Yingfu Lin

University of Michigan–Ann Arbor

Papers

2

Total Citations

80

H-Index

2

About

Yingfu Lin is a leading researcher at the intersection of organic chemistry and data science, whose work is revolutionizing how new chemical reactions are discovered. His primary research focus is the development of software and computational tools to enable high-throughput experimentation (HTE) in the chemical laboratory. Lin’s most significant contribution is the creation of a novel platform for the rapid planning and analysis of high-throughput experiment arrays. This work, detailed in his highly cited 2023 publication (71 citations), directly addresses a critical bottleneck in modern reaction discovery: the need for sophisticated software to manage and extract insights from the vast datasets generated by HTE. By providing chemists with a powerful tool to design, execute, and interpret complex experimental arrays, Lin is accelerating the pace of innovation in synthetic chemistry. His contributions are not merely theoretical; they provide a practical, accessible solution that empowers researchers to move beyond traditional, one-at-a-time experimentation. Through his pioneering work, Yingfu Lin is helping to usher in a new era of data-driven reaction discovery, making the search for novel chemical transformations faster, more efficient, and more insightful.

Research Focus

Key Achievements

2
H-Index
2
Papers
80
Total Citations
40
Avg Citations/Paper
🏆 Most Cited Paper
Rapid planning and analysis of high-throughput experiment arrays for reaction discovery
71 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 10
🏛 Institutions: University of Michigan–Ann Arbor

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago