Artificial Intelligence Research Center

*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 Jun 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:  August 1, 2026 or February 1, 2027  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: The development of clinical AI cycle: from signal discovery to pragmatic trials and real-world deployment Speaker: Professor Chin Lin, Department of Medicine, National Defense Medical University Time: March 11, 2026 (Wednesday), 12:10 – 14:00 p.m. Venue: The Management Building, 11F, AI Lecture Hall or Livestreaming https://reurl.cc/GG72GG Registration: https://reurl.cc/R9AMeD or scan QR code on poster  About the Speaker:   Dr. Chin Lin is a data scientist whose work centers on establishing clinical evidence standards for medical artificial intelligence. His research integrates large-scale electronic health records, electrocardiography, medical imaging, and home-based sensing to develop AI systems that are not only accurate, but clinically actionable and outcome-improving. He has led or co-led more than ten pragmatic randomized controlled trials evaluating AI-enabled clinical workflows, with results published in Nature Medicine, NEJM AI, Radiology, and Nature Communications. His team developed an AI-ECG platform that has received TFDA approval and USFDA Breakthrough Device Designation, has been transferred to industry, and deployed across multiple hospitals and rural screening programs. A central theme of his work is treating AI not as a standalone model, but as a system-level intervention that links prediction, clinical action, and patient outcomes within real-world healthcare environments. Abstract: Recent advances in artificial intelligence (AI) have shifted medical AI research from model-centric performance reporting toward evidence-based clinical impact. In this talk, I introduce the concept of the clinical AI cycle, a comprehensive framework that describes how clinical AI can progress from signal discovery, through pragmatic clinical trials, to real-world deployment in healthcare systems. At the stage of signal discovery, I will illustrate how routinely collected data—such as electrocardiograms (ECGs), chest radiographs (CXRs), and electronic health records (EHRs)—can be leveraged using data-driven approaches and multimodal foundation models to identify latent disease risks. This paradigm enables a single examination to support opportunistic screening for multiple diseases, overcoming the traditional one-test-one-disease limitation. The second stage focuses on pragmatic trials, where AI models are evaluated not merely by predictive accuracy but by their ability to trigger pre-specified clinical actions and improve patient outcomes. By embedding AI alerts into real clinical workflows and evaluating them using randomized controlled and digital trial platforms, AI is positioned as an actionable decision engine rather than a passive prediction tool. Finally, in real-world deployment, I will demonstrate how clinical AI can be scaled to community screening, home healthcare, and wearable devices, and integrated with large-scale health databases. This deployment completes the clinical AI cycle, allowing continuous learning, post-deployment surveillance, and discovery of new clinical insights. Organizers: Institute of Health Data Science ※ Registration needed.

Topic: Merging Sensors, AI, and VR for Athlete Training   Speaker: Prof. Min-Chun Hu — Associate Chair, Department of Computer Science at National Tsing Hua University.   Time: March 10, 2026 (Tuesday), 2:00 – 4:00 p.m.   Venue: The Management Building, 11F, AI Lecture Hall   Join Online: https://reurl.cc/EbkDzv or scan QR code on poster   About the Speaker:    Dr. Min-Chun Hu received her Ph.D. from the Graduate Institute of Networking and Multimedia, National Taiwan University in 2011. After graduation, she worked as a postdoctoral researcher at the Research Center for Information Technology Innovation in Academia Sinica, and later served as an assistant/associate professor in the Department of Computer Science and Information Engineering at National Cheng Kung University. She is currently a professor in the Department of Computer Science at National Tsing Hua University. Dr. Hu has been recognized with numerous awards, including Exploration Research Award of Pan Wen Yuan Foundation (2015), Outstanding Young Researcher Award from the Computer Society of the Republic of China (2017), IEEE Tainan Section Best Young Professional Member Award (2018), Google Research exploreCSR Award (2021-2024), CES Innovation Awards (2023), and NSTC Ta-You Wu Memorial Award (2023). Her research interests encompass digital signal processing, multimedia content analysis, computer vision, computer graphics, virtual reality, and augmented reality. As a passionate basketball enthusiast, she has long been dedicated to developing sports technology that assists athletes in training and performance analysis. Dr. Hu previously served as Deputy Executive Director of the Taiwan Institute of Sports Science and is also the co-founder of NeuinX, a startup specializing in AI technology for sports analysis. Abstract:   Tactical and skill training play a crucial role in athletic development. With the support of artificial intelligence (AI) technology, it is now possible to track the ball and players to detect fine-grained events, helping coaches collect detailed statistics and infer each team’s tactics. Additionally, virtual reality (VR) technology can be leveraged to enhance both the effectiveness and experience of tactical and skill-based training. This talk will introduce modern systems that utilize AI and VR to help athletes conveniently gather valuable sports data and improve a wide range of skills.   Organizers: College of Intelligent Computing & Artificial Intelligence Research Center   ※ No registration needed.

