David L. Barbee, PhD

My research focuses on enhancing the safety, quality, and efficiency of clinical operations through the development and implementation of novel technologies and techniques. I am passionate about identifying opportunities where automation, innovative tools, and cutting-edge approaches can have a meaningful impact on patient care and clinical workflows. NYU and Radiation Oncology have reinforced these efforts by creating my new role as Director of Technology and Innovation. My work spans the full spectrum of our department’s needs—from patient-facing dashboards and messaging systems to staff-focused machine QA automation and clinical dashboards, as well as backend databases that track quality and manage departmental operations. These solutions streamline processes, enhance decision-making, and ensure that operations run smoothly and efficiently.

A key focus of my work is the development of backend systems and dashboards that help manage departmental operations. These tools allow us to monitor clinical workflows and ensure that tasks are completed consistently, preventing delays and ultimately improving the quality of care. I also work closely with vendors to maximize the utility of their applications in our clinic. I’ve initiated partnerships with companies like Mirion / Sun Nuclear leading to NYU’s designation as a Sun Nuclear Center of Excellence, showcasing our knowledge and clinical use of their systems. I’ve also worked with Siemens/Varian to receive their support in development collaboration of advanced treatment planning automation for areas such as total body irradiation (TBI).

As the Lead of the Radiation Oncology Informatics group, I have expanded my focus to include large-scale data management and AI-driven clinical solutions. I’ve worked on building databases to support retrospective data analysis, helping us derive insights from hundreds of patient cases and apply these findings in clinical settings. Moving forward, I’m enthusiastic about integrating big data and AI into clinical workflows to further enhance patient care and operational efficiency.

In my expanded role, I collaborate with multiple departments across the institution, including MCIT Digital Solutions, Radiology, and Informatics, on projects that advance both research and clinical practice. These collaborations are key to identifying areas where technology can optimize clinical operations, and I look forward to continuing this work to drive innovation in both research and patient care.

My primary research interests include:

• Automation of machine QA and clinical processes
• Decision support tools and automation for treatment planning
• Development of clinical applications and dashboards using C# and Python
• Clinical system integration and big data management via SQL and APIs
• 3D printing and design for radiotherapy