Rania Hamdani | Computer Science and Artificial Intelligence | Best Researcher Award

Ms. Rania Hamdani | Computer Science and Artificial Intelligence | Best Researcher Award

AE3S | University of luxembourg | Luxembourg 

Rania Hamdani is a dynamic early-career research scientist specializing in software engineering, data management, and cloud architecture for Industry 5.0 applications. Currently based at the University of Luxembourg, she is engaged in advanced research on integrating heterogeneous data sources and optimizing decision-making in cloud-based systems. With a strong foundation in software development and operational research, Rania has already co-authored three research papers in Cloud-Edge AI and ontology-driven knowledge management. Her diverse technical skills span Python, Java, Docker, Kubernetes, and Azure DevOps, and she has gained international experience through roles in Luxembourg, Canada, France, and Tunisia. Passionate about both academic and applied innovation, she has contributed to multiple interdisciplinary projects in AI, human-computer interaction, and intelligent systems. Rania is also active in professional communities such as IEEE and youth science associations, reflecting her commitment to collaborative growth and scientific outreach.

Professional Profile 

Education Background

Rania Hamdani has a strong academic foundation rooted in engineering and scientific rigor. She earned her Engineering Degree in Software Engineering from the National Higher School of Engineers of Tunis (ENSIT) between 2021 and 2024, where she specialized in Advanced Design, Service-Oriented Architecture, Object-Oriented Programming, Database Management, and Operational Research. Prior to that, she completed a Preparatory Cycle for Engineering Studies at the Preparatory Institute for Engineering Studies of Tunis (2019–2021), focusing intensively on mathematics, physics, and core technology subjects—a rigorous program designed to prepare students for elite engineering schools. Rania also holds a Baccalaureate in Mathematics from Pioneer High School Bourguiba Tunis, where she graduated with distinction (Very Good) in 2019. This academic journey has laid a solid foundation for her multidisciplinary research and professional growth in software and data sciences.

Professional Experience 

Rania Hamdani has developed a rich and diverse professional portfolio across academia and industry, with hands-on experience in software engineering, research, and cloud-based technologies. She is currently a Research Scientist at the University of Luxembourg (since November 2024), where she focuses on optimizing decision-making processes in cloud environments through advanced data integration techniques. Prior to this, she served as a Research Intern at the same institution (May to October 2024), contributing to projects in Ontology-Driven Knowledge Management and Cloud-Edge AI, resulting in three published papers. Alongside her academic work, Rania worked as a Part-Time Software Engineer at CareerBoosts in Canada (2021–2025), where she honed her skills in DevOps, data analysis, test automation, and backend development using tools like Python, Docker, and Kubernetes. Her earlier internships include roles at Qodexia (France), Sagemcom (Tunisia), and Tunisie Telecom, where she worked on smart recruitment platforms, employee management systems, and server monitoring tools using full-stack technologies such as SpringBoot, Angular, and PostgreSQL. This blend of research and industry experience positions Rania as a versatile and forward-thinking technology professional.

Research Interests of Rania Hamdani

Rania Hamdani’s research interests lie at the intersection of software engineering, operational research, data integration, and cloud-edge intelligence, with a strong orientation toward Industry 5.0 applications. She is particularly passionate about developing intelligent systems that enhance decision-making in cloud-based and distributed environments, leveraging AI, machine learning, and ontology-driven knowledge frameworks. Her work focuses on enabling seamless management of heterogeneous data sources, scalable architectures, and adaptive human-computer interaction (HCI) systems. Rania is also deeply engaged in exploring Cloud-Edge AI ecosystems, recommender systems, and automation pipelines using modern tools like Docker, Kubernetes, TensorFlow, and Neo4j. Her multidisciplinary approach reflects a vision for integrating research-driven insights with real-world industrial challenges, making her contributions both academically valuable and practically impactful.

Awards and Honors of Rania Hamdani

While still in the early stages of her research career, Rania Hamdani has demonstrated exceptional academic and technical promise. She graduated with a “Very Good” distinction in her Baccalaureate in Mathematics from the prestigious Pioneer High School Bourguiba in Tunis, reflecting her consistent academic excellence. Rania has also earned multiple professional certifications from Microsoft, including Azure Fundamentals, Azure Data Fundamentals, Azure AI Fundamentals, and Azure Security, Compliance, and Identity Fundamentals, showcasing her dedication to staying at the forefront of cloud and AI technologies. Though formal research awards or honors are not yet listed, her early publications, research contributions, and international internships highlight a trajectory poised for future recognition in both academic and industry spheres.

Publications Top Noted

Title: Adaptive human‑computer interaction for Industry 5.0: A novel concept, with comprehensive review and empirical validation
Year: 2025

Conclusion

Rania Hamdani is highly suitable for the Best Emerging Researcher or Young Researcher Award category. She has excellent technical skills, promising early-stage research output, international exposure, and a forward-looking vision in areas like Industry 5.0, cloud-edge intelligence, and AI-based decision systems. While still building her publication track record and academic leadership, her current trajectory shows strong promise for future impactful contributions to scientific and industrial domains.

Luis Pastor Sanchez-Fernandez | Computer Science and Artificial Intelligence | Cross-disciplinary Excellence Award

Prof. Dr. Luis Pastor Sanchez-Fernandez | Computer Science and Artificial Intelligence | Cross-disciplinary Excellence Award

Senior Researcher at Center for Computing Research Instituto Politecncico Nacional, Mexico

Luis Pastor Sánchez-Fernández is a Full Professor at the Computer Research Center of the National Polytechnic Institute (IPN) in Mexico City, with a PhD in Technical Sciences from the José Antonio Echeverría Polytechnic Institute (CUJAE), Havana (1998). A distinguished researcher and educator, he has been a member of Mexico’s National System of Researchers since 2007 (currently Level II). His work spans multiple disciplines, including biomechanics, bioinformatics, environmental acoustics, signal processing, expert systems, and intelligent automation. He has supervised over 13 doctoral and 46 master’s students, many of whom received honors or were inducted into national research systems. Dr. Sánchez-Fernández has led several research groups and CONACYT-funded projects, notably designing the Environmental Noise Monitoring System for the Historic Center of Mexico City. A recipient of the 2014 IPN Applied Research Award, he is also an accomplished keynote speaker, reviewer for high-impact journals, and advocate for interdisciplinary and socially impactful research.

Professional Profile 

🎓 Education of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández holds a PhD in Technical Sciences from the prestigious José Antonio Echeverría Polytechnic Institute (CUJAE) in Havana, Cuba, awarded in 1998. His doctoral education laid a strong interdisciplinary foundation, combining elements of engineering, computer science, and applied research. This academic background has been instrumental in shaping his cross-disciplinary research career, allowing him to contribute significantly to fields such as biomechanics, signal processing, and intelligent systems.

💼 Professional Experience of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández has served as a Full Professor at the Computer Research Center of the National Polytechnic Institute (IPN), Mexico City, since 2000, where he has been a key figure in advancing interdisciplinary scientific research and technological development. With over two decades of academic and research leadership, he has directed multiple research groups in bioinformatics and intelligent measurement systems, supervised numerous postgraduate theses, and mentored future leaders in science. His expertise spans diverse fields including biomechanics, environmental acoustics, expert systems, and automation. He has also played critical roles as a project leader for national research initiatives funded by CONACYT, and as an advisor and evaluator of scientific proposals. His contributions extend beyond academia into societal impact projects, such as the Environmental Noise Monitoring System for Mexico City, solidifying his reputation as a cross-disciplinary innovator and research leader.

🔬 Research Interests of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández’s research interests lie at the intersection of engineering, computer science, health sciences, and environmental studies, reflecting his strong cross-disciplinary approach. He focuses on the biomechanical analysis of patients with Parkinson’s disease, exploring computational and signal-based methods to improve medical diagnostics and rehabilitation. He is also deeply engaged in environmental acoustics, developing noise indicators and acoustic indices to assess and mitigate the harmful effects of urban noise pollution. His work extends into signal pattern recognition, expert systems, virtual instrumentation, and the design of intelligent systems for automation. Additionally, he has a sustained interest in bioinformatics, leading research groups that develop advanced computational tools for biological data analysis. His research consistently integrates theory and practical application, addressing real-world problems through innovative, multidisciplinary solutions.

🏅 Awards and Honors of Luis Pastor Sánchez-Fernández

Luis Pastor Sánchez-Fernández has received several prestigious awards and honors in recognition of his outstanding contributions to interdisciplinary research and academic mentorship. He was honored with the Applied Research Award by the National Polytechnic Institute (IPN) in 2014, acknowledging his impactful work that bridges scientific innovation and real-world application. As a dedicated mentor, he has received two thesis advisor awards from IPN, celebrating the excellence of his supervised postgraduate research. Many of his doctoral and master’s students have earned honorable mentions and Cum Laude distinctions, with several joining Mexico’s National System of Researchers—a testament to his role in cultivating high-caliber scholars. Since 2007, he has held Level II membership in the National System of Researchers of Mexico (SNI), further solidifying his reputation as a leader in cross-disciplinary scientific advancement.

🧾 Conclusion

The candidate demonstrates exceptional cross-disciplinary impact, strong leadership, and a deep commitment to advancing science at the intersection of multiple fields. His contributions in biomechanics, environmental monitoring, signal processing, and intelligent systems showcase not only depth but also the integration of diverse disciplines to address complex societal challenges. He is an ideal nominee for the Cross-disciplinary Excellence Award. Minor enhancements in visibility, global partnerships, and documentation of publications would make his case even more compelling.

📚 Publications by Luis Pastor Sánchez-Fernández

1.Title: Dataset for Gait Assessment in Parkinson’s Disease Patients

  • Authors: (Not provided)
  • Year: (Not explicitly listed)
  • Type: Data Paper – Open Access
  • Citations: 0

2.Title: Innovations and Technological Advances in Healthcare Remote Monitoring Systems for the Elderly and Vulnerable People: A Scoping Review

  • Authors: (Not fully listed)
  • Year: (Not explicitly listed)
  • Type: Review – Open Access
  • Citations: 0

3.Title: Computer Model for Gait Assessments in Parkinson’s Patients Using a Fuzzy Inference Model and Inertial Sensors

  • Authors: (Not fully listed)
  • Journal: Artificial Intelligence in Medicine
  • Year: 2025
  • Citations: 2

4.Title: Motion Smoothness Analysis of the Gait Cycle, Segmented by Stride and Associated with the Inertial Sensors’ Locations

  • Authors: (Not fully listed)
  • Journal: Sensors
  • Year: 2025
  • Type: Article – Open Access
  • Citations: 1

5.Title: Network Long-Term Evolution Quality of Service Assessment Using a Weighted Fuzzy Inference System

  • Authors: (Not fully listed)
  • Journal: Mathematics
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 0

6.Title: Biomechanics of Parkinson’s Disease with Systems Based on Expert Knowledge and Machine Learning: A Scoping Review

  • Authors: (Not listed)
  • Year: (Not explicitly listed)
  • Type: Review – Open Access
  • Citations: 0

7.Title: An Integrated Approach to the Regional Estimation of Soil Moisture

  • Authors: (Not fully listed)
  • Journal: Hydrology
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 0

8.Title: A Fuzzy Inference Model for Evaluating Data Transfer in LTE Mobile Networks via Crowdsourced Data

  • Authors: (Not fully listed)
  • Journal: Computación y Sistemas
  • Year: 2024
  • Type: Article
  • Citations: 1

9.Title: Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation

  • Authors: (Not fully listed)
  • Journal: Mathematics
  • Year: 2024
  • Type: Article – Open Access
  • Citations: 4

 

 

Maksym Koghut | Computer Science and Artificial Intelligence | United Kingdom

Dr. Maksym Koghut | Computer Science and Artificial Intelligence | United Kingdom

Lecturer at Manchester Metropolitan University, United Kingdom

Dr. Maksym Koghut is an accomplished academic and researcher at Manchester Metropolitan University Business School, UK, with a robust interdisciplinary background spanning management, engineering, and financial sciences. He holds a PhD in Management from the University of Kent and has taught at several leading UK institutions, delivering modules in digital transformation, blockchain, strategy, and innovation. His research focuses on the strategic implications of digital technologies, inter-organisational trust, and AI in business contexts, with publications in high-quality journals and presentations at prominent international conferences. In addition to his academic credentials, Dr. Koghut brings substantial industry experience through leadership roles in multiple startups across the UK and Ukraine. He is a Fellow of the Higher Education Academy and has been recognized with several academic and teaching awards, reflecting his excellence in both research and pedagogy.

Professional Profile 

🎓 Education of Dr. Maksym Koghut

Dr. Maksym Koghut has pursued a dynamic and interdisciplinary educational journey across the UK and Ukraine. He earned his PhD in Management from the University of Kent (2018–2021), where he developed a strong foundation in strategic management and digital transformation. Prior to that, he completed a BA (Hons) in Business Information Management at the University of Huddersfield (2014–2017), and a BA (Hons) in Financial Management from the Inter-Regional Academy of Personnel Management, Ukraine (2010–2012), highlighting his grounding in both information systems and finance. His academic path began with a BEng (Hons) in Mechanical Engineering from Cherkassy Engineering and Technological Institute, Ukraine (1995–2000), demonstrating a solid technical and analytical base. This unique combination of disciplines enhances his expertise in digital business, innovation, and organizational strategy.

