Artificial Intelligence Research Center

Call for Participation and Poster: Dec 12 “Medical AI Workshop: Making AI Safe and Healthy (MASH)” at ACML 2025 Chang Gung University will host the Medical AI Workshop: Making AI Safe and Healthy (MASH) on December 12, 2025 (Friday), in conjunction with the Asian Conference on Machine Learning (ACML 2025). The workshop is jointly organized by the College of Intelligent Computing and the Artificial Intelligence Research Center, and will feature distinguished AI scholars as invited speakers. The workshop is also calling for poster submissions related to Medical AI research. Scholars and researchers from Taiwan and abroad are welcome to submit: 1.     Online Submission: Upload PDF files to submission link, https://sites.google.com/view/acml-2025-medical-ai-forum/call-for-short-presentations-posters?authuser=0 2.     Submission Deadline: October 12, 2025 3.     Notification of acceptance: October 20, 2025 Workshop Information 1.Date: December 12, 2025 2.Venue: Hua Nan Bank International Convention Center (No. 123, Songren Road, Xinyi District, Taipei, Taiwan) 3.Workshop website: https://sites.google.com/view/acml-2025-medical-ai-forum/home 4.Registration link: https://www.acml-conf.org/2025/registration.htm 5.Online registration deadline: November 30, 2025

*Full-Time Research Fellow Invitation* Assistant/ Associate/ Full Research Fellows in Artificial Intelligence Research Center, Chang Gung University Artificial Intelligence Research Center (AIC) at Chang Gung University (CGU) currently invites applications for full-time Assistant, Associate, and Full Research Fellows. There are 2 positions to be filled. Research Fellow Positions: We are looking for candidates with research areas in machine learning, computer vision, natural language processing, smart medicine, smart manufacturing, robotics, metaverse and human-computer interaction. Candidates should have a Ph.D. degree in Artificial Intelligence, Computer Science, Data Science, Engineering, Biomedical or related areas. Senior candidates must demonstrate significant research achievement, and have an international reputation such as strong publication records, patents, industrial experience, or other academic achievements. CGU AIC is a research-oriented institute and teaching duties are not required. Application Deadline: (1)   There is no application deadline. However, applications received by January 15, 2026 will receive the fullest consideration. (2)   Application materials will be reviewed on a first-come, first-served basis. (3)   Interview date/time will be set up promptly if an application has received a favorable opinion by the committee. Online interviews can be arranged. Starting Date:  February 1, 2026 or August 1, 2026 CGU Artificial Intelligence Research Center offers an internationally competitive compensation package commensurate with the candidate’s professional experience. Successful candidates will be appointed at the level of Assistant, Associate or Full Research Fellow according to qualifications. Application Requirements: (1)   Cover letter (one-page). (2)   CV with higher academic degree details (undergraduate to Ph.D.), professional experiences, research statement, publication list, and a list of three professional references. (3)   Chang Gung University is an equal-opportunity employer following the international standard for diversity and inclusion. Applicants from all regions and nationalities are welcome. (4)   Please submit your application in PDF files or in a cloud storage link to Ms. Sue Liu (sueliu@cgu.edu.tw). About AIC @ CGU Artificial Intelligence Research Center (AIC), established with the support of the Formosa Plastics Group (one of the largest private enterprises in Taiwan), is a research center in the Chang Gung University (CGU). In addition to the Formosa Plastics Group companies, AIC works closely with the Chang Gung Medical Foundation (the largest healthcare system in Taiwan) on advanced medical research projects, as well as other research centers in Chang Gung University. AIC also has strong connections with many world-leading high-tech companies in Taiwan. AIC researchers work closely with the faculty in the College of Intelligent Computing (CoIC), many with joint appointments from both units. CoIC is the first academic college in Taiwan devoted to the research and education of the AI technology and application. CoIC has many highly-reputed research faculty with a strong international and/or industrial working experience. AIC researchers and CoIC professors conduct joint research projects using AIC’s server hardware, IoT equipment and other research facilities. The center/college joint research eco-system further provides the support for CGU university-wide and international AI research activities. Chang Gung University (CGU), a student centric and research-directed university with entrepreneurial spirits, was established by the founding Wang family of the Formosa Plastics Group. CGU is highly ranked globally in the QS World Universities Rankings 2023, and in the top 5 among the 151 universities in Taiwan. CGU has 4 colleges: College of Medicine, College of Engineering, College of Management, and College of Intelligent Computing. CGU offers a student-faculty ratio of 12:1, with ~7,000 students, ~600 full-time faculty and ~665 adjunct faculty members. The University strives for excellence in research, teaching, and innovative technology commercialization. Under strong support from the Formosa Plastics Group and the Chang Gung Medical Foundation (the largest private-owned healthcare system in Taiwan), CGU provides advanced yet practical training on industrial technology and medical sciences. CGU is located in the suburban area of the Taipei city, about 30 minutes to the city center by Metro (Mass Rapid Transit). For details about Chang Gung University, please visit  https://www.cgu.edu.tw/en Learn more about CGU: https://www.cgu.edu.tw/en AIC: https://www.cgu.edu.tw/aic-en

