Department of Artificial Intelligence

◆Event: AI Master's Program Recruitment Info Session ◆Date & Time: Jan 20, 2026 (Tue) 12:30 ◆Venue: CGU AI Research Center (Management Building 11F) ◆Speaker: Prof.  Hsien-Tsung Chang, Chair of Department of AI ◆Agenda: 1. Introducing the faculty and research focus of the Master's Program of Department of Artificial Intelligence 2. Panel-style Q&A - Explain everything you don't understand. 3. On-site and online hybrid event 4. Lunch boxes provided ◆Content: 1. On-site and online hybrid event 2. Lunch boxes provided ( Limited to individuals who are not currently enrolled graduate students of CGU, who complete online registration by 12:00 on Jan 19, 2026, and attend in person to collect.) ◆Registration: https://docs.google.com/forms/d/e/1FAIpQLSepPI7mFP4VgofLVn6uks2GxXq84O_Y-mV1jnCDklk_Kzv3-w/viewform

Topic: Integrating genetics, multimodal medical imaging, and AI for high-precision risk prediction of type 2 diabetes Speaker: Hsin-Chou Yang, Ph.D. Research Fellow and Director of the Institute of Statistical Science, Academia Sinica Time: December 24, 2025 (Wednesday), 12:10 – 14:00 p.m. Venue: The Management Building, 11F, AI Lecture Hall or Livestreaming https://reurl.cc/R9Ynp6 Registration: https://forms.office.com/r/YGHweb7HNT or scan QR code on poster  About the Speaker:   Dr. Hsin-Chou Yang is a statistician, bioinformatician, and data scientist at Academia Sinica, where he is a Full Research Fellow and Director. His work integrates methodological innovation with biomedical applications, including major studies on the Han Chinese cohort (Nature), AI-based diabetes prediction (Nature Communications), and COVID-19 viral subtypes (PNAS). He is an elected ISI and GYA member, recipient of multiple national awards, active journal editor/reviewer, conference chair, and mentor to young scientists. Abstract: In this talk, the speaker will share how the team combined genetics, medical imaging, and rich health data from over 131,000 Taiwan Biobank participants to better understand and predict Type 2 Diabetes (T2D). Using AI—from deep learning on raw images to polygenic and imaging risk scores—the study uncovered genetic links, causal relationships, and new insights into how the body signals T2D risk. The integrated model achieved an AUC of 0.944, demonstrating strong potential for scalable, real-world precision health. Organizers: Institute of Health Data Science ※ Registration needed.  

Curious what top engineers in the U.S. really do day to day? Want to hear authentic insights from a Google AI Platform engineer and a former Machine Learning Engineering Manager at Accenture? Don’t miss this event! Join Stephen and Rohisha as they share what life is truly like as engineers in the U.S., giving you a clearer picture of careers in AI/ML and data science—and inspiring your own path forward. Seats are limited, so sign up now! Time: December 4, 2025 (Thursday), 12:10 – 14:00 p.m. Venue: 14th Floor, CoIC Conference Room, Management Building Registration: https://forms.office.com/r/VBSgJpV4L8 or scan QR code on poster  About the Speaker:   Stephen Koo is a Staff Software Engineer at Google specializing in AI and backend systems. He leads the evaluation infrastructure for AI features on the Workspace AI Platform team and previously worked on the core serving stack for Generative AI in Workspace. Before that, he was on the Gmail & Chat team focusing on reliable email processing and smart features. He also developed deep learning models for speech recognition and helped rebuild Stanford AI’s CodaLab platform. He holds an M.S. and B.S. from Stanford.   Rohisha Adke was most recently a Machine Learning Engineering Manager at Accenture, leading teams that built data science and machine learning solutions for clients across energy, retail, healthcare, and tech. She began as a data scientist in Accenture’s global Data Science Center of Excellence, working with clients and tech partners to develop data and ML solutions. She also enjoyed co-presenting at conferences and mentoring aspiring technologists. Rohisha holds an M.S. in Statistics and a B.S. in Mathematical & Computational Science from Stanford and is currently on sabbatical. Abstract: Join us to hear from Stephen Koo, an AI engineer at Google, and Rohisha Adke, former Machine Learning Engineering Manager at Accenture. They will share their experiences, key skills, and challenges working as engineers in the U.S. tech industry across AI, data science, and machine learning fields. Organizers: CoIC ※ Registration needed.

Topic: Metaverse-enabled Precision Health Speaker: Tony Hsiu-Hsi Chen, PhD. Distinguished Professor, Institute of Health Data Analytics and Statistics, National Taiwan University Time: November 25, 2025 (Tuesday), 12:10 – 14:00 p.m. Venue: The Management Building, 11F, AI Lecture Hall or Livestreaming https://reurl.cc/oKx6Dg Registration: https://forms.office.com/r/nBdAaDsgsZ or scan QR code on poster  About the Speaker:   Prof. Hsiu-Hsi Chen specializes in evaluating population-based cancer screening and vaccination programs using advanced statistical models. His work addresses complex issues and develops health economic decision models. Key publications include studies on gastric, colorectal, breast, and oral cancer screening in top journals like JAMA and Gut. He has contributed significantly to stochastic process methods in cancer screening evaluation, published in leading statistics journals. Since 2004, he has chaired the International Asian Cancer Screening Conference Network and collaborated internationally, earning the Finland Distinguished Professor award. Prof. Chen has published over 460 peer-reviewed articles by 2025. Abstract: Metaverse-enabled Precision Health combines AI, digital twin technology, and immersive AR/MR to create a precision screening and prevention system across diseases. For example, COVID-19 digital twins simulate infection dynamics for real-time outbreak prediction and resource optimization. In chronic disease, hypertension digital twins integrate monitoring and lifestyle data for personalized risk and prevention. Cancer models use AI to analyze imaging and genetics, improving early detection and screening schedules. This approach enables dynamic, personalized health management by linking predictive modeling with clinical and public health settings, advancing P4 medicine and fostering an integrated digital health ecosystem for precision prevention. Organizers: Graduate Institute of Health Data Science ※ 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.