Yabin Dang

IBM Research (China)

Papers

2

Total Citations

9

H-Index

2

About

Yabin Dang is a researcher at the forefront of applying artificial intelligence to business process management and enterprise service automation. His work primarily focuses on automatic business process discovery, where he has pioneered the use of advanced neural architectures like Ordered Neurons LSTM to extract structured process models from unstructured textual documentation. This approach addresses a critical bottleneck in BPM implementation, significantly reducing the time and cost traditionally required for manual process mapping. Dang’s research also explores the intersection of automated planning and enterprise services, identifying both opportunities and challenges in deploying AI-driven decision-making within complex organizational workflows. With his most cited work accumulating 6 citations, Dang’s contributions are gaining traction among practitioners seeking to streamline digital transformation. His studies highlight the potential for deep learning to bridge the gap between natural language descriptions and executable process models, offering a practical pathway toward fully automated business process management.

Research Focus

Key Achievements

2
H-Index
2
Papers
9
Total Citations
5
Avg Citations/Paper
🏆 Most Cited Paper
Automatic Business Process Structure Discovery using Ordered Neurons LSTM: A Preliminary Study
6 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: IBM Research (China)

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago