MBZUAI Visiting Professor Haiyan Huang is working on bridging biology and AI by incorporating domain knowledge into modeling frameworks. She combines statistical principles, AI tools, and domain expertise to develop scientifically informed and statistically grounded methods. Her work addresses the challenge of extracting meaningful signals from complex biological data. Why it matters: This interdisciplinary approach can lead to more accurate and useful AI models for biological research and healthcare applications in the region.
Pascal Fua from EPFL gave a talk at MBZUAI on physics-based deep learning for medical imaging. The talk covered how self-supervision and knowledge of human anatomy and physics can improve deep learning algorithms when training data is limited. Applications discussed included endoscopic heart surgery, colonoscopy, and intubation. Why it matters: This highlights the growing importance of domain knowledge and self-supervision in overcoming data scarcity challenges for AI in healthcare applications within the region.
Ian Reid, a Professor of Computer Science at the University of Adelaide, gave a talk at MBZUAI on leveraging deep learning to go beyond geometric SLAM. The talk covered using prior domain knowledge to improve map and shape estimation and enabling navigation in unvisited environments. The research aims to turn cameras into devices for flexible, large-scale situational awareness or "Spatial AI" sensors. Why it matters: Integrating deep learning with SLAM could significantly advance robotic navigation and spatial understanding, with applications for autonomous systems in various industries.
MBZUAI Visiting Professor Haiyan Huang is working on bridging biology and AI by incorporating domain knowledge into modeling frameworks. She combines statistical principles, AI tools, and domain expertise to develop scientifically informed and statistically grounded methods. Her work addresses the challenge of extracting meaningful signals from complex biological data.