💼 Professional Experience of Dr. Maksym Koghut

Dr. Maksym Koghut brings a wealth of professional experience that bridges academia and industry. He is currently a Lecturer at Manchester Metropolitan University Business School, where he leads and teaches postgraduate and degree apprenticeship modules focused on blockchain, digital transformation, and Industry 4.0. His previous academic roles include lecturing positions at Coventry University London, the University of Kent, and the University of Huddersfield, where he developed and led modules in strategic management, digital information systems, innovation, and entrepreneurship. Beyond academia, Dr. Koghut has a strong entrepreneurial background, having founded and directed several businesses in the UK and Ukraine, including Script Software Ltd (a robotics software company), MotorHood Platform Ltd, and other ventures in automotive services, photography, and industrial equipment. This dual experience in research and real-world business operations uniquely positions him as a thought leader in digital enterprise and innovation.

🔬 Research Interests of Dr. Maksym Koghut

Dr. Maksym Koghut’s research interests lie at the intersection of digital transformation and strategic management in modern business environments. He focuses on the strategic implications of emerging technologies such as blockchain, artificial intelligence, and augmented/extended reality (XR), especially in the context of inter-organisational relationships and digital enterprises. His work explores how social capital, trust, and innovation evolve in digitally networked ecosystems, offering insights into how organisations adapt and thrive amid rapid technological change. Dr. Koghut also investigates consumer behavior in digital settings, including mobile payment discontinuance and AI-generated advertising. His research is both conceptually grounded and practically relevant, contributing to academic scholarship and informing industry practices in the digital age.

🏆 Awards and Honors of Dr. Maksym Koghut

Dr. Maksym Koghut has been recognized multiple times for his outstanding contributions to both research and teaching. He received the “Above & Beyond Award” twice from Kent Business School in 2022 for excellence in teaching at both undergraduate and postgraduate levels. His academic journey has been supported by prestigious scholarships, including the Vice Chancellor’s Research Scholarship from the University of Kent in 2018 and the Vice Chancellor’s Scholarship for PhD Studies from Huddersfield Business School in 2017. Additionally, he was awarded the Strategic Planning Society Prize for being the Best Student in Strategy at Huddersfield Business School in 2017. These honors highlight Dr. Koghut’s consistent excellence, dedication, and impact in the academic and professional communities.

🏁 Conclusion

Dr. Maksym Koghut is a compelling and highly suitable candidate for the Best Researcher Award. He brings together a rich combination of academic excellence, cutting-edge research, teaching innovation, and industry engagement. His interdisciplinary expertise and consistent scholarly output in contemporary digital business themes position him as a thought leader in the digital transformation domain.

📚 Publications Top Noted

  1. Title: A Blockchain-based Inter-organisational Relationships: Social and Innovation Implications
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2021
    Citation: Academy of Management Proceedings, 2021-08
  2. Title: A Blockchain-based Inter-organisational Relationships: Social and Innovation Implications
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2021
    Citation: Academy of Management Proceedings, 2021-08
  3. Title: The Effects of Autonomous Contracting on Inter-organisational Relationships: A Process Model of Trust, Social Capital and Value Co-creation
    Authors: Maksym Koghut, Omar Al-Tabbaa, Soo Hee Lee, Martin Meyer
    Year: 2020
    Citation: British Academy of Management Annual Conference, 2020-09-04
  4. Title: The Blockchain-Trust Nexus: A New Era for Inter-organizational Trust Meaning and Formation
    Authors: Maksym Koghut, Omar Al-Tabbaa, Martin Meyer
    Year: 2019
    Citation: Academy of Management Proceedings, 2019-08
  5. Title: Modelling Decentralised Collaboration Between Engineering Teams: A Blockchain-based Solution
    Authors: Maksym Koghut, John Makokha
    Year: 2018
    Citation: VI International Scientific and Technical Conference, 2018-09-01

GULDANA MAKASHEVA | Engineering and Technology | Research Hypothesis Excellence Award

GULDANA MAKASHEVA | Engineering and Technology | Research Hypothesis Excellence Award

Leading Research Scientist at LLP KazHydroMed, Kazakhstan

Mrs. Guldana Makasheva is a seasoned metallurgical researcher and Senior Research Scientist at LLP KazHydroMed, Kazakhstan. With over a decade of hands-on and theoretical experience across various roles in metallurgy, her expertise lies in flotation, hydrometallurgy, and the beneficiation of complex ores and industrial tailings. She is currently pursuing a Ph.D. in Metallurgy at Satbayev University and holds advanced degrees in Metallurgy and Organic Chemistry. Her career spans from laboratory chemist to lead engineer, demonstrating her adaptability and growth. Makasheva has authored numerous scientific publications in both national and international journals and has contributed to high-impact projects aimed at developing eco-friendly and efficient mineral processing technologies. Her research, marked by technical precision and practical relevance, has addressed pressing industrial challenges in Kazakhstan’s mining sector. With a strong foundation in hypothesis-driven experimentation, she exemplifies the principles celebrated by the Research Hypothesis Excellence Award.

Publication Profile

Orcid

Education

Mrs. Makasheva holds a Master’s degree in Technical Sciences with a specialization in Metallurgy and Mineral Processing from Satbayev University, one of Kazakhstan’s premier technical institutions. Her academic foundation began with a Bachelor’s in Chemistry of Organic Substances from Karaganda State University named after E.A. Buketov, where she gained solid grounding in analytical and synthetic chemistry. Continuing her academic journey, she is currently pursuing her Ph.D. in Metallurgy at Satbayev University (2023–present), focusing on advanced beneficiation techniques and processing of complex ore materials. Her academic background is complemented by specialized certifications, including a Certified PC User qualification and Accounting & 1C certification, highlighting her commitment to interdisciplinary skills. Her education has consistently supported her progression as a research leader in metallurgical science, emphasizing innovation, practical application, and publication in high-impact forums. 🎓📘🧪

Experience

Mrs. Guldana Makasheva’s professional trajectory reflects deep engagement with Kazakhstan’s metallurgical sector. Since 2021, she has served as a Senior Research Scientist at LLP KazHydroMed, where she designed cutting-edge research programs and executed pilot-scale tests in slag and ore processing. Earlier, as Lead Process Engineer at JSC “Zhairem GOK” (2020–2021), she worked on mineral flow diagrams and thickening technologies. At JSC “Varvarinskoye” (2011–2020), she ascended from Laboratory Chemist to Metallurgical Process Engineer, gaining end-to-end operational experience—from ore crushing to desorption and AAS/XRF analysis. Her earliest role was at the Institute of Organic Synthesis and Coal Chemistry, where she synthesized catalysts and conducted chromatographic studies. Each position honed her skills in technical reporting, pilot experiments, and project leadership, building a solid foundation for her present-day research excellence.

Awards and Honors

While specific national or international awards are not listed, Mrs. Guldana Makasheva’s consistent leadership in funded scientific projects and co-authorship of peer-reviewed publications signifies her recognition within the scientific community. Her appointment as Lead Investigator across multiple major projects—such as beneficiation of legacy tailings and development of flotation technologies—indicates institutional trust and high-level peer acknowledgment. She has also been a frequent contributor to SCOPUS-indexed and national journals, suggesting editorial confidence in her scientific rigor. As a Senior Research Scientist, she has been a key figure in government and industrial research initiatives, often coordinating multidisciplinary teams to address Kazakhstan’s critical metallurgical challenges. Her accolades are implicit in her elevation to senior scientific ranks and her pivotal roles in transformative projects. Her ongoing Ph.D. candidacy further reflects academic recognition and career progression.

Research Focus

Mrs. Makasheva’s research spans flotation chemistry, hydrometallurgical processing, ore beneficiation, and tailings revalorization. Her core investigations involve innovative techniques for processing refractory oxidized ores and polymetallic tailings, with special emphasis on flotation using hydroxamate-based collectors and gravity-flotation technologies. She has actively contributed to pilot testing for slag processing from metallurgical plants and has optimized concentrate thickening strategies. Her projects are critical to sustainable resource management, addressing legacy waste streams from major mining hubs like Balkhash and Zhezkazgan. Guldana also explores the oxidative-reductive potential in ore enrichment and thermochemical methods for improving flotation performance. Her current Ph.D. research likely intersects with these themes, pushing boundaries in extractive metallurgy. With a clear focus on bridging lab research with field applications, her work is both environmentally and economically transformative.

Publication Top Notes

Jiantao Shi | Robotics and Automation | Best Researcher Award

Jiantao Shi | Robotics and Automation | Best Researcher Award

Mrs Jiayun Nie, chongqing Jiaotong University, China

Jiayun Nie is a distinguished professor at Nanjing Tech University, China, specializing in cooperative control of multi-robot systems, fault diagnosis, and fault-tolerant control of distributed systems. 📡 With a Ph.D. in Control Science and Engineering from Tsinghua University, she has made pioneering contributions to multi-agent systems, UAV adaptive control, and reinforcement learning-based fault diagnosis. ✈️🔍 Her research has led to high-impact publications on fault estimation, bipartite consensus, and deep learning models for system diagnostics. 🤖 She has served as a research fellow at the Nanjing Research Institute of Electronic Technology and has received recognition as an Outstanding Reviewer for the Journal of the Franklin Institute (2017). 📚 Her latest work explores AI-driven fault-tolerant frameworks for autonomous systems and aerospace applications. 🚀 With a stellar academic record and transformative research, she is a deserving recipient of the Best Researcher Award. 🏅

Publication Profile

Orcid

Education

Jiayun Nie’s academic journey is marked by excellence in control science and automation engineering. She earned her Ph.D. in Control Science and Engineering from Tsinghua University (2011-2016), focusing on fault-tolerant systems and adaptive control strategies for multi-robot cooperation. 🤖🔍 Her doctoral research introduced novel iterative learning algorithms for fault estimation and compensation, improving system reliability. Before this, she completed her B.E. in Electrical Engineering and Automation at Beijing Institute of Technology (2007-2011), where she laid the groundwork in robotic control, embedded systems, and automation engineering. 🎛️⚡ During her studies, she was actively involved in research projects on UAV dynamics and cooperative control theory, leading to early publications and innovative designs for fault-resilient robotics. 🚀 Her strong educational foundation, combined with rigorous research, has positioned her as a global leader in fault diagnosis and control engineering. 📚

Experience

Jiayun Nie has an extensive academic and research career, currently serving as a Professor at Nanjing Tech University (2021-present), where she leads groundbreaking work on distributed control and autonomous systems. 🤖🔍 Prior to this, she was a Research Fellow (2019-2021) and Associate Research Fellow (2016-2018) at the Nanjing Research Institute of Electronic Technology, contributing to fault detection models for phased array radar transceivers and advanced control strategies for UAVs. ✈️📡 Her expertise in adaptive control and AI-driven fault detection has been instrumental in developing next-generation intelligent robotic networks. 🚀 Throughout her career, she has collaborated with leading research institutions, advancing the state-of-the-art in reinforcement learning-based fault diagnosis, consensus control, and multi-agent fault-tolerant frameworks. 🏅 Her work continues to influence aerospace, robotics, and autonomous vehicular technologies, making her an authority in the field. 📚

Awards and Honors

Jiayun Nie’s outstanding contributions to robotics and fault-tolerant control have earned her several prestigious accolades. 🎖️ She was recognized as an Outstanding Reviewer for the Journal of the Franklin Institute (2017) 📚, reflecting her expertise in control systems and automation engineering. 🚀 Her innovative research on fault diagnosis in distributed robotic systems has been cited extensively, leading to multiple best paper awards at international IEEE and IFAC conferences. 🏅 She has received multiple grants and funding awards for her pioneering work in multi-agent cooperative control and AI-driven adaptive learning control. 🤖 As a highly regarded professor and researcher, her contributions continue to impact autonomous systems, aviation safety, and smart robotics. ✈️ With her extensive publications and transformative research, she is a deserving recipient of the Best Researcher Award, recognized for her excellence in innovation and scientific advancement. 🏆📡

Research Focus

Jiayun Nie’s research revolves around cooperative control, fault diagnosis, and learning-based fault-tolerant strategies in autonomous systems. 🤖 She has made significant breakthroughs in multi-robot cooperation, bipartite consensus, and AI-driven adaptive fault detection. 📊 Her work in fault-tolerant control enhances resilience in UAVs and aerospace systems, ensuring robustness against unknown disturbances and failures. ✈️ She has developed deep learning and reinforcement learning models for self-healing robotic networks, transforming distributed control frameworks. 🏅 Her studies in event-based control, collision avoidance, and system stability have contributed to advancements in autonomous vehicle technology. 🚀 By integrating data-driven methods with real-time fault estimation, her research provides solutions for smart transportation, defense, and aerospace industries. 📡 With numerous high-impact publications, Jiayun Nie’s pioneering work defines the future of adaptive robotics and autonomous systems. 🎓

Publications Top Notes

  1. “A parallel weighted ADTC-Transformer framework with FUnet fusion and KAN for improved lithium-ion battery SOH prediction” 🔋 (2025)
  2. “Bipartite Fault-Tolerant Consensus Control for Multi-Agent Systems with a Leader of Unknown Input Under a Signed Digraph” 🤖 (2025)
  3. “Iterative learning based fault estimation for stochastic systems with variable pass lengths and data dropouts” 📊 (2025)
  4. “A Two-Stage Fault Diagnosis Method With Rough and Fine Classifiers for Phased Array Radar Transceivers” 📡 (2024)
  5. “An intuitively-derived decoupling and calibration model to the multi-axis force sensor using polynomials basis” 📊 (2024)
  6. “Event-Based Adaptive Fault Tolerant Control and Collision Avoidance of Wheel Mobile Robots With Communication Limits” 🤖 (2024)
  7. “Reinforcement Learning-Based Fault Tolerant Control Design for Aero-Engines With Multiple Types of Faults” ✈️ (2024)

Shichang Chen | Tech Innovations | Best Researcher Award

Shichang Chen | Tech Innovations | Best Researcher Award

Dr Shichang Chen, Zhejiang Sci-Tech University, China

Dr. Shichang Chen 🎓🔬 is a distinguished researcher in polymer materials and engineering. He earned his Ph.D. from Zhejiang Sci-Tech University (2017) and completed postdoctoral research at Zhejiang University (2019-2022). Currently, he is a faculty member at Zhejiang Sci-Tech University. His innovations have led to large-scale reactor applications, with 40 invention patents (22 authorized) and transactions exceeding 100 million yuan 💡💰. He has led multiple national and provincial projects and published 40+ papers in top journals 📄📚. Recognized with prestigious awards, including Zhejiang Province’s High-level Talent Support Program (2024), Dr. Chen advances polymer science and engineering globally 🌍.

Publication Profile

Scopus

Education and Experience

Dr. Shichang Chen 🎓 is a dedicated researcher in polymer materials. He earned his Bachelor’s degree in Polymer Materials and Engineering from Yangtze University (2007-2011) 🏛️. He then pursued his Ph.D. in Textile Science and Engineering at Zhejiang Sci-Tech University (2011-2017) 🧵🔬. Following this, he completed a postdoctoral fellowship in Materials Science and Engineering at Zhejiang University (2019-2022) 🏅. Since 2017, he has been contributing to the Department of Polymer Materials at Zhejiang Sci-Tech University 📚🧪. His expertise spans polymer materials, textiles, and advanced material sciences, driving innovation in the field 🚀.

Research Funding & Projects

Dr. Shichang Chen 🎓🔬 has successfully secured and led multiple prestigious research projects, showcasing his expertise in scientific innovation. His achievements include securing 2 National Funds 🇨🇳, 2 Zhejiang Provincial Funds 🏅, and 10 Enterprise Projects 💼. He has actively contributed to key national research initiatives, including the 973 Program 🔍, National Key R&D Programs 🧪, and three strategic consulting research projects at the Chinese Academy of Engineering 🏛️. Dr. Chen’s dedication to advancing research and technological development continues to make a significant impact in his field. 🚀📚

Research Achievements 

Dr. Shichang Chen has made remarkable contributions to reactor applications for 10,000-ton and 1,000-ton production lines ⚙️🏭. He has declared 40 invention patents, with 22 authorized, and patent transactions exceeding 100 million yuan 💡💰. As a lead researcher, he has hosted 2 national funds, 2 Zhejiang Provincial funds, and 10 enterprise projects, while also playing a key role in national 973 and strategic consulting research projects 📊🔬. With a strong academic presence, he has published a book and 40 papers in top-tier journals like Macromolecules, focusing on polymers and chemical engineering 📖🧪.

Honor Award 

Dr. Shichang Chen 🎓 is a distinguished researcher recognized for his contributions to textile science. In April 2024, he was selected for the Zhejiang Province High-level Talent Support Program as a young top talent 🌟. The previous month, he joined the Zhejiang Academician Pair Young Talents Program 🏅. His excellence was also acknowledged in October 2021 when he was awarded the China Association for Science and Technology Youth Lifting Talent Project 🚀. Additionally, he serves as a Young Editorial Member for the EI Journal of Textile Research (December 2021) and Modern Textile Technology (January 2023) 📖🔬.

Research Focus

Dr. Shichang Chen’s research focuses on polymer engineering, mooring rope mechanics, and chemical process simulations 🔬⚙️. His work includes dynamic stiffness analysis of damaged polyester mooring ropes 🛳️, the mechanical behavior of aramid and polyester fibers under loading history ⚡, and falling film polymerization processes 🏭. He also explores numerical simulation of variable viscosity fluids 💻🔄 and waste PET depolymerization for recycling ♻️🧪. His studies contribute to marine engineering, textile chemistry, and sustainable polymer recycling, advancing both industrial applications and environmental sustainability 🌍🔄. His expertise spans mechanics, materials science, and chemical engineering 🏗️⚗️.

Publication Top Notes

Dynamic stiffness of full-scale damaged polyester mooring ropes

Effects of bedding-in loading history on mechanical behaviors of aramid HMPE and polyester mooring ropes

Process Simulation of falling film liquid-state polymerization of polyester

Numerical Simulation Strategy and Applications for Falling Film Flow with Variable Viscosity Fluids

Depolymerization of waste poly(ethylene terephthalate) into bis(2-hydroxyethyl) terephthalate: Catalytic glycolysis mechanism and kinetics

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Ali Othman Albaji | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Ali Othman Albaji, Libyan Authority for Scientific Research, Libya

With a Bachelor’s in Electrical Engineering and a Master’s in Electronics & Telecommunications from Universiti Teknologi Malaysia, this accomplished professional has extensive experience in academia and industry. Currently an Assistant Professor at the Higher College of Science and Technology in Libya, they also lead CR Technology System in the MENA region. Their research interests include optical wireless technologies and machine learning applications in environmental monitoring. Fluent in Arabic and English, with a diploma in Italian, they are also the President of the Postgraduate Student Society at UTM. 📡🎓🌍✍️

Publication profile

google scholar

Academic Background 

With a diverse academic journey, the individual holds a Master’s in Public Management and Leadership from the London School of Economics (LSE), UK, completed in 2010. They further pursued a Master in Electronics and Telecommunications at the University Technology Malaysia from 2019 to 2023. Their foundational education includes a Bachelor’s degree in Electrical Engineering, specializing in General Communications, from the Civil Aviation Higher College in Tripoli, Libya, earned in 2007. Additionally, they completed a Diploma in the Italian language during the 2011/2012 academic year. 🎓📡

Experience

Dr. Ali Othman Albaji boasts a diverse work history across reputable organizations. He started as a Sales Advisor at Akida Company (LG) and ZTE/Telecom China, honing his expertise in the telecommunications field. His academic journey includes significant roles as an Assistant Professor and lecturer in Electronics and Telecommunications. In addition to his teaching, he has demonstrated leadership as the Chairman of CR Technology System (CRTS Group) and the President of the Postgraduate Student Society at Universiti Teknologi Malaysia. Dr. Albaji’s commitment to both academia and industry underscores his dedication to advancing technology and education. 📡🎓💼🌟

Main Hard Skills 

Dr. Albaji possesses a robust set of technical skills, including proficiency in CAD Design, MATLAB Simulation Analysis, Python, and data visualization tools like Tableau. His capabilities extend to qualitative and quantitative analysis, SCADA systems, and programming languages like Verilog and HTML. These skills enable him to tackle complex research problems and contribute innovatively to his field. 

Languages 

Fluent in Arabic and English, with an IELTS Band Score of 8.5, Dr. Albaji also has a very good command of Italian. This linguistic proficiency allows him to collaborate with international researchers and disseminate his work to a broader audience. 

Research focus

Ali Othman Albaji’s research focus centers on machine learning applications in environmental noise classification, emphasizing smart cities and mobile communications. His work includes developing algorithms for monitoring and classifying noise pollution using MATLAB, contributing to urban planning and public health. He has also explored traffic noise impacts on residential areas and mobile telecommunications in Libya. His diverse research interests extend to the design and implementation of communication systems, highlighting the integration of technology in environmental studies. Through these contributions, Albaji aims to enhance noise management and promote sustainable urban environments. 🌍📊🔊📡

Publication top notes

Investigation on Machine Learning Approaches for Environmental Noise Classifications

A Machine Learning for Environmental Noise Monitoring and Classification Using Matlab

Machine Learning for Environmental Noise Classification in Smart Cities

Designing the Global System for Mobile Communications GSM-900 Cellular Network up to the Nominal Cell Plan in Tripoli, Libya

Conclusion and Recommendations

A Review of Traffic Highway Noise Towards Residential Area

NOISE POLLUTION DATA REPORTING AND WAREHOUSING USING TABLEAU SOFTWARE

Designing and Implementing a Signed Multiplier Radix-2 Using Booth’s Algorithm