Papers

16

Total Citations

144

H-Index

7

About

Thanh-Phong Dao is a prolific researcher specializing in compliant mechanisms, precision robotics, and computational optimization — fields that sit at the intersection of mechanical engineering, biomedical applications, and intelligent systems. His work has made significant contributions to the design and optimization of flexure-based mechanisms, compliant grippers, and assistive devices for physically disabled individuals, consistently advancing methodologies that overcome traditional limitations such as friction, backlash, and complex assembly. Dao is particularly recognized for pioneering hybrid computational approaches that combine finite element methods (FEM), metaheuristic algorithms, fuzzy logic, and machine learning techniques — including ANFIS, neural networks, and multi-objective genetic algorithms — to achieve robust, multi-response optimal designs. His development of compliant planar springs and flexure elbow joints for upper-limb assistive devices reflects a strong commitment to socially impactful engineering. His comprehensive review papers on compliant grippers for micromanipulation have become valuable reference works within the robotics community, accumulating notable citations since 2024. With his most-cited work garnering 28 citations and a growing body of research across robotics, biomedical engineering, and micro-manipulation systems, Dao continues to shape modern approaches to intelligent mechanical design synthesis and precision automation.

Research Focus

Key Achievements

7
H-Index
16
Papers
144
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
A multi-response optimal design of bistable compliant mechanism using efficient approach of desirability, fuzzy logic, ANFIS and LAPO algorithm
28 citations · 2020
📈 Most Prolific Year: 2022 (5 Papers)
🤝 Key Collaborators: 15
🏛 Institutions: Ton Duc Thang University, Ho Chi Minh City University of Technology and Engineering

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 17 days ago