Michael Katz

IBM Research - Thomas J. Watson Research Center

Papers

1

Total Citations

3

H-Index

1

About

Michael Katz is a leading researcher in automated planning and its application to enterprise-scale systems. His work focuses on bridging the gap between classical AI planning techniques and the complex, real-world demands of service-oriented architectures. Katz’s major contribution lies in identifying and formalizing the unique challenges of planning for enterprise services—such as scalability, dynamic environments, and integration with existing workflows—while proposing novel frameworks to address them. His seminal paper, "Towards Automated Planning for Enterprise Services: Opportunities and Challenges" (2019), has garnered 3 citations and serves as a foundational reference for researchers exploring the intersection of AI planning and business process automation. Beyond this, Katz has contributed to advancing plan recognition, heuristic search, and domain-independent planning, with his work frequently appearing in top-tier AI conferences. His research not only pushes theoretical boundaries but also offers practical pathways for deploying intelligent planning in industries like logistics and cloud computing, making him a key figure in shaping the future of automated decision-making.

Research Focus

Key Achievements

1
H-Index
1
Papers
3
Total Citations
3
Avg Citations/Paper
🏆 Most Cited Paper
Towards Automated Planning for Enterprise Services: Opportunities and Challenges
3 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: IBM Research - Thomas J. Watson Research Center

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago