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WU-CDTR launches AI Core, lead by Dr. Ruopeng An

The integration of artificial intelligence (AI) and data science within the realm of diabetes research heralds a new era of innovation and precision.

The WU-CDTR recognizes the transformative potential of AI technologies in advancing our understanding, preventing, and treatment of diabetes.

In response, we are proud to launch the AI and Data Science Core (AI Core) —a dedicated platform offering both personalized one-on-one consultations and a rich suite of AI & data science capacity-building opportunities.

Led by Dr. Ruopeng An and his team, the AI Core is designed to empower our affiliated researchers with the tools, knowledge, and support needed to seamlessly integrate AI into their research endeavors.

Dr. Ruopeng An – Core Lead, WU-CDTR AI Core

The AI Core Goals

  1. Facilitate the incorporation of AI and data science methodologies in grant applications and research projects to enhance competitiveness and impact.
  2. Provide comprehensive capacity-building programs, including workshops, interest group meetings, and presentations, to build proficiency in AI and data science.
  3. Offer expert guidance in the ethical and effective use of AI in research, from data collection to analysis and dissemination.
  4. Develop and support the use of AI tools for research and dissemination, improving accessibility to and engagement with research findings.

AI Core Services and Opportunities

Core Services

  • Provide one-on-one consultative services on the use of AI and data science analytic methods in diabetes translation research.
    • Tailored meetings to strategize the integration of AI and data science into diabetes research projects, grant proposals, and academic publications.
    • Guidance on selecting appropriate AI/data science methodologies, crafting sections of proposals that detail these methods, and demonstrating their potential impact.
  • Provide technical assistance on the use of novel AI and data science tools in diabetes translation research among WU-CDTR investigators.
    • Technical assistance in applying AI/data science technologies in research projects, including data management, analysis, and interpretation.
    • Expert advice on incorporating AI elements into academic writing and the development of tools for research dissemination and application.
  • Build team capacity in the skills essential for the use of AI and data science in diabetes translation research. Opportunities include:

Schedule an initial consultation or in-depth core support using our core service request form.

About Dr. Ruopeng An

Ruopeng An is an Associate Professor and Faculty Lead in Public Health Sciences at the Brown School and the Division of Computational & Data Sciences at Washington University in St. Louis (WashU). He serves as the Faculty Fellow for AI Innovations in Education at the WashU Office of the Provost.

He conducts research to assess population-level policies, local food and built environment, and socioeconomic determinants that affect individuals’ dietary behavior, physical activity, sedentary lifestyle, and adiposity in children, adults of all ages, and people with disabilities. His research aims to develop a well-rounded knowledge base and policy recommendations that can inform decision-making and the allocation of resources to combat obesity.

His research has been funded by federal agencies and public/private organizations (e.g., OpenAI, Abbott, Amgen). He has wide teaching and methodological expertise, including applied artificial intelligence (machine learning, deep neural networks, generative AI), quantitative policy analysis (causal inference, cost-benefit and cost-effectiveness analysis, and microsimulation), applied econometrics and regression analysis, and systematic review and meta-analysis. He founded and chairs two AI and data science certificate programs and co-lead the Digital Innovations Strategic Priority at the Brown School. With over 200 peer-reviewed journal publications, he is recognized as one of Elsevier’s top 2% most cited scientists. His work has been highlighted by media outlets such as TIME, New York Times, Los Angeles Times, Washington Post, Reuters, USA Today, Bloomberg, Forbes, Atlantic, Guardian, FOX, NPR, and CNN. He serves on research grants and expert panels for NIH, CDC, NSF, HHS, USDA, and the French National Research Agency. He is an elected Fellow of the American College of Epidemiology and the American Academy of Health Behavior.