Cameron Craddock

Director of the Computational Neuroimaging Lab

The Computational Neuroimaging Lab (1) develops and maintains a variety of cloud-native resources and open source software tools for collecting, archiving and analyzing biomedical research data, (2) conducts large scale collection of neuroimaging, behavioral, and other assessment data from human subjects, and (3) performs analyses of neuroimaging data using advanced multivariate statistical and machine learning methods to understand mechanisms underlying brain disorders. Responsibilities include:

• Defining the group’s research agenda, obtaining funds to cover operational and personnel costs from federal, and local grant mechanisms (awarded $1.6MM), developing and maintaining a budget.
• Supervising diverse teams of engineers, data scientists and researchers with various levels of seniority (currently supervise 7). This includes technical leadership, mentoring to foster growth and addressing performance issues.
• Building high quality teams through defining job duties, specifying hiring standards, developing interview questions and procedures, screening candidates, and creating onboarding processes.
• Managing an Agile software development life cycle, which includes leading daily scrum, sprint planning and retrospective meetings, managing backlog, coordinating with stakeholders to define and prioritize requirements, unblocking the workflow, and modifying the process when necessary.
• Creating and enforcing mandatory policies on code style, code review, and data analysis best practices.
• Organizing and teaching informal workshops on using software development and computational tools (e.g., CI/CD, git, containers, cloud services) for improving data management and analysis in scientific research.
• Collaborating with local and international researchers on their data analysis and computational needs.

• Building a research management and data collection (iOS and Android) mobile application for remotely collecting high-quality and ecologically valid measurements of human behavior; reduced costs by $200K.
• Conceived, obtained funding for, and led a team to develop the Protect Texas Together mobile phone application (iOS and Android) to help the UT community stay safe from COVID-19. Delivered on-budget and on-time on urgent timelines at a cost that is an order of magnitude less than the next-cheapest option.
• Developing a cloud native SaaS system for high throughput analysis of (big) medical imaging data.
• Managing a Beiwe mobile phone research platform for remotely collecting data on over 3,500 research participants for 15 studies, leveraging serverless technologies to reduce monthly expenses by a third.
• Developing and maintaining a cloud-based system for collecting research data from public APIs (Fitbit, environmental data, etc.). Reduced operational costs by $100K annually over commercial services.