Sorbonne Center for Artificial Intelligence (SCAI), Sorbonne University, and Institute for Datability Science (IDS), Osaka University are both young research/educational institutions responsible for AI and data science. We share the same mission of facilitating interdisciplinary research and education. 

With the success of the first edition of the SCAI-IDS joint workshop in 2021, we keep moving forward for (i) exchanging research/educational ideas cultivated in the course of each of our activities and (ii) incubating future collaboration of SCAI and IDS on AI and data science in various disciplines. In this second edition, we focus on AI and medicine, and cutting-edge researchers from both institutions who are actively working on this topic will give us wonderful talks. In addition to this, this edition of the workshop features research communication between students at both institutes for further cultivating bottom-up collaborations.

This workshop is based on the Comprehensive Academic Exchange Agreement between Sorbonne University and Osaka University concluded in May 2020.

 

PROGRAM:

Opening Session:

• 10:00 Opening I - Welcome to SCAI (Prof. Gérard Biau, Director of SCAI)
• 10:05 Opening II - Thanks from IDS (Yuta Nakashima)
• 10:10 (15 min) Introduction to SCAI (Dr Xavier Fresquet, deputy director of SCAI)
• 10:25 (15 min) Introduction to IDS (Prof. Hajime Nagahara)

AI and Medicine Session 1 (20 min/talk inc. QA):

• 10:40 Transformers for medical image analysis (Nicolas Thome, SU)
• 11:00 Explainability Matters in Medical Applications (Yuta Nakashima, IDS)
• 11:20 AI and diagnosis support in colon capsule endoscopy (Andrea Pinna, SU)

AI and Medicine Session 2 (20 min/talk inc. QA):

• 13:30 Probability-based Machine Learning and Medical Applications (Prof. Hideaki Hayashi, IDS)
• 13:50 Interactive Machine Learning: Design and Applications (Dr. Baptiste Caramiaux SU)
• 14:10 3D Cell Reconstruction from Multi-focus Microscopy Image (Prof. Hajime Nagahara, IDS)

14:30 (10 min)  Break

PhD Student Session

• 14:40  Inference time evidences of adversarial attacks for forensic on Transformers (Hugo Lemarchant, IDS)
• 14:50 Estimating the registration error of MRI brain data based on regression U-Net (Leandro Nascimento, SU) 
• 15:00 Gait Spoofing: Generation of Fake Gait Silhouette Sequence from a Single Photo with Masterization (Yuki Hirose, IDS)
• 15:10 Multimodal Representation Learning for Precision Medicine (Louis Simon, SU)
• 15:20 Deep Sensing for Compressive Video Acquisition (Michitaka Yoshida, IDS)
• 15:30 Image Analysis with hybrid AI for digestive endoscopy (Garance Martin, SU) 

15:40 Free Discussion 

Closing Session

• 16:40 Closing I (Prof Gérard Biau, SCAI)
• 16:45 Closing II (Prof. Hajime Nagahara, IDS)