Topic: How to Know Earlier? Using Machine Learning to Identify the Risk of Disease Development - the Case of Glaucomatous Neuropathy Speaker: Dr. Cezary Mazurek , Poznan Supercomputing and Networking Center Time: December 16, 2025 (Tuesday), 11:00–12:00 p.m. Venue: The Management Building, 11F, AI Lecture Hall About the Speaker: Dr. Cezary Mazurek, Computer Scientist, his professional activity has been associated with the development of the Poznan Supercomputing and Networking Center (PCSS) since its establishment in 1993. He served as CEO of PCSS from 2019 to 2024 and at that time he successfully brought it onto the path of developing infrastructure and applications of quantum computing and AI, and is now continuing this thread with a focus on applications in Life Sciences and Personalized Medicine. For over 30 years, he has been involved in the development of Polish and European e-infrastructure for science and is currently one of the most experienced leaders in R&D projects, many of which he has successfully implemented in practice. To date, he has led development of more than 40 national and international R&D projects. His R&D work has focused on integrating various specialized software components into consistent systems for digital science with emphasis on software governance. In recent years, he has been involved in the development of domain research infrastructures, such as for digital humanities, as well as for personalized medicine.   Cezary’s scientific activities mainly focus on applying machine learning methods for early detection of disease development mechanisms. A solution led by him to support pre-symptomatic diagnosis of glaucoma development using machine learning received patent protection from the Japan Patent Office in 2023 and from European Patent Office in 2025. He is currently extending his interests to advanced methods of data collection and analysis in a digital twin model. He is author or co-author of over 100 papers in professional journals and conference proceedings. Since 2020 the President of Wielkopolska ICT Cluster. Since 2023 the member of GÉANT Association Board of Directors. In 2024 he initiated the establishment of a national consortium EBRAINS-PL and became the member of EBRAINS National Node Board. IEEE Senior Member, member of IEEE Computer Society as well as IEEE Computational Intelligence Society. Abstract: In recent years, there has been a significant increase in the number of studies on the role of artificial/assisted intelligence in the diagnosis of eye diseases. Scientific work in this field is mainly based on the analysis of imaging examinations. However, the development of diseases is very often caused by functional disorders that remain hidden for many years and are not immediately visible in the form of clinical symptoms. An example of such diseases is glaucomatous neuropathy. Since 2014, we have been working in a transdisciplinary team on intelligent decision support technology in the functional diagnosis and treatment of glaucomatous neuropathy. The functionality of the developed software platform is based on the assessment of non-intraocular-pressure risk factors in the development of glaucomatous neuropathy, enabling glaucoma specialists to be supported in the recognition, quantification, and differential diagnosis of glaucomatous neuropathy. The developed system, based on a predictive model, enables the identification of individuals with ocular hypertension at significantly high risk of conversion to primary open-angle glaucoma, as well as the assessment of the effectiveness of glaucoma therapy. The solution has been patented in Japan and Europe. The above example shall also help to present the latest trends in our research work on neurodegenerative diseases and brain health initiated around the EBRAINS research infrastructure, artificial intelligence, and quantum computing technology. Organizers: College of Intelligent Computing & Artificial Intelligence Research Center ※ No registration needed.

Topic: Agentic AI in Action: Integrating Autonomous Systems at NCHU Speaker: Dr. Da-Sheng Lee – Lifetime Distinguished Professor, National Taipei University of Technology & Director, Taipei Smart City Project Management Office" Time: November 11, 2025 (Tuesday), 2:00 – 4:00 p.m. Venue: The Management Building, 11F, AI Lecture Hall Join Online: https://reurl.cc/K9VY6n or scan QR code on poster About the Speaker:   Dr. Da-Sheng Lee is a Lifetime Distinguished Professor at National Taipei University of Technology and holds multiple leadership roles, including Director of TPMO and Technical Director at ITRI’s Green Energy Labs. He integrates academia, industry, and research to implement energy-saving and carbon-reduction technologies. His team has assisted over 100 factories across 19 sectors in Taiwan, optimizing air compressors, chillers, cooling towers, and boilers, and introduced AI-driven solutions achieving deep industrial energy savings. From 2015–2024, he published 28 SCI papers on AI for energy efficiency, with 47 SCI/EI papers total, earning recognition as a top global author and a 2024 Stanford World’s Top 2% Scientist. Abstract: Since 2016, Taipei’s TPMO has implemented 315 PoC projects to advance smart city development. By 2024, Taipei ranked 16th in the Smart City Index and 27th in the Cities in Motion Index, while carbon emissions fell 11.9% from 12,409,700 to 10,931,500 tons CO₂, showing that smart initiatives also drive sustainability. Using a five-stage framework to standardize PoC data, the study finds collaboration between large corporations and SMEs/startups forms an “economy co-evolution loop,” key for intelligence and sustainability. A six-stage AI-Driven Smart City Framework is proposed, integrating city-scale evaluation, AI research loops, and PoC duplicate loops to guide citywide AI deployment. Organizers: College of Intelligent Computing & Artificial Intelligence Research Center ※ No registration needed.