Systematic Construction

Systematic construction focuses on developing efficient and reliable methods for building complex systems, ranging from neural networks for modeling dynamical systems to large-scale knowledge graphs and realistic 3D data augmentations. Current research emphasizes algorithmic approaches, including gradient-free optimization for neural architectures, grammar-based frameworks for constrained text generation, and iterative construction methods for diverse data augmentation and large-scale NeRFs. These advancements improve the accuracy, scalability, and efficiency of various applications, from robotics and autonomous driving to natural language processing and knowledge representation.