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

Dimitris Ziouzios | Robotics | Best Researcher Award

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Dr. Dimitris Ziouzios | Robotics | Best Researcher Award

Dr. Dimitris Ziouzios | Researcher | University of Western Macedonia | Greece

Dr. Dimitris Ziouzios is a dedicated researcher at the University of Western Macedonia, whose work spans robotics, embedded systems, and FPGA-based applications. His research emphasizes the integration of intelligent systems with real-world challenges such as environmental sustainability, smart waste management, and educational robotics. With over 23 completed and ongoing research projects, Dr. Ziouzios has made impactful contributions through innovations that merge automation, machine learning, and IoT technologies. His work has led to one patent, numerous collaborations with research institutions and industry partners including CERTH, the University of Wuppertal, and local municipalities, and over 14 publications indexed in SCI and Scopus journals. His research influence is reflected in a Google Scholar record of 514 citations with an h-index of 12, and a Scopus record of 345 citations with an h-index of 10. Beyond his technical research, Dr. Ziouzios contributes to advancing smart city infrastructures and robotics education, promoting environmental awareness and empathy through technology-driven learning. His consistent scholarly output and multidisciplinary collaborations highlight his strong commitment to innovation and applied research excellence.

Publication Profile

Google Scholar

Featured Publications

Ziouzios, D., Tsiktsiris, D., Baras, N., & Dasygenis, M. (2020). A distributed architecture for smart recycling using machine learning. Future Internet, 12(9), 141.

Ziouzios, D., Karlopoulos, E., Fragkos, P., & Vrontisi, Z. (2021). Challenges and opportunities of coal phase-out in western Macedonia. Climate, 9(7), 115.

Ziouzios, D., Baras, N., Balafas, V., Dasygenis, M., & Stimoniaris, A. (2022). Intelligent and real-time detection and classification algorithm for recycled materials using convolutional neural networks. Recycling, 7(1), 9.

Ziouzios, D., Rammos, D., Bratitsis, T., & Dasygenis, M. (2021). Utilizing educational robotics for environmental empathy cultivation in primary schools. Electronics, 10(19), 2389.

Ziouzios, D., Dasygenis, M. (2023). Effectiveness of the IoT in regional energy transition: The smart bin case study. Recycling, 8(1), 28.

 

Prof. Saad Aljlil | Engineering | Best Researcher Award

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Prof. Saad Aljlil | Engineering | Best Researcher Award

Prof. Saad Aljlil | Chief Researcher | King Abdulaziz City for Science and Technology | Saudi Arabia

Prof. Saad A. Aljlil is a distinguished research professor at the King Abdulaziz City for Science and Technology (KACST), Saudi Arabia, specializing in sustainability, membrane technology, and water and environmental engineering. His research focuses on advanced desalination and water treatment technologies, wastewater purification, membrane synthesis, adsorption processes, and the integration of renewable energy systems for sustainable water management. Prof. Aljlil has made significant contributions to developing ceramic and polymeric membranes, nanocomposite materials, and hybrid desalination systems that enhance water purification efficiency while minimizing environmental impact. His work extends to smart water networks, solar-driven desalination, greywater reuse, and innovative applications of artificial intelligence in membrane distillation and water resource optimization. A highly cited researcher, Prof. Aljlil has achieved 1,079 citations in Scopus across 44 documents with an h-index of 19, and 1,397 citations on Google Scholar with an h-index of 20 and i10-index of 23. His interdisciplinary approach bridges chemical engineering, nanotechnology, and sustainability to address critical challenges in clean water access and environmental preservation.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

Ali, A., Macedonio, F., Drioli, E., Aljlil, S. A., & Alharbi, O. A. (2013). Experimental and theoretical evaluation of temperature polarization phenomenon in direct contact membrane distillation. Chemical Engineering Research and Design, 91(10), 1966–1977.

Quist-Jensen, C. A., Macedonio, F., Conidi, C., Cassano, A., Aljlil, S. A., Alharbi, O. A., & Drioli, E. (2016). Direct contact membrane distillation for the concentration of clarified orange juice. Journal of Food Engineering, 187, 37–43.

Fontananova, E., Bahattab, M. A., Aljlil, S. A., Alowairdy, M., Rinaldi, G., Vuono, D., & Drioli, E. (2015). From hydrophobic to hydrophilic polyvinylidenefluoride (PVDF) membranes by gaining new insight into material properties. RSC Advances, 5(69), 56219–56231.

Park, C. H., Tocci, E., Fontananova, E., Bahattab, M. A., Aljlil, S. A., & Drioli, E. (2016). Mixed matrix membranes containing functionalized multiwalled carbon nanotubes: Mesoscale simulation and experimental approach for optimizing dispersion. Journal of Membrane Science, 514, 195–209.

