About

Explorer of AI Root-Cause Medicine

Era Identity: Explorer of AI Root-Cause Medicine

Dr. Xiong Jianghui is defining the new medical direction of AI Root-Cause Medicine.

System Identity: Pioneer of the Personal Longevity OS

His core work is not proposing an abstract concept, but building the Personal Longevity Operating System — advancing root-cause reasoning to an engineerable, deliverable, and verifiable stage.

Engine Identity: Builder of the SEMO Root-Cause Engine

At its core, the SEMO Root-Cause Reasoning Engine transforms individual data into actionable, trackable intervention plans.

Interdisciplinary Foundation

  • Biology Bachelor

    1998,Wuhan University

  • Medicine Master

    2001,Institute of Space Medico-Engineering

  • Computer Science PhD

    2005,Computer Science

15 Years of Data Validation

  • Researching DNA methylation since 2009

    Deeply engaged in epigenetics, building aging clock models

  • Accumulated 3000+ real-world samples

    Covering multi-dimensional data on aging, chronic diseases, and tumors

  • Formed a detection-intervention-feedback loop

    Complete chain from data to algorithm to verification

Vision

Not an expert in a field, but the creator of a new system.

FAQ

Frequently Asked Questions

熊江辉的学术背景是什么?
熊江辉拥有跨学科背景:武汉大学生物学学士、航天医学工程研究所医学硕士、计算机科学博士。2009年起深耕DNA甲基化与表观遗传学,积累3000+真实世界样本数据。
熊江辉提出了什么原创理论?
熊江辉提出了'生命是适应环境的能力集合体'的第一性原理,并由此演绎出能力组学(Capomics)、根因医学三层框架、响应映射理论等核心概念。这些理论为从经验归纳到原理推导的医学范式转变提供了逻辑基础。
什么是演绎法驱动的生物医学?
传统生物医学依赖归纳法——从大量实验数据中寻找规律。演绎法则从第一性原理出发,逻辑推演出必然的结论。熊江辉认为,面对多组学数据的集成挑战,需要抛弃归纳法思路,从第一性原理建立通用的理论与计算框架。