Scientific AI and Intelligent Simulation
Overview
Applying AI to scientific discovery and simulation, with emphasis on differentiable simulation, physics-informed learning, and AI for science.
Key Questions
- How can AI accelerate scientific simulation without sacrificing physical fidelity?
- What role can differentiable simulation play in end-to-end optimization of scientific models?
- How can multimodal AI systems handle complex scientific documents and data?
Our Contributions
- Developed multimodal AI systems for specialized document analysis
- Explored AI applications in legal and scientific domains
Recommended Papers
Presents a multimodal AI system that combines visual and textual understanding for comprehensive legal document analysis, demonstrating the potential of AI in specialized domain applications.
Recent Work
Presents a multimodal AI system that combines visual and textual understanding for comprehensive legal document analysis, demonstrating the potential of AI in specialized domain applications.
Open Problems
- Bridging the gap between data-driven and physics-based models
- Ensuring interpretability and trustworthiness of AI in scientific applications
- Scaling differentiable simulation to complex real-world systems
Prospective Student Projects
- Differentiable simulation for engineering optimization
- Physics-informed neural networks for dynamic system modeling
- AI-assisted scientific literature mining and knowledge graph construction