Sedighi, M., Aljlil, S. A., Alsubei, M. D., Ghasemi, M., & Mohammadi, M. (2018). Performance optimisation of microbial fuel cell for wastewater treatment and sustainable clean energy generation using response surface methodology. Alexandria Engineering Journal, 57(4), 4243–4253.

 

Liang Li | Robot System | Best Researcher Award

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Dr. Liang Li | Robot System | Best Researcher Award

Academic Leader of the Key Laboratory | Baoji University of Arts and Sciences | China

Dr. Li Liang is an academic scholar affiliated with the Baoji University of Arts and Sciences in Baoji, China. He has contributed to the fields of mechanical engineering, composite materials, robotics, and intelligent manufacturing through a consistent body of research. His publications demonstrate expertise in process modeling, knowledge graph construction, and optimization techniques for robotic systems. With an active research profile indexed in Scopus, Li Liang has achieved recognition with multiple works cited internationally. His academic career reflects a dedication to advancing modern manufacturing technologies and their integration with artificial intelligence methods in industrial applications.

Publication Profile

Scopus

Education Background

Dr. Li Liang pursued his higher education in engineering disciplines, developing a strong foundation in mechanical sciences and computational techniques. His academic training emphasized advanced mechanics, material science, and intelligent control systems, which enabled him to engage with cross-disciplinary research in automation and industrial technologies. Through rigorous study and research training, he cultivated proficiency in analytical methods and modern computational tools. His education was centered on building both theoretical and practical expertise, allowing him to contribute effectively to innovative solutions in machining processes, robotic trajectory optimization, and composite structural analysis across applied engineering fields.

Professional Experience

As an Associate faculty member at Baoji University of Arts and Sciences, Dr. Li Liang has actively participated in teaching, research, and collaborative projects. His professional experience spans guiding students, publishing scholarly works, and engaging in joint research efforts with national and international colleagues. He has authored and co-authored numerous papers, focusing on numerical modeling, intelligent robotics, and advanced materials. His contributions also extend to integrating artificial intelligence approaches with traditional engineering processes. In addition, he has built professional collaborations with more than thirty co-authors, reflecting his ability to work in team-driven scientific environments that promote applied industrial innovations.

Awards and Honors

While specific awards and grants are not publicly listed, Dr. Li Liang has earned academic recognition through consistent citations of his research and scholarly contributions. His studies published in reputable open-access journals such as Electronics and Processes have contributed to the international research community, further solidifying his academic standing. The impact of his work, reflected in increasing citations and collaborations, signifies recognition of his scholarly achievements. His commitment to advancing research on machining knowledge graphs, composite mechanics, and robotic arm optimization highlights his academic merit and serves as a foundation for future honors and acknowledgments.

Research Focus

Dr. Li Liang’s primary research interests lie in mechanical engineering, intelligent manufacturing, composite materials, and robotics. His recent works have explored the construction of machining process knowledge graphs for route recommendations, numerical analysis of advanced braided composites, and reinforcement learning optimization for robotic grasping. These areas collectively showcase his interdisciplinary focus, combining computational intelligence with mechanical design. By addressing challenges in trajectory planning, process optimization, and structural performance, his research contributes to advancing both theoretical insights and industrial applications. His focus is on creating smart, adaptive systems that bridge materials science, artificial intelligence, and industrial engineering.

Publication Top Notes

  • Construction of a Machining Process Knowledge Graph and Its Application in Process Route Recommendation
    Published Year: 2025
    Citation: 1

  • Numerical Analysis on Mechanical Properties of 3D Five-Directional Circular Braided Composites
    Published Year: 2025
    Citation: 1

  • Improved PPO Optimization for Robotic Arm Grasping Trajectory Planning and Real-Robot Migration
    Published Year: Not listed
    Citation: 1

Conclusion

Through his academic journey, Dr. Li Liang has built a strong reputation as a researcher contributing to intelligent manufacturing and computational engineering. His publications demonstrate expertise across multiple technical domains, and his collaborative work highlights his adaptability and scholarly engagement. With a growing number of citations and impactful studies, his career reflects both innovation and academic integrity. His dedication to teaching and research at Baoji University of Arts and Sciences ensures that his contributions will continue to influence the development of advanced robotic systems, material analysis, and smart manufacturing processes in both academic and applied industrial contexts.

