Building AI that turns wearable sensor data into clinically useful insight, for movement disorders, mental health, and beyond. 將穿戴式感測器收集的訊號，轉換為臨床端真正能使用的客觀資訊，可應用於動作障礙、心理健康，以及更廣泛的臨床狀態評估。
My research focuses on multimodal AI for healthcare and clinical neuroscience. During my PhD at KU Leuven, I developed deep-learning systems for detecting and assessing freezing of gait in Parkinson's disease from inertial sensors, validated in collaboration with multiple hospitals. At HUB Lab, we extend that work toward multimodal foundation models for behavioural health, in close collaboration with clinicians and industry partners across Taiwan and Europe. 我的研究聚焦於健康照護與臨床神經科學中的訊號分析方法。博士班期間於比利時荷語魯汶大學（KU Leuven），我發展能從慣性感測器訊號自動偵測並量化帕金森氏症「步態凍結」現象的分析系統，並透過多家醫院的合作完成臨床驗證。在 HUB Lab，我們延伸這條研究路線，發展能整合多種感測訊號的行為分析方法基礎，與台灣及歐洲的臨床合作夥伴與產業夥伴密切合作。