Samir Mekid

About

Samir Mekid is a multidisciplinary engineer and researcher whose work spans robotics, nanotechnology, smart materials, and advanced manufacturing. Best known for his contributions to tactile sensing and bio-inspired design, his highly cited 2022 review of whisker tactile sensors (36 citations) illuminated the transformative potential of biologically inspired sensing for applications ranging from surgical robotics to underwater navigation. His pioneering concept of "nervous materials" — sensor array structures capable of human-like sensing — reflects a broader ambition to delay structural failure and enhance public safety through intelligent material design. Mekid has made significant contributions to nanomanipulation, developing integrated nanomanipulator systems that bridge sub-nanoscale phenomena with mesoscale device fabrication, helping enable next-generation nano-devices and lithography inspection techniques. His work on robotic systems encompasses workspace analysis of planar manipulators, reconfigurable robot architectures with dependent joint concepts, and fault-tolerant control strategies increasingly informed by artificial intelligence and deep learning — demonstrating a forward-looking engagement with AI-enabled manufacturing. More recently, he has extended his scholarly lens to socio-ethical dimensions of emerging technologies such as drones. Across his career, Mekid's research consistently integrates mechanical precision with intelligent systems thinking, making him a notable voice at the intersection of robotics, sensing, and responsible technological innovation.

Research Focus

Key Achievements

Top Papers

1. 1
   Review of Recent Bio-Inspired Design and Manufacturing of Whisker Tactile Sensors

   36 citations · 2022
2. 2
   Towards sensor array materials: can failure be delayed?

   14 citations · 2015
3. 3
   Engineering manipulation at nanoscale: further functional specifications

   11 citations · 2019
4. 4
   A NEW ANALYSIS OF WORKSPACE PERFORMANCES AND ORIENTATION CAPABILITY FOR 3-DOF PLANAR MANIPULATORS

   9 citations · 2010
5. 5
   Fault-tolerant control strategies for industrial robots: state of the art and future perspective on AI-based fault management

   7 citations · 2025
6. 6
   AI Enabled Manufacturing: A Deep Learning Approach to Network Fault Detection

   7 citations · 2025
7. 7
   Integrated Nanomanipulator With In-Process Lithography Inspection

   5 citations · 2020
8. 8
   Concept of dependent joints in functional reconfigurable robots

   4 citations · 2015
9. 9
   Characteristic Analysis of Bioinspired Pod Structure Robotic Configurations

   4 citations · 2013
10. 10
    Intricate and Multifaceted Socio-Ethical Dilemmas Facing the Development of Drone Technology: A Qualitative Exploration

    3 citations · 2025

Key Collaborators

Contact & Links