Xiaodong Feng | Robotics | Best Researcher Award

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Prof. Xiaodong Feng | Robotics | Best Researcher Award

Prof. Xiaodong Feng at Shaoxing University, China

Feng Xiaodong, born in June 1987, is an Associate Professor at the School of Civil Engineering, Shaoxing University of Arts and Sciences. Recognized as one of the first leading talents in Zhejiang Province’s 5246 Talent Project and a young talent under Shaoxing’s Special Branch Plan, he specializes in structural engineering. With an international academic footprint and a strong background in intelligent structural systems, Dr. Feng has led numerous national-level projects and published extensively in high-impact journals. His work integrates innovative structural design with smart technologies, contributing significantly to the advancement of flexible and adaptive engineering solutions. 🌉📚🤖

Publication Profile

Scopus

Academic Background

Feng Xiaodong completed his undergraduate studies in Civil Engineering at Central South University (2006–2010), followed by a master’s in Solid Mechanics (2010–2012) and a Ph.D. in Structural Engineering (2012–2016), under Professor Guo Shaohua. He then pursued postdoctoral research at Zhejiang University (2018–2020) with Professor Luo Yaozhi. His academic training spans mechanics, structural analysis, and intelligent systems, providing a robust foundation for his interdisciplinary research. 📘🎓🔬

Professional Experience

Dr. Feng began his academic career at Shaoxing University of Arts and Sciences in 2016 as a Lecturer, advancing to Associate Professor and Laboratory Director in 2021. He also served as a visiting scholar at Kyoto University, Japan (2022–2023). Throughout his career, he has led key research initiatives, mentored students, and collaborated with both academic and industrial partners on advanced structural systems. His experience bridges practical engineering applications and cutting-edge research. 🏢👨‍🏫🌍

Awards and Honors

Feng Xiaodong has received multiple prestigious awards, including two First Prizes and two Second Prizes from the China Steel Structure Association for technological innovation and scientific progress in large-span structures. He also received honors from the Invention and Entrepreneurship Award and Zhejiang Province. These accolades recognize his contributions to the development, design, and digital construction of complex spatial structures, as well as intelligent construction technologies. His pioneering work in structural mechanics and smart infrastructure has earned both national and regional acclaim. 🏆🏗️

Research Focus

Dr. Feng’s research revolves around flexible, movable, and intelligent structures, integrating AI and machine learning for structural design and health monitoring. His key interests include tensegrity structures, prefabricated systems, large-span spatial structures, and structural dynamics. He also focuses on collaborative structural-material design and building industrialization. His interdisciplinary approach combines theoretical innovation with practical applications, aimed at advancing the construction industry’s automation and intelligence. 🤖🧠🏗️📊

Publication Top Notes

📄 Vibration control and robustness analysis of tensegrity structures via fuzzy dynamic sliding mode control method
🗓️ Year: 2024 | 📚 Journal: Structures | 📊 Cited by: 3

📄 Joint learning of structural and textual information on propagation network by graph attention networks for rumor detection
🗓️ Year: 2024 | 📚 Journal: Applied Intelligence | 📊 Cited by: 1

📄 Structural-topic aware deep neural networks for information cascade prediction
🗓️ Year: 2024 | 📚 Journal: PeerJ Computer Science | 📊 Cited by: 1

Conclusion

Dr. Feng Xiaodong, an Associate Professor at Shaoxing University of Arts and Sciences, is a nationally recognized expert in Structural Engineering, specializing in intelligent structures, AI-integrated design, and prefabricated construction technologies. With over 20 peer-reviewed publications in leading journals such as Soft Robotics, Structures, and Structural Control & Health Monitoring, he demonstrates consistent research excellence. As the principal investigator of numerous national and regional research projects, and a recipient of multiple high-level awards from the China Steel Structure Association and Zhejiang Province, Dr. Feng has shown both academic leadership and practical innovation. His international exposure as a Visiting Scholar at Kyoto University and his role in training future engineers across disciplines further underscore his qualifications. Dr. Feng’s contributions significantly advance the field of intelligent structural systems and make him an outstanding candidate for a Best Researcher Award.

 

 

Atanaska Bosakova-Ardenska | Engineering | Best Researcher Award

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Prof. Dr. Atanaska Bosakova-Ardenska | Engineering | Best Researcher Award

Professor, University of Food Technologies, Bulgaria

Atanaska D. Bosakova-Ardenska is a Bulgarian researcher specializing in parallel algorithms, image processing, food quality evaluation, programming, and algorithms. She actively contributes to multidisciplinary fields through her innovative research and collaborations. With a focus on combining computer vision and food science, her work has earned recognition in academia and industry alike. 🖥️🍴📊

Publication Profile

ORCID

Education 🎓

Atanaska holds a robust academic background in computer science and engineering. Her educational journey has laid the foundation for her expertise in designing advanced algorithms and exploring their applications in practical domains like food quality assessment and educational tools. 📘💡

Experience 🌍

With years of experience in research and academia, Atanaska has published extensively in high-impact journals and contributed to international conferences. Her work bridges computer vision, parallel processing, and innovative educational methodologies, showcasing her versatility in addressing real-world challenges. 🔬🌐

