Zhunzhun Yu
Papers
1
Total Citations
45
H-Index
1
About
Zhunzhun Yu is at the forefront of integrating artificial intelligence with chemical synthesis, specializing in deep learning frameworks for reaction prediction and high-throughput experimentation. Her landmark 2023 paper, "A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data," has already garnered 45 citations, reflecting its immediate impact on the field. Yu’s major contribution lies in developing novel representations of chemical reactions and leveraging scarce reaction data to train robust AI models, overcoming key barriers that have long hindered the application of machine learning to organic chemistry. By demonstrating how deep learning can accurately predict reaction outcomes from high-throughput experimental datasets, she has opened new pathways for accelerating drug discovery and materials development. Her work bridges the gap between computational methods and practical laboratory workflows, offering chemists powerful tools to design and optimize synthetic routes with unprecedented efficiency. Yu’s research continues to push the boundaries of what AI can achieve in chemistry, making her a rising leader in the emerging field of digital synthesis.
Research Focus
Key Achievements
Top Papers
- 1