(Including but not limited to the following topics)
Topic 1: Biomedical
Biomechanics and Tissue Mechanics
Biological Fluid Mechanics and Blood Flow Dynamics
Cell Mechanics and Biomechanical Biology
Biological Heat and Mass Transfer
Biological Materials and Tissue Engineering
Biological Electrical Signals and Neural Engineering
Medical Ultrasound and Optical Imaging
Magnetic Resonance Imaging Technology
X-ray Imaging and CT Reconstruction
Molecular Imaging and Multimodal Imaging
Physiological Signal Detection and Processing
Brain Science and Neural Regulation
Medical Robots and Minimally Invasive Devices
Wearable and Implantable Medical Devices
Biological Sensors and Microfluidic Chips
Digital Pathology and Medical Image Analysis
Biological System Modeling and Simulation
Drug Delivery and Pharmacokinetics
Rehabilitation Engineering and Assistive Technology
Bioinformatics and Genomic Analysis
Topic 2: Robot Vision
Vision Sensors and Calibration
Stereo Vision and Depth Estimation
Multi-view Geometry and 3D Reconstruction
Object Detection and Tracking
Semantic Segmentation and Scene Understanding
Visual Simultaneous Localization and Mapping (V-SLAM)
Visual Inertial Odometry
Pose Estimation and Object Grasping
Visual Processing in Dynamic Scenes
RGB-D and Point Cloud Processing
Event Cameras and High-Speed Vision
Active Vision and Attention Mechanism
Visual Servo Control and Motion Planning
Multi-sensor Fusion (Vision/Lidar/Guidance)
Optical Flow Fields and Motion Estimation
Visual Navigation and Obstacle Avoidance
Visual Tracking in Augmented Reality
Flexible Bodies and Object Deformation Detection
Visual Monitoring and Abnormal Behavior Analysis
Industrial Vision Inspection and Measurement
Topic 3: Machine Learning
Supervised Learning and Classification/Regression
Unsupervised Learning and Clustering/Dimensionality Reduction
Semi-supervised and Weakly-supervised Learning
Deep Learning Network Architectures
Generative Adversarial Networks and Diffusion Models
Graph Neural Networks
Reinforcement Learning and Multi-Agent
Transfer Learning and Domain Adaptation
Meta-Learning and Few-Shot Learning
Self-supervised and Contrastive Learning
Probabilistic Graphical Models and Bayesian Inference
Kernel Methods and Support Vector Machines
Ensemble Learning and Decision Trees
Interpretability and Causal Inference
Model Compression and Knowledge Distillation
Adversarial Attacks and Defense
Federated Learning and Privacy Protection
Time Series Prediction and Sequence Modeling
Hyperparameter Optimization and Automatic Machine Learning
Machine Learning Applications in Medicine/Vision