Mr. Ahmed Hamet Sidi | Robotics Systems | Research Excellence Award

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Mr. Ahmed Hamet Sidi | Robotics Systems | Research Excellence Award

Teacher | University of Djillali Liabes | Niger

Mr. Ahmed Hamet Sidi is an emerging researcher in electromechanics, robotics, and advanced control systems, with a strong focus on dynamic system control, visual servoing, and intelligent automation. His work explores trajectory tracking, optimization techniques, and modern control approaches such as PID, model predictive control, and reinforcement learning for complex electromechanical systems. He has contributed to research on 2-DOF ball-on-plate balancing systems, highlighting precision control and system stability. His publications are indexed in Scopus, with 2 documents and a developing citation profile, alongside growing visibility on Google Scholar with an early-stage h-index. His research demonstrates promising potential in robotics innovation and smart control applications.

Citation Metrics (Scopus)

9

6

3

0

 

Citations
1

Documents
2

h-index
1

             🟦 Citations 🟥 Documents 🟩 h-index


View Scopus Profile

Featured Publications

Enhanced Ball Trajectory Tracking Using Visual Servoing with 2-DOF Ball on Plate Balancing System
– Journal Européen des Systèmes Automatisés, 2024

Dr. Mojtaba Ahmadiehkhanesar | Robotics | Best Researcher Award

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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.

 

Dr. zhendong zhao | robotics | Best Scholar Award

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Dr. zhendong zhao | robotics | Best Scholar Award

Ph.D. graduate student, Hebei University of Technology, China

Zhendong Zhao is a passionate Ph.D. graduate student at the School of Artificial Intelligence and Data Science, Hebei University of Technology, China . With a strong foundation in control science and engineering, Zhendong is deeply involved in cutting-edge research in embodied intelligence and robotics powered by large language models (LLMs). His dedication to integrating AI with robotics has already led to the development of novel frameworks that enhance collaborative and autonomous robotic systems 🤖.

Publication Profile

ORCID

🎓 Education Background:

Zhendong Zhao is currently pursuing his Ph.D. in Control Science and Engineering at Hebei University of Technology. His academic path has been rooted in artificial intelligence, with a strong emphasis on integrating LLMs into real-world robotic applications. He has been trained in advanced AI theories, machine learning, and robotic systems that lay the groundwork for his research endeavors 📚.

💼 Professional Experience:

As a doctoral researcher at Hebei University of Technology, Zhendong Zhao has contributed to developing innovative robotic frameworks. His research focuses on leveraging large language models to enhance robot collaboration, especially in healthcare contexts like nursing robots. Despite his early career stage, Zhendong has demonstrated remarkable potential through independent research and publications in top-tier journals 🧪.

🏅 Awards and Honors:

While no formal awards have been mentioned yet, Zhendong Zhao’s impactful research and publication record already highlight his contributions to AI and robotics. His work has earned attention through prestigious platforms such as IEEE Robotics and Automation Letters and Bioengineering, positioning him as a rising researcher in the field 🏆.

🔬 Research Focus:

Zhendong’s research centers around embodied intelligence and LLM-based dual-arm robotics. He introduced a dual-agent framework named DABICO for task planning in nursing robots. This system builds a dual-agent (left-arm and right-arm) structure that emphasizes inter-agent communication and validation mechanisms. His research pushes the frontier of how LLMs can coordinate physical tasks across robotic limbs in real-time, especially for bimanual coordination tasks in caregiving robots 🦾.

✅ Conclusion:

Zhendong Zhao stands out as a forward-thinking Ph.D. researcher who merges AI theory with practical robotic implementations. With multiple publications in high-impact journals and a focused vision for advancing embodied intelligence, Zhendong is poised to become a significant contributor to the future of intelligent robotics.

📝 Top Publications :

The Multi-Agentization of a Dual-Arm Nursing Robot Based on Large Language Models
📅 Published: 2025
📚 Journal: Bioengineering
🔗 DOI: 10.3390/bioengineering12050448
🔁 Cited by: Crossref-indexed (specific citation count pending)

A Dual-Agent Collaboration Framework Based on LLMs for Nursing Robots to Perform Bimanual Coordination Tasks
📅 Published: 2025
📚 Journal: IEEE Robotics and Automation Letters
🔗 DOI: 10.1109/LRA.2025.3533476
🔁 Cited by: Crossref-indexed (specific citation count pending)

Behnaz Sohani | Robotics | Best Researcher Award

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Dr. Behnaz Sohani | Robotics | Best Researcher Award

Assistant professor, Loughborough University, United Kingdom

Dr. Behnaz Sohani is an accomplished academic and researcher in Robotics and Biomedical Engineering, specializing in object and scene recognition, assistive robotics, rehabilitation systems, and healthcare robotics. She currently serves as a Co-Director of the Biorobotics and Healthcare/Medical Technologies (BMTec) Laboratory and as a Lecturer in Robotics at the University of Lincoln. With over 16 years of experience in education, research, and administration, Dr. Sohani is passionate about advancing technology and improving healthcare through innovative robotics solutions. 🚀🤖📚

