Travis
Beckwith
Neuroscientist with 15+ years in neuroimaging, environmental health, and quantitative methods — from childhood lead exposure and air pollution to sports neurotrauma, structural connectomics, and AI model development.
Professional Summary
Neuroscientist with 15+ years of experience in neuroimaging, environmental health, and quantitative methods, with additional expertise in epidemiology and clinical and translational research. Applied experience in AI model development, adversarial testing, and neurotechnology consultation, with complementary skills in machine learning, open-source software development, and data pipeline engineering developed through independent research and hands-on tool-building. Principal neuroimaging analyst for three NIH-funded longitudinal cohorts. Author of 11 peer-reviewed publications, including three first-author papers with documented impact across national media and legal and policy contexts. Developer of publicly released open-source neuroimaging tools spanning pipeline automation, data standardization, and hardware diagnostics. Proven ability to translate research into practical tools, publications, and real-world impact across academic, clinical, and industry settings.
Research & Professional Interests
Brain–Behavior Relationships
Neural mechanisms underlying cognitive and behavioral outcomes across environmental health, neurotrauma, and clinical populations.
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.
Applied Neuroscience & Computational Approaches
Integration of machine learning, deep learning, and emerging analytic techniques into neuroimaging pipelines and research workflows.
Translational Neuroscience
Application of neuroimaging and epidemiological research to clinical practice, public health, and neurotechnology development.
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 · v2
End-to-end diffusion MRI processing and structural connectivity pipeline with DESIGNER2-based preprocessing, ML-enhanced registration, SS3T-CSD tractography, structural connectome construction, and NODDI microstructure modeling for BIDS-formatted datasets.
- DESIGNER2-based preprocessing including topup, eddy, and Rician denoising
- ML-enhanced T1w-to-DWI registration with automatic selection between SynthMorph, VoxelMorph, and ANTs, GPU-accelerated inference, and quality-based fallback logic
- 10M-streamline SS3T-CSD tractography with SIFT2 filtering and Desikan-Killiany connectomes (streamline count, mean FA, mean length)
- NODDI microstructure estimation (NDI, ODI, FWF) via AMICO with cross-version compatibility handling
- Two-level checkpoint system for safe pipeline resumption and automated per-subject QC reporting (multi-page PDF with slice mosaics, metrics table, and connectome matrix)
- Configurable multi-drive storage architecture for HPC and local environments including WSL2
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 with automatic folder detection
- Pattern-matching configuration for flexible, user-editable DICOM folder mapping
- JSON sidecar enrichment and full BIDS scaffold (dataset_description.json, participants.tsv, README, CHANGES, .bidsignore)
- Parallel conversion, dry-run mode, and safe deletion with verification
- Designed for integration with bids-validator for post-conversion compliance checks
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
Additional tools in active development: a mediation analysis package for MRI data (neuromediate), a microstructural diffusion mapping tool (NERVES), and an ML-based survey analysis package (surveykit-ml).
Professional Experience
- Provide research methodology and neuroscience consultation to an early-stage neurotechnology startup developing an AI-powered cognitive performance platform serving elite sports teams.
- Led research methodology design for pilot study protocol, including study design, outcome measure selection, and human subjects research considerations.
- Advise on integration of neuroscience principles, cognitive behavioral methodologies (cognitive restructuring, belief reframing), and EEG-based neurofeedback systems into product development.
- Design data collection protocols and translate research findings for academic publications and commercial stakeholders.
- Design frontier-level adversarial prompts targeting model failure in neuroscience, biology, clinical medicine, pharmacology, and broader STEM domains; validate failure modes and generate evaluation rubrics specifying reward criteria and accuracy standards.
- Test agentic AI systems for domain knowledge failures and reasoning errors across multi-step tasks in neuroscience and biomedical contexts.
- Review AI model outputs and contributor-generated content for scientific accuracy, providing task-level feedback to quality managers.
