研究方向

课题组专注脑疾病的多模态生理-病理特征解析与人工智能模型构建，研究聚焦于跨模态特征的整合与建模，包括血液多组学、生理信号及临床电子病历等数据，推动AI在精神疾病早期诊断、预后预测与智能干预中的应用转化。
The research group focuses on leveraging AI and deep learning methods to mine multimodal medical big data – including molecular omics (genomics, proteomics, metabolomics, etc.), electronic medical records, and physiological signals like EEG and gait. Our primary applications include intelligent diagnosis/treatment of brain disorders and clinical decision support systems. We develop predictive models and open-source tools to advance cross-modal precision diagnostics and therapeutics for neuropsychiatric diseases. Our research leads internationally in this domain. The multidisciplinary team integrates expertise in bioinformatics, clinical medicine, and computer science, driving the clinical translation of scientific discoveries.

研究项目

我们的项目聚焦在以 AI for Science 的方式来提高对神经精神疾病的病症的理解、诊断、监测、和治疗。 我们使用各种形式的数据：基因、蛋白、代谢等生物组学、医学电子病例记录、脑电、步态等信息来建立多模态预测及诊疗模型， 以此来帮助我们完成通过计算改善患者的健康状态。我们研究项目涉及大数据处理、计算方法，知识库以及AI模型构建、临床决策系统搭建和应用的研究。
We are interested in the use of “computation + experimentation” format to improve the understanding, diagnosis, monitoring, and treatment of neuropsychiatric and neurodevelopmental conditions. We apply a variety of data modalities: genomic, metabolic, pharmacological, medical record, imaging, audio recording etc. to build predictive models that assist us in our mission of improving mental health through computing. We have supported research programs involving computational methodology, big data processing, database and clinical decision system construction, and clinical translational researches.

欢迎有志者（本科生、研究生、博后等各类科研人员）加入我们    招聘助理研究员启示

All potential members, including volunteers, undergraduates, graduates, and postdocs, are all welcomed to join us.

实验室开发的工具与数据库  (Developed Tools & Database)

我们开发了一系列工具与数据库以供科研社区使用，欢迎访问    Toos & Database

We have developed a range of tools and databases for the research community to use。