Papers

7

Total Citations

296

H-Index

5

About

Ahmed Elsherbiny’s research bridges two seemingly distinct worlds—robotics and urological surgery—united by a common goal: enhancing precision and outcomes through advanced technology. His work in soft computing tackles one of robotics’ most stubborn challenges: the inverse kinematics problem, which involves calculating the joint angles needed to position a robot arm accurately. In his highly cited 2017 comparative study (112 citations), he evaluated methods like artificial bee colony algorithms to solve this problem for industrial robot arms, and later refined these approaches for a 5-DOF arm (49 citations). On the surgical side, Elsherbiny has pioneered the use of real-time imaging technologies to improve cancer care. He led the first application of ex vivo fluorescence confocal microscopy for rapid pathological examination of prostate tissue (85 citations), a breakthrough that could transform intraoperative decision-making. He has also investigated techniques to reduce urinary incontinence after robot-assisted prostatectomy and explored new imaging tools for robotic kidney cancer surgery. His work demonstrates a rare ability to translate computational methods into clinical innovations that directly impact patient recovery and surgical precision.

Research Focus

Key Achievements

5
H-Index
7
Papers
296
Total Citations
42
Avg Citations/Paper
🏆 Most Cited Paper
A comparative study of soft computing methods to solve inverse kinematics problem
112 citations · 2017
📈 Most Prolific Year: 2019 (2 Papers)
🤝 Key Collaborators: 60
🏛 Institutions: Mansoura University, University of Modena and Reggio Emilia, Tanta University, German University in Cairo

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago