Curriculum Vitae

Travis
Beckwith

Neuroimaging scientist with 15+ years developing multimodal MRI analysis pipelines and open-source neuroimaging tools — from childhood lead exposure and air pollution to sports neurotrauma, structural connectomics, and AI model development.

01

Professional Summary

Principal neuroimaging analyst for three NIH-funded longitudinal cohorts, providing technical expertise in fMRI, diffusion MRI (DTI, CSD, NODDI), MRS, and volumetric analysis across interdisciplinary research teams. Developer of open-source neuroimaging tools including an integrated diffusion MRI processing and structural connectomics pipeline with ML-enhanced registration, a multi-modal DICOM-to-BIDS conversion tool, and a hardware diagnostic utility for neuroimaging computing environments. Certified Siemens 3T Prisma scanner operator with hands-on experience in data acquisition, protocol implementation, and quality assurance. Proficient in FSL, MRtrix3, AFNI, FreeSurfer, ANTs, SPM, and fMRIPrep, with demonstrated experience deploying containerized workflows on SLURM-based HPC infrastructure and managing BIDS-formatted datasets. Experienced in deploying pre-trained deep learning models for neuroimaging applications, with growing expertise in machine learning and computational approaches to brain imaging.

fMRI Diffusion MRI CSD NODDI Connectomics MRS fMRIPrep FSL MRtrix3 AFNI FreeSurfer ANTs BIDS SLURM / HPC Docker / Singularity Python TensorFlow R MATLAB
02

Research Interests

Neuroimaging Methods & Pipeline Development

Design, optimization, and validation of multimodal MRI analysis workflows for structural, functional, diffusion, and microstructural imaging, including structural connectomics and advanced diffusion modeling.

Brain–Behavior Relationships

Neural mechanisms underlying cognitive and behavioral outcomes across environmental health, neurotrauma, and clinical populations.

Applied Neuroscience & Computational Approaches

Integration of machine learning, deep learning, and emerging analytic techniques into neuroimaging pipelines and research workflows.

03

Software & Tools

Open-source neuroimaging tools spanning the research workflow from hardware validation through data conversion to advanced diffusion analysis. All projects published with documentation on GitHub.

dwiforge

Bash / Python  ·  v1.5-ml-enhanced

End-to-end diffusion MRI processing with ML-enhanced registration, CSD tractography, structural connectome construction, and NODDI microstructure modeling for BIDS-formatted datasets.

  • SynthMorph / VoxelMorph / ANTs registration with automatic method selection and GPU acceleration
  • 10M-streamline CSD tractography with SIFT2 filtering and Desikan-Killiany connectomes
  • Four connectome weightings: streamline count, FA, length, SIFT2
  • NODDI microstructure estimation (NDI, ODI, FWF) via AMICO
  • Checkpoint-based resumption and comprehensive QC reporting (text, HTML, JSONL)

GitHub Repository →

bids-convert

Bash / Python

Configurable multi-modal DICOM-to-BIDS conversion with parallel processing, source archival, metadata enrichment, and full BIDS scaffold generation.

  • Supports anat, func, dwi, fmap, perf, and PET modalities
  • Pattern-matching configuration for flexible DICOM folder mapping
  • JSON sidecar enrichment and full BIDS scaffold (dataset_description.json, participants.tsv, README, CHANGES)
  • Parallel conversion, dry-run mode, and safe deletion with verification

GitHub Repository →

NeuroRig

Python  ·  WSL2 optimized

Lightweight diagnostic utility assessing hardware readiness for neuroimaging processing pipelines (FreeSurfer, fMRIPrep, FSL, AFNI).

  • RAM capacity, disk I/O benchmarking, and NVIDIA CUDA GPU detection
  • WSL2-specific resource allocation verification
  • Interpretive output with actionable recommendations mapped to neuroimaging workload requirements

GitHub Repository →

04

Professional Experience

May 2025–
Present
MetaBrain Labs Inc.
Neurotechnology Adviser
  • Provide research methodology and neuroscience consultation to an early-stage neurotechnology startup developing an AI-powered cognitive performance platform.
  • Led research methodology design for pilot study protocol, including study design, outcome measure selection, and human subjects research considerations.
2024–
Present
Independent / Open Source
Neuroimaging Software Development
  • Designed and built an integrated diffusion MRI processing pipeline incorporating ML-enhanced registration (SynthMorph, VoxelMorph, ANTs), CSD tractography, SIFT2 filtering, connectome construction, and NODDI microstructure modeling.
  • Developed a configurable multi-modal DICOM-to-BIDS conversion tool with parallel processing, source archival, metadata enrichment, and full BIDS scaffold generation.
  • Built a Python hardware diagnostic utility for neuroimaging computing environments with WSL2-specific support.
  • Published all tools with comprehensive documentation on GitHub.
Sep 2024–
Present
Outlier AI
Subject Matter Expert
  • Contribute domain expertise in neuroscience and biomedical sciences to AI model development through content creation, quality evaluation, and multimodal training initiatives.
  • Author expert-level scientific prompts and custom evaluation rubrics testing AI reasoning across STEM domains.
  • Achieved "Oracle" contributor status recognizing sustained high-quality performance across 10+ projects over 14-month tenure.
2023–2024
Indiana University, Bloomington — Clinical Neurotrauma Lab
Postdoctoral Research Fellow
  • Developed and executed task-based fMRI analysis pipeline using fMRIPrep and AFNI for N-back working memory paradigm in longitudinal sports injury cohort.
  • Deployed containerized fMRIPrep workflows via Singularity on SLURM, managing BIDS-formatted datasets and batch processing.
  • Acquired neuroimaging data as certified Level 1 MRI scanner operator on Siemens 3T Prisma.
  • Led manuscript preparation examining ADHD as a moderating variable in cognitive outcomes following subconcussive head impacts.
  • Began independent development of advanced diffusion MRI processing pipeline incorporating CSD, NODDI, structural connectomics, and ML-enhanced registration.
  • Trained graduate students on neuroimaging software, command-line fundamentals, and analysis procedures.
2018–2021
University of Cincinnati College of Medicine — Dept. of Environmental Health
Postdoctoral Research Fellow
  • Served as principal neuroimaging analyst for three concurrent NIH-funded longitudinal cohorts, developing multimodal pipelines for structural MRI, fMRI, DTI, and MRS data.
  • Managed neuroimaging data workflows from scanner acquisition through DICOM server to HPC processing, including DICOM-to-NIfTI conversion and BIDS-compliant dataset organization.
  • Designed and standardized quality control procedures across multimodal datasets including QC summary reports, outlier flagging, and subject-level documentation.
  • Independently initiated cortical thickness analysis approach for air pollution cohort, resulting in first-author publication and CCHMC annual research report recognition.
  • Authored and co-authored six peer-reviewed publications on environmental impacts on brain development.
2015–2017
Cincinnati Children's Hospital Medical Center — Imaging Research Center
Postdoctoral Research Fellow
  • Provided neuroimaging analysis expertise for interdisciplinary projects using structural MRI, DTI, MRS, and fMRI across multiple concurrent studies.
  • Evaluated and compared neuroimaging analysis tools and preprocessing approaches (e.g., FSL vs. Tortoise for diffusion, ANTs for registration, atlas selection) to inform methodological decisions.
  • Served as primary methodological resource for software and pipeline selection, advising PIs on tool suitability.
  • Authored technical documentation for MRI_Analysis_Calculator ImageJ plugin adopted for ongoing lab use.
2008–2015
University of Cincinnati College of Medicine — Neuroscience Graduate Program
Graduate Research Assistant
  • Led multiple research projects investigating childhood lead exposure effects on neurodevelopment using multimodal MRI.
  • Developed standardized templates and automated batch processing procedures for rodent MRI data.
  • Co-authored five peer-reviewed publications, two review articles, and one book chapter.
05

Education

Ph.D., Neuroscience
University of Cincinnati, Cincinnati, OH
2008–2015
Dissertation: "A Magnetic Resonance Imaging Study of the Developmental Consequences of Childhood Lead Exposure in Adulthood"
B.A., Psychology & Neuroscience  |  B.F.A., Creative Writing & English
Bowling Green State University, Bowling Green, OH
2001–2007
Graduated cum laude with University and English Honors
Additional Training
Post-Baccalaureate Certificate — Clinical and Translational Research
University of Cincinnati College of Medicine
2018–2019
Preparing Future Faculty Program
University of Cincinnati
2012–2013
CONN Toolbox Functional Connectivity Workshop
Neuroimaging Methods Training
2015
06

Technical Skills

Neuroimaging Platforms

FSL (incl. MELODIC) · MRtrix3 · AFNI · SPM (incl. CAT12) · FreeSurfer · ANTs · fMRIPrep · AMICO · CONN · ImageJ

Modalities

fMRI (task-based & resting-state) · Diffusion MRI (DTI, CSD, multi-shell) · NODDI microstructure modeling · MRS · Structural/Volumetric · Surface-based morphometry · Structural connectomics

Analysis Methods

CSD tractography (multi-tissue, single- & multi-shell) · SIFT2 streamline filtering · NODDI estimation (NDI, ODI, FWF) · Atlas-based connectome construction · Multi-weighted connectivity matrices · Cortical thickness & surface area · Volumetric segmentation · Resting-state connectivity (ICA) · Brain-behavior correlation · Longitudinal progression tracking

Programming & Scripting

Python (TensorFlow, nibabel, AMICO, NumPy, scikit-learn) · R · MATLAB · Bash/Shell scripting (advanced) · SAS

Machine Learning & Deep Learning

Deployment of pre-trained deep learning models for neuroimaging registration (SynthMorph, VoxelMorph) · GPU-accelerated inference (CUDA/TensorFlow) · Automated method selection with quality-based fallback logic

Statistical Methods

GLM · Mixed/multilevel models · Longitudinal analysis · Multiple comparisons correction · Multivariate approaches · Machine learning

Data Management & Reproducibility

BIDS format specification · BIDS scaffold generation & metadata enrichment · Multi-modal DICOM-to-BIDS conversion tooling · Git/GitHub · Docker · Singularity/Apptainer · Checkpoint-based pipeline resumption · Structured logging (text, HTML, JSONL) · SLURM

Computing Environment

High-performance computing (SLURM) · Containerized pipeline deployment · WSL2 · NVIDIA GPU computing environments · Hardware benchmarking for neuroimaging workloads

MRI Operations

Siemens 3T Prisma (Level 1 certified, 2023) · syngo platform · Protocol implementation · Human subjects scanning

07

Publications

Peer-Reviewed Journals
Beckwith, T.J., Dietrich, K.N., Wright, J.P., Altaye, M. and Cecil, K.M.
Criminal arrests associated with reduced regional brain volumes in an adult population with documented childhood lead exposure.
Environmental Research, 201, p.111559 (2021)  ·  DOI
Beckwith, T., Cecil, K.M., Altaye, M., Severs, R., Wolf, C., Percy, Z., Maloney, T., Yolton, K., LeMasters, G., Ryan, P.H.
Reduced Cortical Thickness Associated with Traffic-Related Air Pollution in a Longitudinally Studied Pediatric Cohort.
PLoS One 15 (1), e0228092 (2020)  ·  DOI
Fleck, D.E., Eliassen, J.C., Guerdjikova, A.I., ... Beckwith, T., et al.
Effect of Lisdexamfetamine on Emotional Network Brain Dysfunction in Binge Eating Disorder.
Psychiatry Research: Neuroimaging 286, 53–59 (2019)  ·  DOI
Brunst, K.J., Ryan, P.H., Altaye, M., Yolton, K., Maloney, T., Beckwith, T., LeMasters, G., Cecil, K.M.
Myo-inositol mediates the effects of traffic-related air pollution on generalized anxiety symptoms at age 12 years.
Environmental Research 175, 71–78 (2019)  ·  DOI
Raghubar, K.P., Lamba, M., Cecil, K., Yeates, K.O., Mahone, E.M., Limke, C., Grosshans, D., Beckwith, T.J., Ris, M.D.
Dose-volume Metrics and their Relation to Memory Performance in Pediatric Brain Tumor Patients: A Preliminary Study.
Pediatric Blood & Cancer 65, e27245 (2018)  ·  DOI
Beckwith, T.J., Dietrich, K.N., Wright, J.P., Altaye, M., Cecil, K.M.
Reduced Regional Volumes Associated with Total Psychopathy Scores in an Adult Population with Childhood Lead Exposure.
NeuroToxicology 67, 1–26 (2018)  ·  DOI
Lindquist, D.M., Beckwith, T., Cecil, K.M., et al.
Prenatal and Early Postnatal Lead Exposure in Mice: Neuroimaging Findings.
Quantitative Imaging in Medicine and Surgery 5 (4), 511–518 (2015)  ·  DOI
Webber, E.S., Mankin, D., McGraw, J., Beckwith, T.J., Cromwell, H.C.
Ultrasonic Vocalizations, Predictability and Sensorimotor Gating in the Rat.
Behavioural Brain Research 253, 32–41 (2013)  ·  DOI
Gitelman, D., Klein-Gitelman, M.S., Ying, J., ... Beckwith, T., et al.
Brain Morphometric Changes Associated with Child-Onset Systemic Lupus Erythematosus and Neurocognitive Deficit.
Arthritis & Rheumatism 65 (8), 2190–2200 (2013)  ·  DOI
Webber, E.S., Harmon, K.M., Beckwith, T.J., Peña, S., Burgdorf, J., Panksepp, J., Cromwell, H.C.
Selective Breeding for 50 kHz Ultrasonic Vocalization Emission Produces Alterations in the Ontogeny and Regulation of Rough-and-Tumble Play.
Behavioural Brain Research 229 (1), 138–44 (2012)  ·  DOI
Harmon, K.M., Greenwald, M., Beckwith, T.J., McFarland, A.M., Cromwell, H.C.
The Effects of Prenatal Stress on Motivation in the Rat Pup.
Stress 12 (3), 250–8 (2009)  ·  DOI
Book Chapters & Reviews
Cecil, K.M., Beckwith, T.J.
A Toxicological Model of Frontal Lobe Injury: Childhood Lead Exposure. In: Frontal Lobe: Anatomy, Functions and Injuries. Nova Science Publishers, 57–78.
Book Chapter (2013)
Beckwith, T., Cecil, K.M.
Acquired White Matter Injury: Infection and Inflammatory Processes.
Journal of Pediatric Neuroradiology 2 (1), 97–108 (2013)  ·  DOI
Cecil, K.M., Beckwith, T.
Advanced Magnetic Resonance Techniques for Evaluating White Matter.
Journal of Pediatric Neuroradiology 2 (1), 3–15 (2013)  ·  DOI
Manuscripts in Preparation
Beckwith, T., Nowak, M., Kawata, K.
Role of ADHD Diagnosis on Working Memory Before and After Repetitive Subconcussive Head Impacts: A Pilot Study
In preparation
Beckwith, T.
An Integrated Pipeline for Diffusion MRI Processing, ML-Enhanced Registration, Structural Connectomics, and NODDI Microstructure Modeling
In preparation · Target: JOSS / Frontiers in Neuroinformatics
08

Selected Presentations

14 additional conference abstracts and posters presented at major scientific meetings (2012–2019). Complete list available upon request.

09

Teaching & Training

2015–2024
Multiple institutions
Neuroimaging Methods Training
  • Individual and small-group training for graduate and summer research students on FSL, AFNI, FreeSurfer, and ImageJ.
  • Authored technical processing manual for MRI_Analysis_Calculator ImageJ plugin, standardizing procedures for lab use.
  • Provided ongoing methodology consultation on analysis approaches, software selection, and data management.
2011–2013
University of Cincinnati / Howard Hughes Medical Institute — ExSEL Program
Teaching Assistant
  • Developed and delivered STEM curriculum including presentations, lab exercises, and interactive activities for 20 high school students.
  • Mentored and supervised 4 graduate teaching assistants on classroom management and teaching strategies.
10

Honors & Awards

11

Service & Leadership

Grant Review Ad Hoc Manuscript Reviewer

Environment International  ·  NeuroImage  ·  Physiology & Behavior  ·  Psychiatry Research: Neuroimaging  ·  The Lancet Planetary Health

Professional Affiliations

Indiana Academy of Science  ·  Society for Neuroscience