Industry_research

Daniel N. Bullock

iisdanbul@gmail.com; DanNBullock.github.io

Alexandria, VA, USA

Education

Ph.D., Psychology, Neuroscience
at Indiana University Bloomington (Bloomington, IN),
Department of Psychological and Brain Sciences, Program in Neuroscience
6 / 2015 to 6 / 2021
B.S., Biology
at North Carolina State University (Raleigh, NC),
Department of Biological Sciences

Minor(s): Math, Genetics
8 / 2005 to 5 / 2006, &
8 / 2012 to 5 / 2015
Graduate Program, Philosophy
at University of Cincinnati (Cincinnati, OH),
Department of Philosophy
8 / 2009 to 5 / 2011
B.A., Psychology, Philosophy
at University of North Carolina at Chapel Hill (Chapel Hill, NC),
Department of Psychology and Neuroscience

Minor(s): Cognitive Science
8 / 2006 to 5 / 2009

Experience

Science and Engineering Technical Advisor (SETA) [Contractor]
at The Advanced Research Projects Agency for Health (ARPA-H) (Washington, D.C.),
Health Science Futures (HSF)

Supervised by Ileana Hancu()
Domain: Technology Development, Translation, and Transfer
Type: Project Management, Research
Dates: 7 / 2024
Workload: 40 hrs per week

As a Science and Engineering Technical Advisor (SETA) I serve as the primary expert overseeing a collection of ARPA-H projects with a total annual budget of more than $18 million and a total project-lifetime budget of more than $80 million. In addition to this, I serve as secondary SETA on projects with a total annual budget of more than $23 million and a total project-lifetime budget of more than $125 million. I provide technical guidance and oversight to project teams and ARPA-H personnel, regularly interface with internal and external stakeholders, track project milestone progress, and review incoming proposals. I also help scope and design new projects. I developed the initial structure and vision for the ARPA-H Systematic Targeting Of MicroPlastics (STOMP) program. I served as the primary architect of the former Imaging Data Exchange (INDEX) program’s major technical requirements (TA 2).

Technical skills: Dataset Quality Assessment, Data Science, Data Visualization, Figure Generation, Platform Design
Science and Technology Policy Fellow
at National Science Foundation (Alexandria, VA),
Computer and Information Science and Engineering, Office of Advanced Cyberinfrastructure

Supervised by Alejandro Suarez() , Robert Beverly()
Domain: Open Science and Cyberinfrastructure policy
Type: Research, Policy
Dates: 8 / 2022 to 7 / 2024
Workload: 40 hrs per week

As an AAAS STPF Fellow placed in the Office of Advanced Cyberinfrastructure (OAC) I have engaged in a wide range of endeavors supporting the mission of the OAC. These include assisting with the Pathways to Open Source Ecosystem (POSE) (e.g., panels, revising program description, triage), several ongoing endeavors supporting NSF Public access efforts, and internal reviews. My interagency work includes assisting with the OSTP’s Subcommittee on Open Science’s (SOS) Open Science Infrastructure (OSI) Working Group, where I performed an analysis using openly accessible data from federal agencies and incorporated these results into a report on current agency investments in Open Science Infrastructure. I also serve as a member of the NSF team coordinating and organizing the multi-agency National AI Research Resource (NAIRR) Pilot program, in particular assisting with the development of practices and policies related to data.

Technical skills: Python, Linux, Git, XML, JSON, Big Data, Data Scraping, Dataset Quality Assessment, Data Science, Data Visualization, Figure Generation, Jupyter Notebooks, Open-Source Development, Open-Source Software
Postdoctoral Researcher
at University of Minnesota (Minneapolis, MN),
Medical School, Department of Neuroscience

Supervised by Sarah Heilbronner() , Jan Zimmermann()
Domain: Computational Neuroanatomy
Type: Research
Dates: 7 / 2021 to 7 / 2022
Workload: 40+ hrs per week

As a postdoctoral researcher I produced automated segmentation methods for the brain’s major white matter tracts in tractography using cross-species and literature-based information. These tools allowed for the cross-referencing of ‘ground truth’ studies of non-human primate brain connectivity anatomy with imaging based studies of human brain connectivity anatomy, and have also served as anatomy models used in the development of deep brain stimulation (DBS) techniques and technologies. This also entailed the visualization of tractography and segmentation results, as well as the quantification of tract properties. To ensure the replicability and stability of these products I developed, documented, and maintained several code repositories.

Technical skills: Python, Linux, Git, Docker, Neuroimaging Software Packages, Neuroimaging, Neuroanatomy, Neuroscience, Brain Imaging Data Structure (BIDS), Neuroimaging Data Structures, Neuroimaging Data Processing, 3-D Image Processing, Medical Image Processing, Bash and Shell Scripting, Big Data, Dataset Quality Assessment, Data Science, Jupyter Notebooks, Containerization, Open-Source Development, Open-Source Software, High Performance Computing (HPC), Data Visualization, Testing and Debugging, Coordinated/Collaborative Testing and Debugging, Statistical Analysis, Advanced Statistical Analysis
Application developer and maintainer
at Indiana University Bloomington (Bloomington, IN),
Department of Psychological and Brain Sciences, Program in Neuroscience

Supervised by Franco Pestilli() , Soichi Hayashi()
Domain: Platform Development
Type: Development
Dates: 7 / 2017 to 7 / 2023
Workload: ~ 5 - 10 hrs per week

As an application developer for the brainlife platform, I was responsible for the production and maintenance of containerized brain-data processing applications, enabling drastically simplified use of advanced processing and analysis techniques. This entailed the creation of novel data processing and visualization code, as well as adaptation of existing resources. I also engaged in testing, monitoring, and feedback on service deployment and coordination. I also led the scoping, creation, coordination, and maintenance of specific data formats/standards.

Technical skills: Python, Matlab, JSON, Markdown, Linux, Git, Neuroimaging Software Packages, Brain Imaging Data Structure (BIDS), Neuroimaging, Neuroimaging Data Structures, Neuroimaging Data Processing, 3-D Image Processing, Bash and Shell Scripting, Big Data, Dataset Quality Assessment, Data Science, Docker, Containerization, High Performance Computing (HPC), Continuous Integration and Continuous Delivery/Deployment (CI/CD), Testing and Debugging, Coordinated/Collaborative Testing and Debugging, Data Visualization, Statistical Analysis, Advanced Statistical Analysis
Graduate Student/Researcher
at Indiana University Bloomington (Bloomington, IN),
Department of Psychological and Brain Sciences, Program in Neuroscience

Supervised by Franco Pestilli()
Domain: Computational Neuroanatomy
Type: Research
Dates: 6 / 2015 to 6 / 2021
Workload: 40+ hrs per week

As a graduate student researcher I developed and implemented automated segmentation methods for major white matter tracts in tractography, enabling personalized models of brain anatomy and connectivity. This also entailed the visualization of tractography and segmentation results, as well as the quantification of tract properties and development of tractography quality assurance methods. This work required a deep review of contemporary and historical neuroanatomy literature.

Technical skills: Python, Matlab, Linux, Git, Neuroimaging Software Packages, Neuroimaging, Neuroanatomy, Neuroscience, Brain Imaging Data Structure (BIDS), Neuroimaging Data Structures, Neuroimaging Data Processing, 3-D Image Processing, Medical Image Processing, Bash and Shell Scripting, Big Data, Dataset Quality Assessment, Data Science, Jupyter Notebooks, High Performance Computing (HPC), Data Visualization, Statistical Analysis, Advanced Statistical Analysis

Awards, Fellowships and Grants

Title and SourceTypeDurationLink
AAAS Science and Technology Policy Fellow
at National Science Foundation (NSF) via Association For the Advancement of Science (AAAS)
Fellowship 8 / 2022 to 8 / 2024
Neuroimaging NIH Postdoctoral Training Fellowship (T32)
at University of Minnesota via National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Fellowship 1 / 2022 to 8 / 2022
Data Science for the Public Good (DSPG) Young Scholars program
at University of Virginia Biocomplexity Institute via Data Science for the Public Good (DSPG)
Fellowship 6 / 2020 to 8 / 2020
Clinical Translational NIMH Predoctoral Training Fellowship (T32)
at Indiana University Bloomington, Department of Psychological and Brain Sciences, Clinical Science Program via National Institute of Mental Health (NIMH)
Fellowship 8 / 2018 to 5 / 2020
UW eScience Institute Neurohackacademy Summer Scholar
at University of Washington eScience Institute via NeuroHackAcademy
Fellowship 8 / 2019 to 9 / 2019
Center for Information and Neural Networks (CiNet) Training Fellowship
at Center for Information and Neural Networks (CiNet) via National Institute of Information and Communications Technology (NICT)
Fellowship 12 / 2016 to 1 / 2017
Psychological and Brain Sciences departmental fellowship
at Indiana University Bloomington via Department of Psychological and Brain Sciences
Fellowship 8 / 2015 to 5 / 2017
SENS Research Foundation Summer Scholar
at Wake Forest Institute for Regenerative Medicine via Sens Research Foundation
Fellowship 6 / 2013 to 8 / 2013
Wake Forest Institute for Regenerative Medicine Summer Scholar
at Wake Forest University School of Medicine via Wake Forest Institute for Regenerative Medicine
Fellowship 6 / 2013 to 8 / 2013
NCSU Undergraduate Research Grant
at North Carolina State University via Office of Undergraduate Research
Grant 1 / 2013 to 6 / 2013, &
1 / 2014 to 6 / 2014