Profile

  • Scopus
  • ORCID
  • Google Scholar

    Strengths for the Award

    1. Community-Oriented Research: Dr. Behnaz Sohani’s work in robotics and biomedical engineering has a clear impact on community health and well-being. Her research focuses on developing assistive and healthcare robotics, which directly benefits individuals with medical conditions and those needing rehabilitation. The development of medical imaging devices and intelligent robots aligns well with the award’s focus on community impact.
    2. Innovative Contributions: Dr. Sohani has been involved in groundbreaking projects, such as designing imaging devices for early detection of brain strokes and cancers. Her use of AI and advanced technologies in healthcare demonstrates innovation that addresses significant community health challenges.
    3. Leadership and Collaboration: As the Co-Director of the Biorobotics and Healthcare/Medical Technologies Laboratory, she has shown strong leadership in driving impactful research projects. Her ability to collaborate with both academic and industrial partners, including medical professionals, enhances the relevance and application of her research.
    4. Educational Impact: Dr. Sohani’s role as a lecturer and mentor at the University of Lincoln contributes to shaping the next generation of engineers and researchers. Her teaching covers a broad spectrum of robotics and biomedical engineering topics, ensuring that her knowledge and passion are shared with students who can continue to drive community-oriented innovations.
    5. Grants and Recognition: Securing significant grants, such as those from the Royal Society and European Regional Development Fund, underscores her ability to attract funding for projects with high community impact. Her successful grant applications reflect recognition and validation from the research community and funding bodies.

    Areas for Improvement

    1. Broader Community Engagement: While Dr. Sohani’s work is impactful within academic and healthcare circles, increasing outreach to broader community stakeholders could enhance the visibility and accessibility of her innovations. Engaging more directly with community organizations or public health initiatives could amplify her research’s community impact.
    2. Communication of Impact: Dr. Sohani’s CV highlights numerous achievements and research outputs but could benefit from more explicit examples of how her work has directly improved or benefited community members. Providing case studies or testimonials could better illustrate the tangible benefits of her research.
    3. Public Awareness: Increasing public awareness about the practical applications of her research could further strengthen the case for the award. This could involve more public engagement activities, such as workshops, seminars, or media outreach, to showcase how her technologies are being used in real-world scenarios.

       

      Education

      Dr. Sohani earned her PhD in Robotics and Biomedical Engineering from London South Bank University (2017-2021). Her doctoral research focused on medical imaging for diagnostic applications, particularly in detecting brain abnormalities using microwave imaging. 🧠🎓

      Experience

      Dr. Sohani has held various academic and research positions. Since January 2021, she has been a Lecturer in Robotics and Biomedical Engineering and the Lead and Director of the BMTec Laboratory at the University of Lincoln. Her roles include generating research income, publishing research outputs, and delivering high-quality teaching programs. Previously, she served as a Postdoctoral Research Fellow at London South Bank University, where she designed medical devices augmented by AI. 📊🧪👩‍🏫

      Research Interests

      Dr. Sohani’s research interests encompass robotics and biomedical engineering, with a focus on assistive robotics, healthcare robotics, path planning, real-time control, computer vision, signal processing, and AI technologies. She is dedicated to advancing the early detection and management of medical conditions and addressing critical healthcare challenges through innovative robotic solutions. 🤖🩺🔍

      Awards

      Dr. Sohani has received several prestigious awards and grants, including successful grant applications to the Royal Society (£70K), being the principal investigator on three research projects funded by the European Regional Development Fund (ERDF), and her PhD funding from the European Union’s Horizon research & innovation program under the Marie Sklodowska-Curie Grant Agreement. 🏆🎓💼

       Publications

      1. “Revolutionizing Demand Response Management: Empowering Consumers through Power Aggregator and Right of Flexibility.” Energies 17.6: 1419, (2024). Cited by 3 articles
      2. Aliyu, M. et al. “An artificial neural network model for the prediction of entrained droplet fraction in annular gas-liquid two-phase flow in vertical pipes.” International Journal of Multiphase Flow 164 (2023): 104452. Cited by 2 articles
      3. Nnadi, S. et al. “Development, Experimental, and Numerical Characterisation of Novel Flexible Strain Sensors for Soft Robotics Applications”, Robotics, 13(7), 103, (2024). Cited by 5 articles
      4. Webber, M., et al. “A techno-economic review of direct air capture of moisture processes: sustainable versus energy-intensive methods.” International Journal of Environmental Science and Technology: 1-35, (2024). Cited by 7 article
      5. Sohani, B. et al. “Developing a Comprehensive Model for the Prevention of Tension Neck Syndrome: A Focus on Musculoskeletal Disorder Prevention Strategies.” Advanced Robotics and Automation (WRC SARA), Beijing, China, pp. 541-548. IEEE, (2023). Cited by 4 articles