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Event & Seminar

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【AI Seminar】2025.04.29 Transforming Healthcare with AI: From Data to Direct Care - Dr. Jessy Kang

2025.04.10
Topic: Transforming Healthcare with AI: From Data to Direct Care Speaker: Shih-Chung Jessy Kang.  Founder and CEO, Smart Ageing Tech Time: 2025/04/29 (Tue) 14:00-16:00 Venue: The Management Building, 11F, AI Lecture Hall Join Online: https://reurl.cc/gRZ14V or scan QR code on poster  About the Speaker:   Jessy, who grew up in a family that owns a hospital, holds a Stanford Ph.D. with expertise in robotics and AI. He conducted a decade of healthcare technology research at National Taiwan University, building a longstanding collaboration with research institutions in Finland and Japan. In 2018, he and several core research team members established a tech company, Smart Ageing Tech (as known as Jubo), dedicated to solving the issue of the aging population and societies. In late 2018, Smart Ageing Tech launched its first product: Jubo Facility Solution. The solution includes four parts: (1) IoT trolley: to reduce the efforts on the measurement of vital signs at the bedside; (2) Smart Nursing Information System: to increase the quality and accuracy of the nursing record through smart input interface; (3) Facility Management Chatbot: to facilitate real-time and effective management via integration with LINE; (4) Family Communication Chatbot: to enhance the family engagement in long-term care. As of 2024, it has been adopted by over 1,200 long-term care institutions, supporting the health data management of more than 150,000 residents. Prior to founding Jubo, Dr. Kang had an accomplished academic career in AI and robotics, receiving numerous awards and holding 23 related patents. His leadership emphasizes teamwork, innovation, and value creation. By uniting interdisciplinary talent, he has positioned Jubo as a leading provider of SaaS and AI solutions for the caregiving industry. Abstract: This talk will explore real-world applications of AI in long-term care, focusing on how smart systems can reduce caregiver workload and enhance care quality. Dr. Jessy Kang will present how Jubo uses AI to automate tasks like vital sign monitoring, wound documentation, and care handovers across over 1,200 care institutions. He will also share insights from building a health-tech startup rooted in academic research, and how Jubo delivers high-impact solutions with a Social Return on Investment (SROI) of 9.6. Organizers: College of Intelligent Computing & Artificial Intelligence Research Center ※ No registration needed.
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【Workshop】 2025.04.22 Workshop on Using AI Teaching Platform - Using Generative AI: RAG as an Example

2025.03.27
📅 Date: 2025/04/22 (Tuesday) 13:00 - 16:00 (Check-in starts at 12:50) 🎤 Speakers: Prof. Yu-Chung Wang, Deputy Director, AI Research Center Assistant Prof. Fu-Chiang Chou, Research Fellow, AI Research Center 📍 Location: AI Research Center, 11th Floor, Management Building, Chang Gung University 時間Time 工作坊內容Content 講師Speaker 13:00-14:30 (90 mins) AI教學平台使用教學 AI Center Teaching Platform Usage Instruction 人工智慧研究中心 副主任王佑中教授 Deputy Director\ Prof. Yu-Chung Wang, AI Research Center 14:30-16:00 (90 mins) 生成式AI:RAG技術實作 Generative AI: RAG Technology Implementation 人工智慧研究中心博士級研究助理周福強助理教授 Doctoral-level Research Assistant \ Assistant Prof. Fu-Chiang Chou, AI Research Center Intended Audience This workshop is ideal for teachers, teaching assistants, and researchers interested in utilizing AI technology in education. How to Register? Login to iCGU → Go to Event Registration System → Select Workshop on Using AI Teaching Platform 📌 Seats Available: 30 participants (Until full capacity is reached). Please bring a laptop with internet access. 📌 Workshop Credit Hours: Teachers will receive 3 hours of training credits. Participants must check in by 13:10 and attend the full session to receive credits. Partial attendance or missing check-in/check-out will not be counted towards teaching quality improvement hours. Contact Information 📞 Contact: 3001; 413-3001
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【AI Seminar】2025.04.15 AI in Drug Discovery and Development - Prof. Yufeng Jane Tseng

2025.03.25
Topic: AI in Drug Discovery and Development Speaker: Yufeng Jane Tseng.  Department of Computer Science and Information Engineering, National Taiwan University Time: 2025/04/15 (Tue) 14:00-16:00 Venue: The Management Building, 11F, AI Lecture Hall Join Online: https://reurl.cc/XAeDDa or scan QR code on poster  About the Speaker:   Professor Yufeng Jane Tseng received her B.S. degree in Pharmacy from National Taiwan University in 1997. Prof. Tseng then received her Ph.D. in Medicinal Chemistry and Pharmacognosy from the University of Illinois at Chicago (UIC) in 2002 and received the Charles Bell Award for Computational Chemistry in 2001. From 1998 to 2006, Prof. Tseng worked as a Principal Molecular Modeling Software Developer at The Chem21 Group, Inc., in Lake Forest, USA. From 2004 to 2006, Prof. Tseng also worked as a postdoctoral research fellow at the National Center for Biotechnology Information, National Institutes of Health in Bethesda, MD, USA. Prof. Tseng joined the Department of Computer Science and Information Engineering at National Taiwan University (NTU) in 2006 as an Assistant Professor and holds a joint appointment at the School of Pharmacy also at NTU. Prof. Tseng has devoted 19 years of active service in education and is a leader in computational chemistry and computer-aided drug design. Since 2009, she has founded and served as the Principal Investigator of the Metabolomics Core Laboratory at NTU. Since 2010, Prof. Tseng has been organizing and chairing the Drug Discovery Symposium at the American Chemical Society (ACS) National Meetings and continues her services at ACS to the present. In 2014, she became a Professor at the Graduate Institute of Biomedical Electronics and Bioinformatics, with the Department of Computer Science and Information, and at the School of Pharmacy. Prof. Tseng was appointed the Director of the Drug Research Center at NTU, and in 2016, she was appointed the associate Director of the Neurobiology and Cognitive Science Center at NTU. In 2019, she was appointed as the associate chair of the Computer Science and Engineering department at NTU and the center scientists at the National Center for Theoretical Sciences, Physics Division (NCTS Physics). In 2020, she was appointed as the Principal Investigator at Stanford-Taiwan Biomedical Fellowship Program, STPI. Abstract: AI or deep learning is a buzzword in recent years. How it was applied and truly helped remained vague in drug discovery and drug development. This talk is going to cover the use of computer-aided techniques as well as the true AI aided process in the CNS disease. Organizers: College of Intelligent Computing & Artificial Intelligence Research Center ※ No registration needed.
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【AI Seminar】2025.03.25 Video Understanding and Generation on Multimodal Foundation Models - Prof. Ming-Hsuan Yang

2025.03.06
Topic: Video Understanding and Generation with Multimodal Foundation Models Speaker: Ming-Hsuan Yang.  Department of Electrical Engineering and Computer Science, University of California, Merced Time: 2025/03/25 (Tue) 14:10-16:00 Venue: The Management Building, 11F, AI Lecture Hall Join Online: https://reurl.cc/b3M6rd or scan QR code on poster  About the Speaker:   Ming-Hsuan Yang is a Professor at the University of California, Merced, and a Research Scientist at Google DeepMind. He has received numerous prestigious awards, including the Google Faculty Award 2009, the NSF CAREER Award 2012, and the Nvidia Pioneer Research Award 2017 and 2018. He received Best Paper Honorable Mention at UIST 2017, Best Paper Honorable Mention at CVPR 2018, Best Student Paper Honorable Mention at ACCV 2018, Longuet-Higgins Prize (Test-of-Time Award) at CVPR 2023, Best Paper at ICML 2024, and Test-of-Time Award from at WACV 2025. Yang is an Associate Editor-in-Chief of IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) and an Associate Editor for the International Journal of Computer Vision (IJCV). Previously, he was the Editor-in-Chief of Computer Vision and Image Understanding (CVIU) and Program Co-Chair for ICCV 2019. He is a Fellow of IEEE, ACM, and AAAI. Abstract: Recent advances in vision and language models have significantly improved visual understanding and generation tasks. In this talk, I will present our latest research on designing effective tokenizers for transformers and our efforts to adapt frozen large language models for diverse vision tasks. These tasks include visual classification, video-text retrieval, visual captioning, visual question answering, visual grounding, video generation, stylization, outpainting, and video-to-audio conversion. If time permits, I will also discuss our recent findings on learning diffusion models and dynamic 3D vision. Organizers: College of Intelligent Computing & Artificial Intelligence Research Center ※ No registration needed.