NESL Research Roadmap (實驗室發展路徑)-網路暨嵌入式系統實驗室

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NESL Research Roadmap (實驗室發展路徑)

Dr. Chao-Hsien Lee started to study network protocol design, mobile computing system and video streaming service while admitting into the graduate school. During the Ph.D. program, he published several international journal and conference papers, including IEEE Q1 journals. When he was an assistant professor, he explored and investigated more applications and services, e.g., long-term healthcare industry, wearable/embedded decvice design, industrial internet of things (IIoT), and satellite ground station. Based on the aforementioned background, Networked & Embedded Systems Laboratory (NESL) led by Dr. Chao-Hsien Lee divides the research scope into three levels, i.e. (a) lightweight deep learning edge computing, which should focus on how to design the deep learning models and structures optimized for the embedded environment, (b) video streaming & intelligent analytics, which can achieve the video streaming with the ultra high quality and real content recognition, and (c) advanced networking & encryption techniques, which can provide low-computation, multi-delivery, and securely-encrypted network coding mechanism. The on-going research topics and issues can be further classified into (i) Industrial Internet of Things (IoT) Eco-systems, (ii) Edge Computing Oriented Deep Learning Lightweight Algorithms, (iii) Software-defined / Time-sensitive / Sensing Networking, (iv) Lightweight Hybrid Encryption & Network Coding Techniques, (v) Wearable/Embedded Devices based on Deep Learning for Healthcare, (vi) Web / Peer-to-Peer (P2P) based Secure Video Streaming Services, and (vii) Cloud Database supporting Big Data Analytics. Please refer each research topics seperately in details.

<Research Interests>

Lightweight Deep Learning Edge Computing
Video Streaming & Intelligent Analytics
Advanced Networking & Encryption Techniques

李昭賢博士從研究所開始進行網路協定設計、行動計算系統、視訊串流服務等研究，並於博士學位取得期間發表數篇國際期刊論文與國內外會議論文，其中包含Q1之IEEE期刊，擔任助理教授起，因任職單位、執行計畫之緣故，逐步拓展至長期健康照護產業、穿戴式/嵌入式裝置設計、工業物聯網、衛星通訊地面站等多元化應用。因此，由李昭賢博士指導之網路暨嵌入式系統實驗室將研究範圍區分成(a)輕量化深度學習邊緣計算：強調可於嵌入式系統運行之深度學習模型與結構設計、(b)視訊串流與智慧分析：強調高品質視訊傳輸與即時內容識別的網路服務、以及(c)先進網路與加密技術：探討可兼具計算簡化、多重傳輸、安全加密之網路編碼機制等三方面，並可進一步規劃出七個正在進行中的研究主題方向，包含：(1)工業物聯網生態系統、(2)邊緣計算導向之深度學習輕量化演算法、(3)軟體定義/時間敏感/感測網路、(4)輕量化混合加密與網路編碼技術、(5)以深度學習為基礎之穿戴/嵌入式健康照護裝置、(6)網頁/同儕基礎之視訊加密串流服務、以及(7)支援大數據分析之雲端資料庫，不同主題方向之詳細內容請參照研究主題專區。

<研究方向>