📅 Date: Thursday, 3rd July, 9 AM – 10 AM (Hanoi, GMT +7)
🛎 Format: Offline
📍 Venue: VISHC Open Space, VinUniversity

🎙 Speakers:
1️⃣ Tri Phan, PhD Student, VinUniversity
🗣 Topic: INTELLIGENT CALIBRATION OF SOFT FILAMENT SENSORS FOR ENHANCED JOINT MONITORING AND REHABILITATION
💡 Abstract: Soft sensors offer great potential for joint monitoring and rehabilitation due to their ability to conform to the human body. However, the inherent challenges of nonlinearity, hysteresis, and long-term drift in soft sensors hinder their effective real-world application. In this talk, Tri Phan will discuss an intelligent calibration method to compensate for drift, ensuring reliable and accurate data over time. Focusing on knee rehabilitation, he will show how this approach leads to a wearable, user-friendly, and cost-effective joint support system with integrated soft filament sensors. This method enhances sensor performance and contributes significantly to the practical application of soft sensors in joint rehabilitation.

📌 Speaker Short Bio: Tri Phan is currently a Ph.D. student in Computer Science at VinUniversity under the supervision of Dr. Thai Mai Thanh and Dr. Hieu Pham. His research focuses on biorobotics, specifically applying machine learning techniques to Soft Filament Sensors for joint rehabilitation.

2️⃣ Huyen Le, PhD student, VinUniversity
🗣 Topic: TOWARDS AI-BASED QUANTITATIVE ANALYSIS OF SARCOMERE ORGANIZATION IN HUMAN-INDUCED PLURIPOTENT STEM CELL-DERIVED CARDIOMYOCYTES (HIPSC-CMS)
💡 Abstract: hiPSC-CMs are an invaluable tool for cardiovascular research and clinical applications. Maturation of sarcomere organization is essential for their contractile function and structural integrity. However, traditional assessment methods such as manual annotation are labor-intensive and unsuitable for high-throughput analysis. This talk introduces the creation of a publicly available dataset of hiPSC-CMs from healthy Vietnamese individuals and HCM patients. In the second phase, deep learning techniques will be integrated for automated, rapid, and unbiased structural assessment of sarcomeres and myofibrils. Finally, future plans include exploring label-free imaging techniques capable of visualizing the subcellular structure of hiPSC-CMs.

📌 Speaker Short Bio: Huyen Le is a current Ph.D. student in Computer Science at VinUni-Illinois Smart Health Center (VISHC), VinUniversity. Her research focuses on AI in biomedical imaging, particularly polarized light imaging and machine learning for antiviral drug evaluation. She aims to develop tools facilitating biomedical research and new discoveries.