Advancing Research Translation with AI Stakeholder Insights (2026-2027)

Background

Duke produces an extraordinary volume of scientific innovation — yet much of this work never reaches the public in the form of usable products, services or technologies. Technology transfer is currently dominated by a small subset of faculty: of roughly 500 invention disclosures between 2018 and 2022, nearly 30 percent came from only ten laboratories. Meanwhile, PhD students across engineering increasingly express interest in entrepreneurship, but traditional STEM training rarely includes experience in community engagement, end-user research or market exploration.

Undergraduates and master’s students, however, often have training in human-centered design, qualitative research or applied problem-solving. This project builds on the interdisciplinary strengths of Bass Connections to bridge the gap between research creation and real-world application. By pairing students with PhD researchers and using AI tools for structured brainstorming, the team will help identify promising use-cases for emerging technologies and gather stakeholder insights to guide translation pathways.

Project Description

The project follows a structured, multi-stage process that mirrors early research translation pipelines:

Research technology understanding
Team members will learn directly from PhD researchers about three cutting-edge technologies selected from the Pratt School of Engineering. Students will study papers, interview research teams and produce a clear, jargon-free Research Technology Report summarizing each technology’s purpose, capabilities and limitations.

Use-case generation with AI
Using Duke’s ChatGPT system and custom-built prompting frameworks, the team will brainstorm hundreds of potential societal use-cases per technology. Students will refine ideas by setting guardrails, validating outputs against research literature and iteratively improving prompt design. A detailed Use-Case Database will catalog opportunities.

Downselection and stakeholder interviews
Working closely with PhD mentors, the team will select three to five high-potential use-cases per technology. For each, team members will conduct approximately 20 interviews with stakeholders such as clinicians, industry experts, community members, nonprofits or operational partners. These conversations will clarify real-world needs, barriers, feasibility and potential impact.

Analysis and synthesis
Team members will analyze qualitative data using tools like Condens, generating evidence-based insights. They will then produce a comprehensive Research and Development Report, outlining validated use-cases, recommended next steps and potential pathways to achieve societal benefit.

The project also includes a dedicated AI subteam to deepen exploration of prompt engineering, custom GPT development and best practices for integrating AI tools into research workflows.

Anticipated Outputs

Research Technology Reports (3 total, one per research team)
Use-case databases containing hundreds of potential applications
40–60 stakeholder interview records per technology
Comprehensive Research and Development Reports synthesizing opportunities and barriers
Best-practices toolkit for engaging AI tools in early-stage research translation
Presentations to participating PhD labs, department leadership and innovation partners

Student Opportunities

The team will include around 10 graduate/professional students and 20 undergraduate students from engineering, cultural anthropology, public policy, AI and computer science, statistical science and innovation and entrepreneurship.

Students will gain experience in:

Breaking down complex scientific concepts into accessible explanations
Applying prompt engineering and AI-assisted brainstorming methods
Conducting qualitative interviews with stakeholders and end-users
Performing qualitative analysis and synthesizing unstructured data
Communicating findings to researchers and external partners
Understanding pathways for technology commercialization, translational research and societal impact

Graduate students will serve as mentors for small subteams and guide technical and analytical rigor.

Timing

Fall 2026 – Spring 2027

Fall 2026:

Technology understanding and report drafting
AI tool training and use-case development
Use-case selection and early interview planning
Development of interview protocols

Spring 2027:

Interview training and piloting
Completion of 60+ stakeholder interviews
Analysis of qualitative data
Development of final Research and Development Reports

Crediting

Academic credit available for fall and spring semesters