Jana Al Haj Ali | Computer Science and Artificial Intelligence | Best Researcher Award

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Mrs. Jana Al Haj Ali | Computer Science and Artificial Intelligence | Best Researcher Award

Mrs. Jana Al Haj Ali | Computer Science and Artificial Intelligence | PhD Student | University of Lorraine | France

Mrs. Jana Al Haj Ali is an accomplished researcher and PhD student in Computer Engineering, specializing in the design and implementation of cognitive digital twins for industrial applications. Her work integrates neuro-symbolic AI approaches to enable intelligent, adaptive, and human-centric human-robot interaction within cyber-physical systems. Through her innovative research, she has contributed to advancing the understanding of cognitive architectures, simulation models, and interoperability protocols, aiming to improve automation, safety, and efficiency in Industry 5.0 contexts. She is known for combining technical expertise, scientific rigor, and collaborative spirit to drive impactful solutions at the intersection of artificial intelligence, robotics, and cognitive systems.

Professional Profile 

Education

Mrs. Jana Al Haj Ali holds a Bachelor’s degree in Mathematics, followed by a Master’s degree in Mathematical Engineering for Data Science, which provided her with an interdisciplinary foundation in mathematical modeling, machine learning, and computational techniques. She is currently pursuing her doctoral studies in Computer Engineering at a leading research institute in France, where she is actively engaged in high-impact research focusing on cognitive digital twin technologies. Her educational background bridges mathematics, data science, and computer engineering, allowing her to approach complex research problems from both theoretical and applied perspectives.

Experience

Mrs. Jana Al Haj Ali has extensive research experience in the development of modular architectures for cognitive digital twins, focusing on emulation, cognition, and simulation functionalities. She has implemented cognitive exchange protocols between industrial robots and human operators, enabling adaptive reconfiguration of cyber-physical systems based on real-time cognitive feedback. She also completed a visiting research project at a prominent European research institute, where she designed cognitive models and integrated them into simulation environments to evaluate collaborative performance. Additionally, she has experience in data analysis, machine learning modeling, and physical risk estimation from her earlier research internships.

Research Interest

Her primary research interests include cognitive cyber-physical systems, cognitive digital twins, neuro-symbolic AI, knowledge representation, and human-robot collaboration. She is particularly focused on enhancing cognitive interoperability, developing architectures that combine deep learning with symbolic reasoning, and designing intelligent simulation frameworks that predict system behavior in real-time. Her work aims to address key challenges in Industry 5.0 by creating more resilient, adaptive, and human-centric automation solutions.

Award

Mrs. Jana Al Haj Ali has been recognized for her contributions through opportunities to present her research at prestigious international conferences, summer schools, and national symposia. Her participation in scientific events and collaboration with international research teams reflects her growing impact in the academic community. She is highly regarded for her ability to translate complex cognitive models into practical implementations, earning acknowledgment from peers and mentors for her innovative approach.

Selected Publication

  • Human Digital Twins: A Systematic Literature Review and Concept Disambiguation for Industry 5.0 (2025) – 45 citations

  • Cognition in Digital Twins for Cyber-Physical Systems and Humans: Where and Why? (2024) – 30 citations

  • Cognitive Architecture for Cognitive Cyber-Physical Systems (2024) – 28 citations

  • Cognitive Systems and Interoperability in the Enterprise: A Systematic Literature Review (2024) – 33 citations

Conclusion

Mrs. Jana Al Haj Ali is an outstanding candidate for this award, with a strong academic background, impactful research contributions, and a commitment to advancing the field of cognitive digital twins and human-robot collaboration. Her work demonstrates a unique combination of theoretical innovation and practical application, contributing to the future of intelligent and adaptive industrial systems. With a growing publication record, active participation in international collaborations, and dedication to knowledge dissemination, she is well positioned to emerge as a leader in cognitive cyber-physical systems research.

 

Zhibin Liu | Computer Science and Artificial Intelligence | Best Researcher Award

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Assoc. Prof. Dr. Zhibin Liu | Computer Science and Artificial Intelligence | Best Researcher Award

Associate professor | School of Computer Science Qufu Normal University | China

Assoc. Prof. Dr. Zhibin Liu is a highly regarded academic and researcher in the field of computer science, currently serving as an associate professor at the School of Computer Science, Qufu Normal University. His professional journey demonstrates a strong commitment to advancing innovation in computing technologies, particularly within the areas of Internet of Things (IoT), machine learning, and reinforcement learning. He has established himself as a recognized scholar with notable research outputs and impactful contributions to the development of intelligent systems. His academic career reflects a balance between teaching excellence, high-quality research, and meaningful international collaborations, making him a respected figure among peers and students alike.

Professional Profile 

Education

Assoc. Prof. Dr. Zhibin Liu completed his doctoral studies in computer application technology at Hohai University, where he developed expertise in advanced computing techniques and intelligent network optimization. Prior to this, he obtained his master’s degree in computer science from Xi’an University of Science and Technology. His educational background has laid the foundation for his strong analytical skills, deep technical knowledge, and a research-oriented mindset that supports the integration of theory with practical applications. These academic milestones highlight his determination to pursue excellence in the evolving field of computer science and to contribute to the broader scholarly community through innovation and thought leadership.

Experience

Assoc. Prof. Dr. Zhibin Liu has extensive teaching and research experience in the domains of IoT, wireless communication systems, and computational intelligence. At Qufu Normal University, he has played a crucial role in mentoring students, supervising research projects, and leading collaborative academic initiatives. His contributions extend beyond national boundaries, as he has engaged with international researchers to develop joint solutions for pressing technological challenges. He has been actively involved in projects that emphasize routing algorithms, optimization of resource allocation, and the integration of reinforcement learning into real-world applications. Through his sustained efforts, he has strengthened the research culture within his institution and contributed to the growth of knowledge in cutting-edge areas of computer science.

Research Interest

The research interests of Assoc. Prof. Dr. Zhibin Liu are diverse and aligned with the global challenges in modern computing systems. His primary focus lies in the research and application of IoT and machine learning, with specific emphasis on routing algorithms and efficient resource allocation strategies for wireless sensor networks. He also investigates the integration of deep reinforcement learning to address optimization problems within communication systems. His work reflects a clear vision of enhancing scalability, energy efficiency, and computational performance in intelligent systems. This forward-looking research agenda demonstrates his commitment to bridging the gap between theoretical advancements and practical applications, ensuring his contributions remain relevant in addressing real-world challenges.

Award

Assoc. Prof. Dr. Zhibin Liu has received recognition for his impactful contributions to research and academia. His awards and honors highlight his role as a leading researcher in IoT and machine learning, particularly for his pioneering work in reinforcement learning and network optimization. These accolades reflect both institutional and scholarly recognition, positioning him as an influential figure in his domain. His dedication to academic excellence, research innovation, and community engagement has earned him respect and acknowledgment at both national and international levels. Such achievements signify his outstanding professional standing and underscore why he is a strong candidate for this award.

Selected Publication

  • Reinforcement learning based on multi agent value distribution for beamforming optimization in cellular networks (Published: 2021, Citations: 45).

  • Optimization of computational efficiency in IoT based on joint assistance of ARIS and UAV in MEC systems (Published: 2022, Citations: 32).

  • Energy efficient resource allocation strategy for wireless sensor networks using reinforcement learning (Published: 2020, Citations: 56).

  • Dynamic routing algorithm for IoT enabled smart environments through machine learning optimization (Published: 2019, Citations: 61).

Conclusion

Assoc. Prof. Dr. Zhibin Liu exemplifies academic excellence, research innovation, and leadership in the field of computer science. His contributions to IoT systems, reinforcement learning, and wireless network optimization have had significant influence, both in advancing knowledge and in enabling applications that address complex challenges in communication and computing. His achievements in research, combined with his dedication to mentoring students and leading collaborations, reflect his strong leadership qualities. With his consistent record of high-quality publications, international collaborations, and commitment to innovation, Assoc. Prof. Dr. Zhibin Liu is an outstanding candidate for this award. His future endeavors hold immense potential to shape the evolution of intelligent systems and contribute meaningfully to the global academic and scientific community.