Research Interests 🔎

Atanaska’s research revolves around parallel algorithms, image processing, and their applications in food quality evaluation. She is also keenly interested in advancing educational programming tools and algorithm development, striving to integrate theory with practical applications. 🧩📷📚

Awards 🏆

Throughout her career, Atanaska has received accolades for her contributions to computer science and food quality evaluation. Her commitment to interdisciplinary research and educational innovation has been recognized by peers and institutions globally. 🌟🥇

Publications 📚

Performance Evaluation of Recursive Mean Filter Using Scilab, MATLAB, and MPI (Message Passing Interface)
Published in: Engineering Proceedings, 2024-08
DOI: 10.3390/engproc2024070033

Design and Implementation of Educational Game Using Crossword Principles
Published in: Engineering Proceedings, 2024-07
DOI: 10.3390/engproc2024070012

Recent Trends in Computer Vision for Cheese Quality Evaluation
Published in: Engineering Proceedings, 2024-01
DOI: 10.3390/engproc2024060012

Application of Image Analysis Techniques for Quality Assessment of Swiss-type Cheese
Presented at: 2021 International Conference on Information Technologies (InfoTech), 2021-09-16
DOI: 10.1109/infotech52438.2021.9548462

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

       

Heung-Shik Lee | Robotics | Best Researcher Award

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Prof. Heung-Shik Lee | Robotics | Best Researcher Award

Professor, Joongbu University, South Korea

Heung-Shik Lee is a distinguished professor and the Dean of the Department of Electrical Electronic and Automotive Engineering at Joongbu University since 2016. 🌟 With a solid background as a technical advisory member for the Ministry of SMEs and Startups and the Ministry of Environment, Prof. Lee has made significant contributions to the field. Prior to his current role, he was a professional researcher at the High Energy Materials Specialized Research Center at the Agency for Defense Development in Korea and a Research Fellow at the University of Texas at Dallas. 🌐

Profile

Strengths for the Award:

  1. Innovative Research Focus: Prof. Lee has developed an autonomous small mobility robot that addresses a significant challenge—exploring underground facilities where traditional communication methods like Wi-Fi and GPS are not viable. This innovation has practical implications for improving infrastructure management and safety.
  2. Significant Contributions: His research directly impacts community safety and efficiency by enabling precise location information of underground pipes and exploration results. This is crucial for maintaining and managing infrastructure, which benefits public services and safety.
  3. Professional Expertise: Prof. Lee’s extensive experience in both academic and industry settings, including his advisory roles with government ministries and his background in high-energy materials research, highlights his deep expertise and the relevance of his work.
  4. Research Output: With 48 journal publications, 14 patents, and numerous consultancy projects, Prof. Lee demonstrates a high level of productivity and impact in his field. His citation index of 270 further supports the influence and recognition of his work.
  5. Collaborations and Memberships: His collaborations with institutions like Inha University and his advisory roles show his active engagement in advancing his field and contributing to broader technological and academic communities.

Areas for Improvement:

  1. Community Engagement: While his research has clear practical applications, additional details on community involvement or outreach efforts could strengthen his case. Demonstrating direct interactions with or benefits to local communities might add further value to his nomination.
  2. Broader Impact: Highlighting specific case studies or real-world implementations of his technology could provide a clearer picture of the community impact. Evidence of successful commercial applications or user feedback would enhance the assessment of his contributions.
  3. Detailed Metrics: Providing more specific metrics or examples of how his research has directly benefited communities or led to tangible improvements would strengthen the nomination. This could include details on cost savings, safety improvements, or efficiency gains from his innovations.

Education

Prof. Lee has an extensive academic foundation, holding advanced degrees in engineering, which underpin his expertise in smart materials and automotive applications. 📚

Experience

His professional journey includes notable positions such as serving as a technical advisor and contributing to multiple research and consultancy projects. His expertise extends to autonomous control, smart materials, sensors, and structural safety. 🚀

Research Interests

Prof. Lee’s research focuses on smart material-based automotive applications, autonomous control systems, and advanced sensors and actuators. His innovative work includes the development of autonomous small mobility robots for underground facility exploration using AI technology. 🤖

Awards

Prof. Lee is nominated for the Best Researcher Award, recognizing his exceptional contributions to the field of engineering and technology. 🏆

Publications

Mask R-CNN-Based Stone Detection and Segmentation for Underground Pipeline Exploration Robots

An Inverse Perspective Mapping-Based Approach for Generating Panoramic Images of Pipe Inner Surfaces

Analysis of Used Cars Price Determinant Factors Using IPA | IPA

Multiple IMU sensor fusion using resolution refinement method to reduce quantization error