Topic: Artificial Intelligence: Deep Learning versus Green Learning   Speaker: Dr. Jay Kuo, Distinguished Professor of Electrical and Computer Engineering and Computer Science, University of Southern California   Time: October 21, 2025 (Tuesday), 2:10 – 3:00 p.m.   Venue: The Management Building, 11F, AI Lecture Hall   Join Online: https://reurl.cc/EQlmra or scan QR code on poster   About the Speaker:    Dr. C.-C. Jay Kuo received his Ph.D. from the Massachusetts Institute of Technology in 1987. He is now with the University of Southern California (USC) as the Ming Hsieh Chair Professor, a Distinguished Professor of Electrical and Computer Engineering and Computer Science, and the Director of the Media Communications Laboratory. His research interests are in visual computing and communication. He is an Academician of Academia Sinica and a Fellow of AAAS, ACM, IEEE, NAI, and SPIE.   Dr. Kuo has received a few awards for his research contributions, including the 2010 Electronic Imaging Scientist of the Year Award, the 2010-11 Fulbright-Nokia Distinguished Chair in Information and Communications Technologies, the 2019 IEEE Computer Society Edward J. McCluskey Technical Achievement Award, the 2019 IEEE Signal Processing Society Claude Shannon-Harry Nyquist Technical Achievement Award, the 72nd annual Technology and Engineering Emmy Award (2020), and the 2021 IEEE Circuits and Systems Society Charles A. Desoer Technical Achievement Award. Dr. Kuo was the Editor-in-Chief of the IEEE Transactions on Information Forensics and Security (2012-2014) and the Journal of Visual Communication and Image Representation (1997-2011). He is currently the Editor-in-Chief for the APSIPA Trans. on Signal and Information Processing (2022-2023). He has guided 181 students to their Ph.D. degrees and supervised 31 postdoctoral research fellows.   Abstract:   The term “Artificial Intelligence (AI)” was coined in 1956. The field evolved slowly in the first 55 years. Yet, we have witnessed rapid advances in AI in the last decade. A recent successful example is the emergence of large language models. In this talk, I will shed light on two issues. First, I will explain the reasons for the advancement of AI in the last decade. Simply speaking, modern AI relies on numerous training samples that contain input/output pairs. An AI system provides a data-fitting solution to capture input and output mapping. Second, I will present two data–fitting methodologies: deep learning (DL) and green learning (GL). Although DL is dominant today, it is neither interpretable nor sustainable. Developing an alternative, interpretable, and sustainable AI methodology is challenging but essential. I have researched this problem since 2015. GL models offer energy-efficient AI solutions in cloud centers and mobile/edge devices. They have been successfully applied to various applications. I will use several medical imaging examples to highlight the differences between DL and GL solutions.     Organizers: College of Intelligent Computing & Artificial Intelligence Research Center   ※ No registration needed.

Topic: A Unified Framework to Calculate Every Deep Learning Architecture by Hand Speaker: Dr. Tom Yeh, Assistant Professor, Department of Computer Science, University of Colorado Boulder Time: October 14, 2025 (Tuesday), 2:00 – 4:00 p.m. Venue: The Management Building, 11F, AI Lecture Hall Join Online: https://reurl.cc/K9n8dM or scan QR code on poster  About the Speaker:   Prof. Tom Yeh leads the Imagine AI Lab at the University of Colorado Boulder. His research and teaching spans AI, HCI, Education, Ethics, and Neuroscience. He published more than 150 papers. He is the author of the popular AI by Hand ✍️ series, with by more than 160K followers across LinkedIn, X, and Substack. At his university, Prof. Tom Yeh received several awards, including the Student Affair Faculty of the Year Award. Abstract: I will present AI by Hand, a new framework I developed to demonstrate the core calculations of a wide range of deep learning architectures by hand, including basic building blocks such as artificial neuros and multi-layer perceptron, well-known architectures such as the transformer,, and state-of-art architectures such as the Diffusion Transformer and the Switch Transformer. Organizers: College of Intelligent Computing & Artificial Intelligence Research Center ※ No registration needed.

Topic：From Data to Action: Leveraging AI, Big Data, and Modeling for Precision Health and Epidemic Prevention   Speaker:  Hsiao-Hui Sophie Tsou from Institute of Population Health Sciences 、 National Health Research Institutes   Time: 2025/10/01 (Wed)  12:10-14:00   Venue: The Management Building, 11F, AI Lecture Hall   Registration link: https://pse.is/86j68c or you can scan the link from the poster   Abstract:   In healthcare research and development, the integration of modeling, big data, and artificial intelligence (AI) with advanced scientific tools has become a driving force for innovation. These approaches not only enhance our understanding of complex diseases but also improve the evaluation of medical and public health interventions. This presentation will highlight the expanding role of big data in infectious disease epidemiology, with a particular focus on applications in disease surveillance, predictive modeling, and the assessment of intervention effectiveness. We will also share a comparative analysis of COVID-19 containment strategies across 50 regions, providing insights into policy impact and response effectiveness. In addition, the potential of AI for advancing precision health will be demonstrated, showcasing how personalized approaches can transform healthcare delivery. Finally, we will discuss future challenges and opportunities for the continued development and implementation on infectious disease.