Badr Machkour | Artificial Intelligence | Best Researcher Award

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Dr. Badr Machkour | Artificial Intelligence | Best Researcher Award

Professor, Faculty of Legal, Economic and Social Sciences, Morocco 

Dr. Badr Machkour is a Moroccan researcher and academic with deep expertise in economics, finance, and digital transformation. Currently holding a Ph.D. in Economic and Management Sciences, he has contributed to multiple domains including Industry 4.0, financial digitalization, and educational innovation. With a robust blend of academic and consulting experience, Dr. Machkour bridges theory and practice to drive impactful research. 🌐📊

Profile

Scopus

Google Scholar

Orcid

🎓 Education

Dr. Machkour holds a Doctorate in Economic and Management Sciences (2018–2023) from the FSJES of Agadir. His academic foundation includes a degree in Audit and Management Control from ENCG Agadir (2014–2017), post-preparatory classes in Economics and Commerce (2012–2014), and a Mathematics Baccalaureate (2011–2012). His diverse training forms a strong base for multidisciplinary research. 📚🧠

💼 Professional Experience

Dr. Machkour has extensive experience as a financial auditor, consultant, and trainer. He currently serves as a trainer at the Cité des Métiers et des Compétences (OFPPT), delivering finance and management programs. His previous roles span auditing and consulting at prominent firms like Augeco, MAZARS Maroc, and Agadir Conseil, involving sectors from agriculture to banking. 🏢💼📈

🔬 Research Interests

His research explores the intersection of Industry 4.0, digital banking solutions, customer experience, AI in education, and entrepreneurship. Dr. Machkour is particularly interested in how technology transforms economic relationships, pedagogical structures, and corporate strategies. 🤖📱🏫

🏆 Awards & Honors

While specific awards are not listed, Dr. Machkour’s work has been featured in indexed journals and cited internationally — notably his highly cited paper on Industry 4.0’s implications in finance. His academic contributions reflect both quality and influence. 🥇🌍

📑 Publications

Industry 4.0 and its Implications for the Financial Sector, Procedia Computer Science, 2020 — Cited by 151 🏦

The Rise of Artificial Intelligence in Educational Management: A Prospective Analysis on the Role of the Virtual Educational Director, Procedia Computer Science, 2025 🧠

Internet of Things in Education: Transforming Learning Environments, Enhancing Pedagogy, and Optimizing Resource Management, Data and Metadata, 2024 🏫

L’impact de l’adoption des solutions digitales sur la relation banque-client, Revue Française d’Economie et de Gestion, 2024 — Cited by 2 📲

Les facteurs d’adoption des solutions digitales bancaires par les consommateurs marocains, IJAFAME, 2022 — Cited by 1 📱

The Uses of Connected Objects and Their Influence on the Customer Experience, Test Engineering and Management, 2020 — Cited by 1 🌐

Etude exploratoire du développement de l’esprit Entrepreneurial et des compétences Entrepreneuriales auprès des étudiants au Maroc, Alternatives Managériales Economiques, 2024 👨‍🎓

Entrepreneurship 4.0 and Success Factors in the Context of Industry 4.0: A literature review, African Scientific Journal, 2024 🚀

✅ Conclusion

Overall, Dr. Badr Machkour is a promising and accomplished researcher whose work bridges digital innovation and economic practice with scholarly insight. His growing citation record, topical relevance, and interdisciplinary reach make him a strong candidate for the Best Researcher Award. With continued international engagement and broader collaborative networks, his impact is poised to grow even further. 🌍📈

Yue Wu | Machine Learning | Best Researcher Award

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Yue Wu | Machine Learning | Best Researcher Award

Assist. Prof. Dr Yue Wu, Hangzhou Dian, China

Assist. Prof. Dr. Yue Wu is a promising young academician whose work bridges the gap between automation, machine learning, and electronic design automation. Currently serving as an Assistant Professor at the School of Electronics and Information Engineering, Hangzhou Dianzi University, China, he exemplifies research excellence through his interdisciplinary expertise. He earned his Ph.D. from Zhejiang University in Aeronautics and Astronautics and a B.S. from Wuhan University of Technology in Automation. His scholarly interests focus on logic synthesis, physical design, and intelligent prediction algorithms using graph neural networks. Despite his early career stage, Dr. Wu has demonstrated impactful contributions to both academia and industry-relevant applications. His recent publication on pre-routing slack prediction using graph attention networks stands out as a novel solution in the realm of EDA. With a strong academic foundation and active research output, Dr. Wu is a fitting nominee for the Best Researcher Award, representing the next generation of innovation in AI-driven engineering.

Publication Profile

Orcid

Education

Dr. Yue Wu has a solid educational foundation in engineering and automation. He earned his Bachelor of Science (B.S.) in Automation from the Wuhan University of Technology in 2018. There, he developed a robust understanding of control systems, signal processing, and computational modeling. Pursuing his academic passion, he undertook doctoral studies at the School of Aeronautics and Astronautics, Zhejiang University, one of China’s premier research institutions. He completed his Ph.D. in 2023, focusing on interdisciplinary topics combining aeronautical engineering, data science, and intelligent systems. His doctoral work incorporated advanced machine learning techniques and their applications in hardware-aware environments, preparing him to lead novel research at the intersection of automation and electronics. This strong academic background equips him with the theoretical depth and practical experience essential for future-forward research in intelligent systems and electronic design automation.

Experience

Dr. Yue Wu is currently serving as an Assistant Professor at the School of Electronics and Information Engineering, Hangzhou Dianzi University, since 2023. Despite being in the early phase of his academic career, he has demonstrated exceptional scholarly promise through teaching, mentorship, and high-impact research. His role involves designing and delivering advanced courses on machine learning, logic circuits, and digital system design while actively supervising undergraduate and graduate research projects. He collaborates with interdisciplinary teams, focusing on the integration of machine learning techniques into physical design and logic synthesis processes, bridging hardware and AI innovations. Prior to this, he was involved in multiple research projects at Zhejiang University during his Ph.D., contributing to algorithm development and experimental validation of graph-based learning techniques. Dr. Wu’s combined expertise in automation, EDA tools, and machine learning positions him as a rising leader in academic research and technological advancement.

Awards and Honors

As a rising scholar, Dr. Yue Wu has been recognized for his academic achievements and research contributions. While specific institutional or national awards are yet to be recorded in the public domain, his selection as a faculty member at Hangzhou Dianzi University, known for its emphasis on electronic and information technology research, is a testament to his academic caliber. His recent first-author publication in the peer-reviewed journal “Automation” (2025) highlights his research excellence and innovation in the application of graph attention networks to pre-routing slack prediction, a complex problem in VLSI design. Additionally, his collaborative projects during his Ph.D. at Zhejiang University received internal recognition and contributed to multiple research grants. Dr. Wu’s research profile is steadily growing, and he is well on the path toward future accolades at the national and international levels as he continues to publish and lead in cutting-edge interdisciplinary domains.

Research Focus

Dr. Yue Wu’s research focuses on the intersection of machine learning and electronic design automation (EDA). His primary interest lies in developing intelligent systems that enhance the physical design and logic synthesis processes used in integrated circuit (IC) design. By leveraging advanced models like graph neural networks (GNNs) and attention-based architectures, Dr. Wu aims to address critical challenges such as slack prediction, timing analysis, and routing optimization. His expertise also extends to hardware-aware machine learning, wherein algorithmic efficiency is optimized for real-world applications in chip manufacturing. His recent work—“Pre-Routing Slack Prediction Based on Graph Attention Network”—demonstrates his ability to combine theoretical AI models with practical EDA problems. By pushing the boundaries of design automation through AI integration, Dr. Wu contributes to faster, smarter, and more power-efficient chip design—critical for the next generation of computing devices. His vision is to make intelligent design automation a core component of future electronics engineering.

Publication Top Notes

Pre-Routing Slack Prediction Based on Graph Attention Network

 

Inga Christina Miadowicz | Computer Science and Artificial Intelligence | Best Researcher Award

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Inga Christina Miadowicz | Computer Science and Artificial Intelligence | Best Researcher Award

Mrs Inga Christina Miadowicz, Deutsches Zentrum für Luft- und Raumfahrt, Germany

Dr. Inga Christina Miadowicz is a dedicated researcher specializing in IT management, industrial autonomy, and solar energy systems. She holds a Master’s in IT-Management from FOM Mannheim and a Bachelor’s in Applied Computer Science from DHBW Mannheim. Currently a Research Assistant at Deutsches Zentrum für Luft- und Raumfahrt (DLR), she leads projects in autonomous solar power plants and cyber-physical system infrastructures. Her expertise spans software engineering, distributed systems, and performance optimization. As a university lecturer at DHBW Mannheim, she teaches advanced software engineering and distributed systems. Her contributions to solar power plant digitization, industrial autonomy, and energy management have been published in renowned journals and conferences. She is an active participant in cutting-edge research on 5G communication for solar plants. With a strong foundation in IT architecture, cloud computing, and SAP technologies, she continues to drive innovation in the field of renewable energy and digital transformation. 🔬☀️🚀

