Welcome to join this lecture and learn how data science and AI technologies can help advance medical research and clinical care toward a smarter future!

📌The lecture will introduce the use of hashing algorithms for estimating similarity measures, and explain how combining maximum likelihood estimation (MLE) and control variates can improve the efficiency and accuracy of data analysis and model inference. The speaker will approach the topic from the perspective of statistics and machine learning, showing the theoretical connection and practical potential between the two methods.

These techniques can help build faster and more reliable AI models for medical applications, supporting clinical decision-making and precision medicine in practice.

 📅 Lecture Information

▪️ Topic: Maximum Likelihood Estimation and Control Variates with Hashing Algorithms
▪️ Speaker: Keegan Kang (Assistant Professor of Statistics, Bucknell University)
▪️ Date & Time: October 22, 2025 (Wednesday), 12:10–13:30
▪️ Venue: Room IR630, 6th Floor, International Academic Research Building, Kaohsiung Medical University

▪️ Registration Link: https://forms.gle/gueA7oMzVWshRQPh7
▪️ Registration Deadline: Until 12:00 PM, October 20, 2025 (Monday); online registration only
▪️ Format: Hybrid (On-site: 60 participants; Online: unlimited)
▪️ Organizer: Biomedical Artificial Intelligence Academy, Kaohsiung Medical University

▪️ Note: ☕ Lunch will be provided for on-site participants. Everyone is welcome to join!

※ This lecture is eligible for KMU faculty growth credits. Participants must complete both sign-in/out and the satisfaction survey to receive credit points.

We look forward to your participation!