Daniel Waren

NYU Langone Health

Papers

3

Total Citations

5

H-Index

2

About

Daniel Waren is a rising orthopedic researcher focused on advancing total joint arthroplasty through robotic-assisted and navigation-assisted surgical techniques. His work centers on improving precision and recovery outcomes in hip and knee replacement surgeries. Waren’s key contributions include demonstrating that robotic-assisted total hip arthroplasty (RA-THA) can significantly shorten the time to achieve a minimal clinically important difference compared to conventional methods, with his 2025 study on this topic already garnering 2 citations. In total knee arthroplasty, he revealed that robotic arm–assisted procedures produce smaller femoral components and larger tibial baseplates than manual techniques, a 2024 finding that has also earned 2 citations. Most recently, Waren has pioneered the use of artificial intelligence to predict coronal alignment in robotic-assisted total knee arthroplasty, a 2025 study that marks an early but promising step toward personalized surgical planning. Though early in his career, Waren’s integration of robotics, navigation, and AI positions him at the forefront of data-driven orthopedic innovation, with his work already shaping how surgeons optimize implant sizing and accelerate patient recovery.

Research Focus

Key Achievements

2
H-Index
3
Papers
5
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Time to Achieve a Minimal Clinically Important Difference After Total Hip Arthroplasty: A Retrospective Cohort Comparison of Robotic-Assisted, Navigation-Assisted, and Conventional Techniques
2 citations · 2025
📈 Most Prolific Year: 2025 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: NYU Langone Health

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago