鄧志峰 Jr-Fong Dang

研究領域
Field of research

機器學習、深度學習、異常偵測、預測性維修、瑕疵檢測、智慧製造

Machine learning, Deep Learning, Anomaly Detection, Equipment Health Monitoring and Predictive Maintenance, Defect Detection, Smart Manufacturing

實驗室簡介
Laboratory introduction

致力於融合製程控制理論、智慧化設備設計與人工智慧技術，針對製造業中的高精度、高效率及高可靠性需求，提出創新解決方案。研究室的核心方向涵蓋 多變數製程控制、製程建模與最佳化、智慧設備與機電整合、數位孿生 以及 人工智慧在智慧製造的應用。團隊同時與產業密切合作，將研究成果導入實際製造環境，協助企業提升產品品質、降低能耗並實現彈性化生產。透過跨領域的研究與技術整合，實驗室期望成為智慧製造與先進製程控制領域的技術創新核心，培育具備國際競爭力的工程與研發人才。

We focus on integrating process control theory, intelligent equipment design, and artificial intelligence technologies to address the demands for high precision, high efficiency, and high reliability in modern manufacturing. Our core research areas include multivariable process control, process modeling and optimization, intelligent equipment and mechatronic system design, digital twin technology, and AI applications in smart manufacturing. The laboratory works closely with industry partners to implement research outcomes in real-world manufacturing environments, enabling improved product quality, reduced energy consumption, and flexible production capabilities. By combining interdisciplinary expertise and advanced engineering techniques, the laboratory aims to become a leading innovation hub in advanced process control and intelligent manufacturing, while cultivating highly skilled engineers and researchers with global competitiveness.

邱俊智 Chun-Chih Chiu

研究領域
Field of research

隨機模擬最佳化 、數位雙生之應用 、智慧製造與排程 、物流與運輸系統 、人工智慧於作業決策之應用

Stochastic Simulation Optimization; Applications of Digital Twin; Intelligent Manufacturing and Scheduling; Logistics and Transportation Systems; Applications of Artificial Intelligence in Operations

實驗室簡介
Laboratory introduction

本實驗室專注於人工智慧導向的智慧營運決策研究，結合隨機模擬最佳化、群體智慧演算法、數位雙生、人工智慧與強化學習等核心技術，致力於解決高度不確定且複雜的系統營運決策問題。研究應用涵蓋智慧製造、半導體製造決策、電動車充電策略、智慧機器人倉儲揀貨系統與機場行李處理等實務場域，並針對各類營運挑戰提出具前瞻性與實用性的創新解決方案。

This lab is dedicated to AI-driven research on smart operations decision-making. By integrating core technologies such as stochastic simulation optimization, swarm intelligence algorithms, digital twins, artificial intelligence, and reinforcement learning, we aim to address highly uncertain and complex operational decision problems. Our research is applied to practical domains including intelligent manufacturing, semiconductor production planning, electric vehicle charging strategies, robotic smart warehousing and picking systems, and airport baggage handling. We strive to deliver forward-looking and practical solutions to diverse operational challenges.

鍾昕燁 Sin-Ye Jhong

研究領域
Field of research

電腦視覺及影像處理、機器/深度學習、強化式學習、多模態融合技術、生成式人工智慧、代理式人工智慧、智慧物聯網、智慧無人載具、智慧製造、智慧交通

Computer Vision & Image Processing, Machine/Deep Learning, Reinforcement Learning, Multimodal Fusion, Generative AI, Agentic AI, Smart IoT, Intelligent Unmanned Vehicles, Smart Manufacturing, Intelligent Transportation

實驗室簡介
Laboratory introduction

本實驗室致力於開發能自主感知、決策並與真實世界互動的智慧系統。團隊應用生成式AI、多模態融合與強化學習等前瞻技術 ，專注於智慧無人載具 、輔助機器人與智慧製造三大領域。透過與相關產業的緊密合作，我們將尖端研究轉化為實際的解決方案，應對真實世界的複雜挑戰。歡迎對打造下一代智慧系統充滿熱情的你，加入團隊共同定義人機互動的未來。

The Autonomous Systems and Intelligent Interaction (ASI²) Laboratory develops intelligent systems that can robustly perceive, reason, and act in complex, real-world environments. Our research lies at the intersection of generative AI, computer vision, multimodal learning, and robotics. Key applications include building multimodal fusion frameworks for autonomous vehicles , developing Vision-Language-Action (VLA) models for assistive robotics , and designing multi-agent systems for smart manufacturing. Through active collaborations with the automotive, robotics, and high-tech industries, we translate fundamental research into impactful, real-world solutions and cultivate the next generation of innovators in intelligent systems.

梁書豪 Shu-Hao Liang

研究領域
Field of research

智慧物聯網、雲端運算、工業網路安全、5G網路、工業機器人應用

AIoT, Cloud Computing, Cybersecurity, 5G network, Industrial Robot Application

實驗室簡介
Laboratory introduction

本實驗室的核心精神為正直(Integrity), 創新(Innovation), 無限 (Infinite)。期待學生進行學術研究工作時，抱持正直態度不抄襲、不剽竊，以創新思維突研究瓶頸, 同時相信自己的能力無極限。實驗室的特色在於強調實作能力的培養, 尊重學生選擇自己的研究方向。

The spirit of this laboratory is integrity, innovation, and infinite. We expect students to be honest and avoid plagiarism when conducting academic research, break through research bottlenecks with innovative thinking, and believe that their abilities are limitless. The characteristic of the laboratory is that it emphasizes the cultivation of practical ability and respects students' choice of their own research direction.

高裕翔 Yuh-Shying Gau

研究領域
Field of research

智慧載具路徑規劃與預測, 智慧裝卸載演算法, 人機協同, AMR, PLC與自動化邏輯, UAV

AI Vehicle Path-Path and Prediction, Load-unload Algorithm, Human-Machine Collaboration, PLC and Automation, and UAV-related topics

實驗室簡介
Laboratory introduction

IVL實驗室的發展邏輯基於製造人性化與自動化的出發點, 主要應用在以智慧載具與其搭載上的感測器模組資料決策過程,軟體配備Dassualt Solidworks (全功能, 電腦輔助設計製造與工程模擬), Autodesk Flexsim (數位雙生與工廠模擬軟體), 德國MVTec Halcon影像處理辨識軟體;硬體t除電腦外,配備Schneider M241 PLC, MG400機械手臂, ToF與超音波傳感器, FLIR的高解析度智慧檢測工業攝影機等.

The IVL's strategy is based on human-centric design and automation, focusing on decision-making with sensor data on intelligent vehicles. It features additional software like Dassault SolidWorks for design, Autodesk FlexSim for digital twin modeling, and MVTec Halcon for image processing. Hardware includes personal computers, Schneider PLCs, robotic arms, ToF and ultrasonic sensors, and FLIR cameras for precise sensing and autonomous control.