Dr. Dian-Ru Li is currently an Assistant Professor in the Department of Mechanical Engineering at National Taiwan University. Dr. Li received her bachelor’s and master’s degrees from the Department of Mechanical Engineering at National Taiwan University, and earned her Ph.D. in Mechanical Engineering from the University of Michigan, Ann Arbor, in 2019. She subsequently served as a postdoctoral research fellow at the University of Michigan for one year. From 2020 to 2022, Dr. Li worked as a Senior Mechanical Engineer in R&D at Zap Surgical Systems, where she was primarily responsible for novel mechanical design and development, as well as improving the performance of the ZAP-X® Gyroscopic Radiosurgery system.

Dr. Li’s research interests span design and manufacturing, with a particular focus on biomedical engineering, especially medical device development, as well as advanced and smart manufacturing. She has long been engaged in interdisciplinary research and has extensive experience in successful collaborations with industry and clinical partners. Her research expertise includes the mechanics of tool–workpiece interactions, involving metals, polymers, and biological tissues, as well as mechanical structural analysis. She is also familiar with the full process of medical product design and development, including conceptual prototyping, design for manufacturability assessment, performance testing, and patent/commercialization evaluation. In recent years, Dr. Li’s research has further expanded into advanced and smart manufacturing, with an emphasis on integrating emerging technologies such as computer vision and machine learning into manufacturing processes to enhance product quality and promote process sustainability.

In 2018, Dr. Li was selected to participate in the Rising Stars in Mechanical Engineering workshop hosted by the Massachusetts Institute of Technology, as one of thirty outstanding early-career women scholars worldwide. She also led a team in developing an innovative nasal airway device, which won first prize in the Michigan Business Challenge in 2020. To date, Dr. Li has published 11 international journal papers and 11 conference papers, one of which received a presentation award at the 2017 World Congress on Micro and Nano Manufacturing. She also holds four patent applications, including one granted U.S. patent. Dr. Li is also a member of the American Society of Mechanical Engineers (ASME).

李典儒博士現任國立臺灣大學機械工程學系助理教授。李博士於國立臺灣大學機械工程學系取得學士與碩士學位，並於2019年獲得美國密西根大學安娜堡校區機械工程博士學位，隨後於該校擔任博士後研究員一年。2020至2022年間，李博士於 Zap Surgical Systems 公司擔任研發資深機械工程師，主要負責新型機械設計與開發，以及改良 ZAP-X® 立體定位放射手術系統的性能表現。

 李博士的研究領域涵蓋設計與製造，特別聚焦於生物醫學工程（醫療器材開發）以及先進與智慧製造。她長期從事跨領域研究，並與產業界及臨床單位有多項成功合作經驗。其研究專長包括工具與工件（涵蓋金屬、塑膠及生物組織）之交互作用力學分析，以及機械結構分析。同時，她熟悉醫療產品設計與開發的完整流程，包含概念原型製作、可製造性評估、性能測試與專利／商品化評估。此外，李博士近年研究主題延伸至先進與智慧製造，致力於將電腦視覺、機器學習等新興科技整合入製造過程中，以提升產品品質並促進製程永續化。

 李博士於2018年入選麻省理工學院舉辦之「機械工程新星」（Rising Stars in Mechanical Engineering）研討會，為全球三十位傑出青年女性學者之一。她亦曾領導團隊開發創新型鼻腔氣道裝置，並於2020年榮獲密西根商業挑戰賽（Michigan Business Challenge）首獎。李博士目前已發表11篇國際期刊論文、11篇研討會論文（其中一篇於2017年微奈米製造世界大會獲得論文發表獎），並擁有4項專利申請（其中1項美國專利已獲核准）。她同時為美國機械工程師學會（ASME）會員。

實驗研究方向

智慧與先進製造實驗室（Smart and Advanced Manufacturing Lab, SAMLab）致力於結合人工智慧（AI）與先進製造技術，發展跨領域的智慧化工程應用。實驗室以積層製造（3D 列印）作為核心研究與驗證平台，並拓展至多軸製造技術、生醫工程與智慧醫療器材開發等方向，打造新一代智慧製造與生醫創新系統。

1. AI導向的智慧積層製造

我們運用機器學習、深度學習、影像辨識與多種感測技術，讓積層製造具備即時監控、異常偵測、參數預測與自動化修正的能力。透過 AI 的導入，傳統 3D 列印得以轉型為高可控性、高穩定度的智慧化製程，使製造品質與可靠度大幅提升，並擴大其跨領域應用可能性。

2. 新型積層製造技術開發

此研究方向著重透過材料創新、機構設計與系統整合來突破現行製程限制，發展下一世代的積層製造技術。研究內容包含多軸機械手臂積層製造、軟性材料與複合材料列印、無支撐材列印策略等，同時也探索壓電材料、導電材料與功能性材料在積層製造中的可行性，使應用範圍顯著拓展。

3. AI於生醫工程與創新醫療器材中的應用

我們將智慧製造與 AI 技術延伸至生醫領域，利用人工智慧進行各類醫療訊號與生醫資料的分析、異常偵測與決策輔助，提升臨床應用的精準性與效率。同時，我們也研究積層製造在生物材料、組織工程與醫療器材開發中的應用，並建立模擬平台探討手術器械與生物組織的交互作用。相關成果亦涵蓋創新醫療器材的設計、驗證與商業化可行性評估。

更多研究方向、成果與最新消息，歡迎參考實驗室網站：https://ntusamlab.com

Smart and Advanced Manufacturing (SAM) Lab focuses on applying advanced and smart manufacturing technologies to improve manufacturing processes and enable multidisciplinary applications. Target research themes include Smart Additive Manufacturing, Novel Additive Manufacturing Process, and Biomanufacturing and Innovative Medical Device Development.

“Smart Additive Manufacturing” is to implement advanced computer science techniques, including machine learning and computer vision, to enable smart error monitoring, detection, and correction for additive manufacturing processes.

“Novel Additive Manufacturing Process” aims to develop new additive manufacturing process by exploring new printing materials, machine mechanism design, and system integration. Examples include multi-axis robotic additive manufacturing, soft material printing, and support-free material extrusion.

“Biomanufacturing and Innovative Medical Device Development” utilizes advanced manufacturing knowledge and techniques to innovate biomedical/biomanufacturing applications. Topics include simulations and experiments of various tool-tissue interactions in surgical procedures, application of additive manufacturing on bioengineering, and design and manufacturing of innovative medical devices.