Shimin Su
Papers
1
Total Citations
45
H-Index
1
About
Shimin Su is a rising leader at the intersection of artificial intelligence and synthetic chemistry, where their work is redefining how chemical reactions are predicted and optimized. Their research centers on developing deep learning frameworks that can accurately forecast reaction outcomes, a critical challenge for accelerating drug discovery and materials development. In their landmark 2023 study, Su introduced a novel approach that not only achieves high accuracy in reaction prediction but also demonstrates robust performance when applied to real-world high-throughput experimentation data—a feat that bridges the gap between computational models and practical lab workflows. This work has already garnered 45 citations, signaling its rapid influence on both the AI and chemistry communities. By tackling the dual hurdles of reaction representation and data scarcity, Su's contributions are paving the way for more efficient, data-driven experimental design. Their achievements underscore a commitment to transforming how chemists harness machine learning, making complex synthetic planning more accessible and reliable for researchers worldwide.
Research Focus
Key Achievements
Top Papers
- 1