu.edu LinkedIn Interactive Portfolio
A somewhat unconventional neuroscientist. My Ph.D. was in visual neuroscience, but these days I spend most of my time building the infrastructure, pipelines, and practical software that keep brain-imaging projects moving: large MRI datasets, multiple-sclerosis research, and clinician-facing tools. I work comfortably across psychology, radiology, engineering, and clinical neurology, especially when a useful problem does not fit neatly inside one field.
Core Strengths
- Infrastructure
- XNAT, Slurm/Jubail HPC, Docker, Singularity/Apptainer, GitHub Actions, Box API
- Neuroimaging
- fMRIPrep, FreeSurfer, TractoFlow, MRIQC, BIDS, dcm2bids, DICOM, ANTs, SPM12, MELD/MAP18
- Programming
- Python, MATLAB, TypeScript/JavaScript, React Native, Next.js, Node.js/Express, Three.js, Supabase
Experience
Postdoctoral Fellow|NYU Abu Dhabi, Center for Brain and Health
– PresentResearch infrastructure & analysis
- Imaging data platform. Integrated and deployed leading open-source neuroimaging tools (fMRIPrep, MRIQC, TractoFlow, HCP, dcm2bids, and deep-learning visual-area segmentation) as containerized XNAT/HPC pipelines, so researchers can run them on their own data directly on the platform; also built two in-house pipelines (a BIDS-to-HCP converter and the ARI validator), plus automated data curation and QA, a nightly validation dashboard, XNAT-to-Box backup, and the documentation the imaging team relies on.
- Scanner-upgrade QC. Ran cross-scanner QC (SNR/tSNR/CNR) across Siemens CIMA.X and Prisma systems in Germany, NYUAD, and UAEU; the comparison report supported NYUAD's decision to upgrade to the CIMA.X.
- Normative brain dashboard. Processed 9,000+ HCP and ADNI subjects into an age- and sex-referenced dashboard with an upload-and-compare interface.
- Stimulus-computer migration. Rebuilt the CBH MRI stimulus setup from Intel to Apple Silicon: ported and tested active experiments, created reusable templates, and restored EyeLink, VPixx, and ProPixx integration.
- MS imaging analysis. Co-led tract-based quantitative MRI across 27 white-matter pathways, testing whether lesion location and tissue composition predict disability beyond total lesion load.
- Cross-department fMRI support. Co-authored an Engineering EEG-fMRI brain-computer interface (BCI) study of how the brain's hand representation reorganizes as users learn to control a supernumerary robotic thumb by motor imagery before and after training.
- Training & support. Trained 10+ researchers across fMRI, diffusion, vision, biobank, genetics, and MS projects; resolved 25+ reported data-validation and pipeline issues; built afqView, a BIDS-aware browser app for reviewing tractography across 116 subjects.
Clinical imaging tools & support
- LesionView. Built longitudinal lesion review and clinician-facing HTML/PDF report generation for new and enlarging MS lesions; migrated the original MATLAB prototype to a browser-based app and iterated weekly with Yas Clinic neurologists. Co-inventor on a provisional patent application (NYU Ref. ABD01-03).
- CvsView. Built central-vein-sign and paramagnetic-rim-lesion review tooling; corrected SWI-FLAIR registration artifacts through relabeling, developed a LightGBM classification workflow, and containerized the tool for internal research evaluation and clinician review, piloted with Harley Street Medical Centre.
- Brain-atrophy pipeline. Built for internal research review and reporting in collaboration with Yas Clinic clinicians; also ran FLAIR* central-vein-sign processing for Harley Street Medical Centre and Cleveland Clinic Abu Dhabi.
- Epilepsy MRI. Supported CCAD using MELD and in-house MAP18/VBM against a 1,618-subject reference dataset; produced reports and joined multidisciplinary case review.
- Presurgical fMRI. Supported task-language mapping for an AVM case, from acquisition and processing through analysis and clinical review.