Publication Profile

Orcid

Education

Dr. Inga Christina Miadowicz has a solid academic background in IT management and applied computer science. She earned her Master of Science in IT-Management (2018-2021) from Fachhochschule für Oekonomie und Management (FOM), Mannheim, where she specialized in enterprise IT strategies and digital transformation. Her Bachelor of Science in Applied Computer Science (2013-2016) from Duale Hochschule Baden-Württemberg (DHBW), Mannheim, provided her with hands-on experience in software development, system architecture, and distributed computing. She completed her Abitur (2004-2013) at Theodor-Fliedner-Gymnasium, Düsseldorf, establishing a strong foundation in STEM disciplines. Her commitment to continuous learning is reflected in multiple professional certifications, including Certified Business Professional and Certified Solution Professional (FICO), as well as specialized training in Apache Kafka, SAP HANA, SAPUI5, and OData services. Through her graduate program at DLR (since 2022), she continues to enhance her expertise in advanced IT solutions for industrial applications. 📚💡

Experience

Dr. Inga Christina Miadowicz has extensive experience in IT research, software development, and teaching. Since April 2022, she has been a Research Assistant at DLR (Cologne, Germany), leading projects on autonomous solar power plants and industrial autonomy. She has also served as a university lecturer at DHBW Mannheim (since 2018), teaching distributed systems and software engineering. Previously, she was a Lead Developer at FICO (2019-2022), where she developed anti-money laundering software and optimized performance engineering tools. As a Development Consultant at Slenderiser GmbH (2018-2019), she contributed to SAP S/4HANA transformations. Her tenure at SAP SE (2016-2018) focused on cloud and on-premise solutions for consumer industries. She also gained experience as a Dual Studies developer at ALDI SÜD (2013-2016), working on web and cloud computing solutions. Her diverse expertise in cyber-physical systems, SAP development, and IT architecture makes her a leading researcher in the field. 🚀🌞

Awards and Honors

Dr. Inga Christina Miadowicz has been recognized for her contributions to IT management, software engineering, and renewable energy research. She was awarded the Chinese Government Scholarship for her exceptional academic achievements. Her graduate program at DLR is a testament to her dedication to cutting-edge industrial research. She has received multiple professional certifications, including Certified Business Professional and Certified Solution Professional (FICO), as well as specialized SAP certifications like C_FIORIDEV_20. Her work on autonomous solar power plants and 5G communication for solar plants has been featured at prestigious conferences like SolarPACES. Her performance engineering contributions at FICO helped optimize anti-money laundering software, earning industry recognition. As a university lecturer, she has mentored numerous students in software development and distributed systems. Her commitment to research, education, and technological advancement positions her as a strong candidate for the Best Researcher Award. 🎖️📡☀️

Research Focus

Dr. Inga Christina Miadowicz focuses on industrial autonomy, digital transformation, and renewable energy optimization. At DLR, she leads research on autonomous solar power plants, developing cyber-physical systems and AI-driven automation for power plant operations. Her work integrates 5G communication networks with solar tower plants, enhancing real-time data processing and remote control capabilities. She specializes in distributed systems, software engineering, and cloud-based industrial solutions, particularly in SAP S/4HANA, Fiori applications, and performance engineering. Her research extends to data-driven hardware sizing tools, automation frameworks, and performance optimization for large-scale infrastructure. Her expertise in cybersecurity, IT architecture, and advanced analytics enables her to drive innovation in industrial digitalization. Through her publications in Solar Energy Advances and SolarPACES Conference Proceedings, she contributes to the advancement of solar energy integration and digital infrastructure for smart grids. Her work bridges the gap between IT, industrial automation, and sustainable energy solutions. 🌞📊💡

Publication Top Notes

📄 An Action Research Study on the Digital Transformation of Concentrated Solar Thermal Plants – Solar Energy Advances (2025)
📄 An Action Research Study on the Digital Transformation of Concentrated Solar Thermal Plants – Solar Energy Advances (2024-11-19)
📄 5G as Communication Platform for Solar Tower Plants – SolarPACES Conference Proceedings (2024-07-24)
📄 5G as Communication Platform for Solar Tower Plants – SolarPACES Conference Proceedings (2024-07-24, DOI: 10.52825/solarpaces.v2i.858)
📄 5G as Communication Platform for Solar Tower Plants – 29th International Conference on Concentrating Solar Power and Chemical Energy Systems, SolarPACES 2023