- Achieved "Oracle" contributor status recognizing sustained high-quality performance across 10+ projects over a 14-month tenure.
- Designed and built an integrated diffusion MRI processing and structural connectivity pipeline for BIDS-formatted datasets, incorporating DESIGNER2-based preprocessing, ML-enhanced registration (SynthMorph, VoxelMorph, ANTs), SS3T-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 and archived on Zenodo.
- Led statistical analysis and manuscript preparation for a pilot study examining ADHD diagnosis as a moderating variable in cognitive outcomes following repetitive subconcussive head impacts.
- Developed and executed a task-based fMRI analysis pipeline using fMRIPrep and AFNI for an N-back working memory paradigm in a longitudinal sports injury cohort.
- Deployed containerized fMRIPrep workflows via Singularity on SLURM, managing BIDS-formatted datasets and batch processing.
- Acquired neuroimaging data as a certified Level 1 MRI scanner operator on Siemens 3T Prisma, including protocol implementation and quality assurance.
- Began independent development of an 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.
- Served as principal neuroimaging analyst for three concurrent NIH-funded longitudinal cohorts (Cincinnati Lead Study, CCAAPS, HOME Study), 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 a cortical thickness analysis approach for the air pollution cohort, resulting in a first-author publication and CCHMC annual research report recognition.
- Authored and co-authored six peer-reviewed publications on environmental impacts on brain development.
- 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 the MRI_Analysis_Calculator ImageJ plugin, adopted for ongoing lab use.
- 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.
Education
Technical Skills
FSL (incl. MELODIC) · MRtrix3 · DESIGNER2 · AFNI · SPM (incl. CAT12) · FreeSurfer · ANTs · fMRIPrep · AMICO · CONN · ImageJ · E-Prime · PsychoPy
fMRI (task-based & resting-state) · Diffusion MRI (DTI, CSD, multi-shell) · NODDI microstructure modeling · MRS · Structural/Volumetric · Surface-based morphometry · Structural connectomics · FDG-PET/CT (limited experience)
CSD tractography (multi-tissue, single- & multi-shell) · SIFT2 streamline filtering · NODDI estimation (NDI, ODI, FWF) · Atlas-based connectome construction (Desikan-Killiany) · Multi-weighted connectivity matrices · Cortical thickness & surface area · Volumetric segmentation · White matter tractography (deterministic & probabilistic) · Resting-state connectivity (ICA) · Brain-behavior correlation · Longitudinal progression tracking · Quality assurance/QC
Python (TensorFlow, nibabel, AMICO, NumPy, scikit-learn) · R · MATLAB · Bash/Shell scripting (advanced: associative arrays, parallel job execution, configurable pattern matching) · SAS
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 · Integration of ML components into production Bash pipelines
GLM · Mixed/multilevel models · Longitudinal analysis · Multiple comparisons correction · Multivariate approaches · Machine learning
BIDS format specification · BIDS scaffold generation & metadata enrichment · Multi-modal DICOM-to-BIDS conversion tooling (dcm2niix integration) · Git/GitHub · Docker · Singularity/Apptainer · Checkpoint-based pipeline resumption · Structured logging (text, HTML, JSONL) · Data documentation & SOPs
High-performance computing (SLURM) · Containerized pipeline deployment · WSL2 · NVIDIA GPU computing environments · Hardware benchmarking for neuroimaging workloads
Siemens 3T Prisma (Level 1 certified, 2023) · syngo platform · Protocol implementation · Sequence selection · Human subjects scanning
Publications
My 2021 first-author publication on criminal arrests and childhood lead exposure has been cited in federal litigation (Amici Curiae brief, U.S. Court of Appeals for the D.C. Circuit, 2026) and legal scholarship. My 2020 first-author publication on traffic-related air pollution and cortical thickness received international media coverage including Reuters, the Daily Mail, and ScienceDaily, with an Altmetric Attention Score in the top 5% of all research outputs tracked. Full details available in the CV PDF.
Selected Presentations
- "Childhood Lead Exposure: Influences on Adult Brain and Behavior." Epidemiology Seminar Series, Dept. of Environmental Health, University of Cincinnati 2020
- "Childhood Lead Exposure: Influences on the Brain and Behavior in Adulthood." MECEH Training Program, University of Cincinnati 2019
- "Brain Differences Associated with Traffic-Related Air Pollution in a Longitudinally Studied Pediatric Cohort." MECEH Training Program, University of Cincinnati 2018
- Adult measures of criminality correlated with reduced regional brain volumes in childhood lead exposure cohort. [Conference Proceeding] Neurotoxicology and Teratology, 79 2020
- Traffic-Related Air Pollution Associated with Altered Neuroimaging Outcomes. American Society of Neuroradiology Annual Meeting, Las Vegas, NV. [Electronic Poster] 2020
- Traffic-Related Air Pollution Associated with Reduced Cortical Thickness and Altered White Matter Organization. ISMRM 25th Annual Meeting, Honolulu, HI. [Oral Presentation] 2017
- Adult Measures of Psychopathy in a Cohort with Childhood Lead Exposure. American Society of Neuroradiology Annual Meeting, Washington, DC. [Electronic Poster eP-73] 2016
15+ additional talks, seminars, and conference abstracts presented at major scientific meetings (2007–2020). Complete list available in the CV PDF.
Teaching & Training
- Served as the de facto neuroimaging methods resource across multiple postdoctoral lab settings, providing individual and small-group training to graduate and summer research students on FSL, AFNI, FreeSurfer, and ImageJ.
- Authored technical processing manual for the MRI_Analysis_Calculator ImageJ plugin, standardizing procedures for lab use.
- Provided ongoing methodology consultation on analysis approaches, software selection, and data management.
- Developed and delivered original STEM curriculum including presentations, lab exercises, and interactive activities for cohorts of 20 academically selected high school students.
- Mentored and supervised 4 graduate teaching assistants on classroom management and teaching strategies.
- Served under faculty mentorship as part of the Preparing Future Faculty certificate program, gaining formal training in course design and pedagogy.
- Led discussion sections, laboratory activities, and study sessions for first-year neuroscience graduate students.
Honors & Awards
- Most-Shared Findings, Cincinnati Children's Hospital Medical Center Research Horizons Blog Jan 2020
- Featured Research, Dept. of Radiology, CCHMC Annual Report — "Reduced Cortical Thickness Associated with Traffic-Related Air Pollution" 2020
- NIEHS T-32 Training Grant Fellowship (T32-ES10957) — Molecular Epidemiology in Children's Environmental Health Program 2018–2020
- Neuroscience Graduate Program Fellowship, University of Cincinnati College of Medicine 2008–2015
- Outstanding Research Award (Year-long Project), Psychology Undergraduate Research Symposium, Bowling Green State University 2007
Service & Leadership
- Student Representative, Neuroscience Graduate Program Admissions Committee | University of Cincinnati College of Medicine 2012–2013
- Student Representative, Network for Neuroscience Discovery Steering Committee | University of Cincinnati College of Medicine 2012–2013
- Graduate Student Recruiter, Neuroscience Graduate Program | University of Cincinnati College of Medicine 2009–2011
- Pilot Project Program Reviewer, Center for Integrative Environmental Health Sciences (CIEHS) | NIEHS P30, University of Louisville 2020
- Poster Session Judge, 40th Annual Graduate Student Research Forum, University of Cincinnati College of Medicine 2019
Environment International · NeuroImage · Physiology & Behavior · Psychiatry Research: Neuroimaging · The Lancet Planetary Health
Professional AffiliationsSociety for Neuroscience · Indiana Academy of Science · American Association for the Advancement of Science · Developmental Neurotoxicology Society · National Postdoctoral Association · Society for Epidemiologic Research