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A Decentralized, Nurse-led Community Advancing Practice & Research
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  • Governance & DAO Structure
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Jianxiong Sheng, PhD

Faculty Fellow, NurseKnowsNurse™

Role at NurseKnowsNurse™

Dr. Sheng contributes to NurseKnowsNurse™ by supporting data-intensive research and innovation through rigorous quantitative and statistical analysis, with attention to methodological soundness and interpretability.
Currently at MIT, he strengthens analytical design, model interpretation, and evidence evaluation across projects integrating complex data sources, human-AI collaboration, and the organizational and technical architecture underlying the NurseKnowsNurse™ DAO.

Professional Background

Dr. Sheng is a quantitative scientist with advanced training in applied mathematics, statistical modeling, and computational analysis, as well as formal nursing education. He has held research appointments at the Massachusetts Institute of Technology (MIT) and Harvard University, where his work focused on applying rigorous quantitative methods to complex, longitudinal, and high-dimensional data.

In addition to his academic background, Dr. Sheng has worked across industry settings involving risk modeling, quantitative analysis, and data-driven decision support. He has extensive familiarity with decentralized systems, blockchain-based architectures, and Web3 technologies, particularly as they relate to data integrity, distributed coordination, and system-level trust.

Areas of Focus

At NurseKnowsNurse™, Dr. Sheng contributes to initiatives involving:

  • Statistical and quantitative modeling for complex data systems

  • Longitudinal and high-dimensional data analysis

  • Methodological evaluation of AI-assisted analytics

  • Decentralized and blockchain-informed system design for future organizational models

Professional Service

Dr. Sheng contributes professional service through research and interdisciplinary collaboration across academic and applied settings. His work reflects a sustained commitment to quantitative rigor, transparency, and responsible analytical practice, alongside thoughtful exploration of future-ready organizational and technical structures.

Network Contact

  • jsheng at rnknowsrn.org

External Links

  • Google Scholar / ORCID
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