Research Directions
Artificial intelligence, Materials science, and Sustainability
Our research lies at the intersection of artificial intelligence, materials science, and sustainability. By advancing machine learning methods for vision, language, and multimodal understanding, my group develops intelligent systems that accelerate scientific discovery and address critical challenges in renewable energy, manufacturing, and chemical innovation. Our contributions span from fundamental AI benchmarks and algorithms to domain-specific applications in photovoltaic defect detection, industrial safety, and molecular property prediction. This narrative highlights our progress across three interconnected themes: (1) advancing robustness and efficiency in computer vision and foundation models, (2) enabling AI-driven solutions for photovoltaics and industrial safety, and (3) pioneering multimodal AI for chemistry and critical materials discovery with experimental Validation. The figure highlights the current research directions:
