Call for Students

★ 張原豪博士（資訊科學研究所）

• 個人網站： Yuan-Hao Chang (Johnson Chang)

• 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 .