Digital Heart

Welcome to my webpage. I am an Associate Professor at the Medical School of Nanjing University, China. My research integrates multiscale and multiphysics computational modeling with deep learning to uncover cardiovascular disease mechanisms and improve therapeutic strategies.

长期招聘助理研究员、博士后、科研助理，招收博士或硕士研究生、访问学生、本科生等。诚挚欢迎对信息与医学交叉、数字医学、心血管疾病、人工智能等相关领域感兴趣的青年才俊加入，共创数字孪生驱动的精准医学新模式。

重点招聘招生领域（博士后、博士、硕士、科研助理），也可推荐至附属鼓楼医院：

一、专业方向：计算机、电子信息、生物医学工程等医工交叉学科专业方向。在心脏数字孪生、复杂器官系统与疾病数字建模、深度学习驱动复杂系统模型代理、基于深度学习的因果推理、或虚拟现实技术等相关领域有相关经验者优先。
二、AI分析数字孪生构建技术人员岗位：
1.深度学习代理模型（Surrogate Model）开发；
2.基于深度学习的因果推理方法解析复杂病理机制；
3.跨学科协作；
三、多器官数字孪生建模技术人员岗位：
1.心脏数字孪生模型开发；
2.高性能计算与算法实现；
3.多器官模型集成与验证，跨学科协作；
Contact: hni@nju.edu.cn

The heart functions as a robust blood pump because electrical activation and contraction remain tightly coordinated through excitation-contraction (EC) coupling. Disruption of this rhythm or activation sequence, i.e. cardiac arrhythmia, contributes to major cardiovascular diseases, increases morbidity and mortality, and can lead to sudden cardiac death.

My research develops computational systems frameworks and personalized simulation pipelines for building human cardiac ‘digital twins’ that can inform therapy. We combine biophysically detailed cellular models with anatomically realistic whole-heart reconstructions derived from experimental and CT/MRI data to study electrical and mechanical function across scales. These quantitative platforms are used to dissect arrhythmia mechanisms, evaluate anti-arrhythmic interventions, assess cardiotoxicity, and support virtual trials and patient-specific therapeutic planning such as catheter ablation.