Call for Students
NCKU CPS Lab 成立於2011年8月，（原名為ISA Lab）。
由蔡佩璇教授帶領，實驗室成員約10~12位，包含碩博士及大學專題生。
NCKU CPS Lab, (a.k.a ISA Lab), has been established since 2011 and led by Prof. Pei-Hsuan Tsai. There are about 10 to 12 members in the lab, including master students and Ph.D students.
主要應用場域 Main Application Field
智慧醫院
Smart Hospital智慧消防
Smart Fire Protection智慧工廠
Smart factory智慧建築
Smart Building智慧城市
Smart City智慧交通
Smart Transportation
研究方向 Research Direction
路徑規劃演算法
Path Planning Algorithm基於影像之AI流程驗證
AI Video-based SOP Verification自動化消防逃生輔助系統
Automation of Fire Response System物件與動作辨識
AI Video-based Object and Action recognition定位與導航系統
Localization and Positioning System即時工作排程與分配
Real-time Job Scheduling and Dispatching資料融合與決策分析
Data Fusion and Decision Analysis感測器網路
Sensor Network
在跨領域研究上進行系統架構功能設計、開發輔助工具並提供訊息處理、資料融合與決策分析等服務。
在現今以人機物融合系統 (Cyber-Physical System) 為導向的架構趨勢下，並行考量使用者行為與習慣，開發客製化的軟硬體設備與服務導向的產品，包括客製化系統功能模組、硬體機構設計、智慧型嵌入式系統與行動裝置應用程式等。
校外連結方面:CPS Lab 同時和中央研究院的研究員張原豪博士（資訊科學研究所）、修丕承博士（資訊科技創新研究中心）合作，進入本實驗室的研究所新生在研究主題的選擇上，也能加入兩位研究員老師的研究主題。
國際連結方面:CPS Lab目前與美國伊利諾大學香檳分校 Computer Science CPS lab led by Professor Lui Sha，共同研究有關Medical Guidance System，有興趣的同學歡迎加入!
★ 張原豪博士（資訊科學研究所）
隨手雜記： 豪豪老實說
研究領域：非揮發性記憶體、記憶/儲存系統、作業系統、即時系統、嵌入式系統、電腦系統
研究簡介（節錄）:
My research area is mainly on computer systems and embedded systems, with a prime focus on improving the capability of memory and storage systems. The research results were published in top conferences (e.g., ACM/IEEE DAC, ACM/IEEE ICCAD, and ACM/IEEE CODES) and top journals (e.g., IEEE TC, IEEE TCAD, IEEE TVLSI, ACM TECS, ACM TODAES, and ACM TOS).
★ 修丕承博士（資訊科技創新研究中心）
實驗室網站： 嵌入式暨行動運算實驗室
研究領域：嵌入式系統 (Embedded Systems), 間歇性運算 (Intermittent Computing), 微型深度學習 (TinyML)
研究簡介：
Dr. Hsiu’s research goal is to realize Intermittent Artificial of Things (iAIoT), enabling battery-less IoT devices to intermittently execute deep neural networks (DNN) via ambient power. iAIoT is a novel research direction at the intersection of intermittent computing and deep learning. He has led a research team to release a suite of system runtime and libraries, facilitating AI and IoT application developers to easily build low cost, intermittent-aware inference systems. In particular, an intermittent operating system (TCAD’20), which was the first attempt to allow multitasking and task concurrency on intermittent systems, makes complicated intermittent applications increasingly possible. The HAWAII middleware (TCAD’20), which comprises an inference engine and API library, enables hardware accelerated intermittent DNN inference, while the iNAS framework (TECS’21) was the first framework that introduces intermittent execution behavior into neural architecture search to automatically find intermittently-executable DNN models. A solar-powered image classification system was developed with our intermittent system runtime and inference library as an example: https://youtu.be/n6lEAjmn0Ng .
歡迎有興趣的同學一起加入實驗室!