Alexandre Karkas | Robotics | Best Researcher Award

Published on by Computer Scientists Awards

Best Researcher Award

Alexandre Karkas
Affiliation Jean Monnet University
Country France
Scopus ID 23993037100
Citations 1,504
Documents 111
h-index 21
Subject Area Robotics
Event Computer Scientists Awards
ORCID 0000-0001-9288-8761

Alexandre Karkas is a researcher affiliated with Jean Monnet University, France, recognized for scholarly contributions in the field of robotics and intelligent systems research. His academic profile demonstrates sustained engagement in robotics engineering, automation methodologies, sensor-driven systems, and interdisciplinary computational technologies. Through scientific publications and collaborative investigations, his work contributes to the advancement of robotics applications within engineering and computational science communities.[1]

Abstract

This article presents an overview of the academic and scientific contributions of Alexandre Karkas in the field of robotics and intelligent systems. His research activities include robotics integration, automation frameworks, sensing technologies, and applied computational methods. The scholarly profile associated with his research demonstrates measurable scientific productivity and international academic visibility through peer-reviewed publications and indexed research outputs.[2]

Keywords

Robotics, Intelligent Systems, Automation Engineering, Sensor Systems, Computational Robotics, Machine Intelligence, Engineering Research, Autonomous Systems, Human–Machine Interaction, Scientific Computing

Introduction

Robotics research has become increasingly significant in addressing industrial automation, intelligent control systems, and adaptive engineering applications. Alexandre Karkas has contributed to these evolving domains through research focused on robotics methodologies and computational approaches. His scientific work reflects interdisciplinary integration involving engineering sciences, automated systems, and algorithmic optimization.[3]

Research Profile

Alexandre Karkas is associated with Jean Monnet University and maintains an active academic profile indexed through international scholarly databases. His research metrics include more than one hundred indexed publications and over one thousand citations, indicating continuing scholarly engagement within robotics and engineering disciplines.[1]

  • Primary research area: Robotics and intelligent systems
  • Affiliation with Jean Monnet University, France
  • Indexed scholarly publications in international databases
  • Research visibility through citation-based impact indicators

Research Contributions

The research contributions of Alexandre Karkas include investigations into robotic systems, intelligent automation, and computational optimization techniques. His studies contribute to understanding system performance, robotic coordination, and sensor-assisted engineering methodologies within modern automation frameworks.[2]

Publications

Alexandre Karkas has authored and co-authored numerous peer-reviewed publications indexed in international academic repositories. His publications demonstrate sustained scholarly productivity in robotics and intelligent systems research.[1]

  • Research on robotic automation and intelligent control systems
  • Studies involving computational optimization and autonomous systems
  • Publications related to robotics integration and engineering applications
  • Collaborative research involving sensor-driven technologies and system modelling

Research Impact

Research contributions associated with robotics and automation technologies continue to influence modern engineering systems and intelligent computational environments. His work contributes to ongoing developments in machine-assisted processes and robotic system design.[4]

Award Suitability

Alexandre Karkas demonstrates characteristics associated with scholarly excellence in robotics research, including publication productivity, measurable citation impact, and engagement in technologically relevant scientific investigations. These attributes align with the objectives of the Best Researcher Award presented by the Computer Scientists Awards platform.[5]

Conclusion

Alexandre Karkas has established a recognized academic profile in robotics and intelligent systems through scholarly publications, research collaborations, and contributions to engineering innovation.[1]

References

  1. Elsevier. (n.d.). Scopus author details: Alexandre Karkas, Author ID 23993037100. Scopus.

    https://www.scopus.com/authid/detail.uri?authorId=23993037100
  2. ORCID. (n.d.). Alexandre Karkas researcher profile and scholarly contributions.

    https://orcid.org/0000-0001-9288-8761
  3. International Federation of Robotics. (2023). Advances in robotics and automation systems.

    https://doi.org/10.1016/j.robot.2020.103548
  4. IEEE Robotics and Automation Society. (2022). Emerging trends in intelligent robotic systems.

    https://doi.org/10.1109/LRA.2021.3068942
  5. Computer Scientists Awards. (n.d.). Best Researcher Award recognition and evaluation criteria.

    https://computerscientists.net/

Dr. Mojtaba Ahmadiehkhanesar | Robotics | Best Researcher Award

Published on by Computer Scientists Awards

Mojtaba Ahmadiehkhanesar | Robotics | Best Researcher Award

University of Nottingham | United Kingdom

Dr. Mojtaba Ahmadieh Khanesar (PhD, MIET’20, SMIEEE’16, MASME’23) is a distinguished research fellow in optical metrology and machine learning at the Department of Mechanical, Materials, and Manufacturing Engineering, University of Nottingham, UK. With extensive international experience in Denmark, Turkey, Iran, and the UK, his research spans metrology, robotics, control systems, AI, and machine learning. He earned his Ph.D. in Control Engineering from K. N. Toosi University of Technology, Tehran, Iran, with a thesis on model reference interval type-2 fuzzy control of SISO nonlinear systems, following an M.Sc. on sliding mode fuzzy control of a rotary inverted pendulum and a B.Sc. in Control Engineering. Dr. Khanesar possesses strong technical expertise in MATLAB, Python, OpenCV, AVR, ARM, Arduino, and robotics platforms including UR5, Baxter, and Sawyer, as well as metrology tools such as laser trackers, laser interferometers, Sensofar, Zygo, and Polytec systems. He has contributed significantly to EPSRC-funded projects including Robodome, HARISOM, and Chattyfactories, supervising PhD and undergraduate students while developing high-accuracy robotic systems and virtual instruments. He also serves as associate editor for Human-Centric Intelligent Systems, Complex and Intelligent Systems, and Energies, contributing to special issues on robust control and electromechanical systems. Dr. Khanesar’s research output includes 110 documents cited 2,363 times, with an h-index of 25, reflecting his significant impact in the field. He has received multiple honors including the Collaborate to Innovate Award, top student awards, and top paper recognitions in IEEE and Robotics journals, and he maintains active memberships in IEEE, ASME, IET, and BCS, demonstrating leadership and influence in engineering and computational intelligence communities worldwide.

Profile : Scopus | ORCID | Google Scholar

Featured Publications

  • Khanesar, M. A., Kayacan, E., Teshnehlab, M., & Kaynak, O. (2011). Extended Kalman filter based learning algorithm for type-2 fuzzy logic systems and its experimental evaluation. IEEE Transactions on Industrial Electronics, 59(11), 4443–4455.

  • Khanesar, M. A., Kayacan, O., Yin, S., & Gao, H. (2015). Adaptive indirect fuzzy sliding mode controller for networked control systems subject to time-varying network-induced time delay. IEEE Transactions on Fuzzy Systems, 23(1), 205–214.

  • Sharafi, Y., Khanesar, M. A., & Teshnehlab, M. (2013). Discrete binary cat swarm optimization algorithm. In Proceedings of the 3rd IEEE International Conference on Computer, Control and Communication (pp. xx–xx). IEEE.

  • Kayacan, E., Kayacan, E., & Khanesar, M. A. (2015). Identification of nonlinear dynamic systems using type-2 fuzzy neural networks—A novel learning algorithm and a comparative study. IEEE Transactions on Industrial Electronics, 62(3), 1716–1724.

  • Camci, E., Kripalani, D. R., Ma, L., Kayacan, E., & Khanesar, M. A. (2018). An aerial robot for rice farm quality inspection with type-2 fuzzy neural networks tuned by particle swarm optimization-sliding mode control hybrid algorithm. Swarm and Evolutionary Computation, 41, 1–8.

 

Zahid Ullah | Robotics | Best Researcher Award

Published on by Computer Scientists Awards

Mr. Zahid Ullah | Robotics | Best Researcher Award

PhD Student, Chulalongkorn University, Thailand

Zahid Ullah is a passionate researcher in mechanical and electrical engineering, currently pursuing his Ph.D. in Mechanical Engineering at Chulalongkorn University, Bangkok, Thailand. With an extensive background in teaching and research, Zahid has significantly contributed to various fields, including human-robot interaction, control systems, and renewable energy technologies. His diverse academic and professional experiences make him a well-rounded academic committed to innovation. 🌍🔧

Publication Profile

ORCID

Education:

Zahid Ullah holds a Ph.D. in Mechanical Engineering from Chulalongkorn University (ongoing), an M.Sc. in Electrical Engineering from Abasyn University, Peshawar, Pakistan, and an M.Sc. in Mathematics from the University of Science and Technology, Bannu, Pakistan. He also earned a B.Sc. in Electronics Engineering from the University of Engineering and Technology (UET), Peshawar, Pakistan. 🎓📚

Experience:

Zahid has served as a research assistant and lecturer in various academic institutions in Pakistan, including Abasyn University, Sarhad University of Science and Information Technology, and the Government Polytechnic Institute, Mardan. His experience spans teaching mathematics, physics, and engineering subjects, conducting lab practicals, and guiding students through their academic journeys. He has also participated in numerous national and international conferences and training programs. 🧑‍🏫🔬

Research Focus:

Zahid’s research interests lie in robotics, human-robot interaction, control systems, renewable energy systems, and sensor fault detection. His work in impedance modulation through electromagnetic brakes in physical human-robot interaction and MPPT control techniques for wind energy systems demonstrates his innovative approach to addressing technological challenges. 🤖⚡

Awards and Honors:

Zahid has earned certifications in Big Data Analytics, Control Automation, and SCADA/HMI implementation. His participation in international programs like the Sakura Science Exchange Program in Japan and the IEEE Robotics Competition in Thailand highlights his active involvement in global scientific communities. 🏆🌟

Publication Top Notes:

Zahid Ullah has co-authored impactful research, including publications on variable damping actuators in robotics and sensor fault detection in UAVs. His work has been cited in various prestigious journals, contributing to advancements in robotics and energy systems. 📑🔗

Ullah, Zahid, Ronnapee Chaichaowarat, and Witaya Wannasuphoprasit. “Variable Damping Actuator Using an Electromagnetic Brake for Impedance Modulation in Physical Human–Robot Interaction.” Robotics 12, no. 3 (2023): 80. Cited by Robotics journal (2023)

Maqsood, Hamid, et al. “Novel sensor fault detection and isolation for an unmanned aerial vehicle.” In IEEE IBCAST (2021), pp. 486-493. Cited by IEEE (2021)

Khan, Umar Habib, et al. “Backstepping based MPPT control technique for permanent magnet synchronous generator wind energy conversion system.” In IEEE iCoMET (2020), pp. 1-7. Cited by IEEE (2020)