Nasser Mozayani | software | Best Researcher Award

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Dr. Nasser Mozayani | software | Best Researcher Award

Associate Professor, Iran University of Science and technology, Iran

🎓 Dr. Nasser Mozayani is an Associate Professor at the School of Computer Engineering at Iran University of Science and Technology (IUST) in Tehran, Iran. With a distinguished career in computer engineering, he has contributed significantly to research, teaching, and administration in his field. Dr. Mozayani specializes in machine learning, multi-agent systems, and the metaverse, bringing innovative insights into these cutting-edge areas. He has held several prominent positions at IUST, including Dean of the Computer Engineering Department, and has been actively involved in national research and technological projects.

Publication Profile

ORCID

Education

📘 Dr. Mozayani completed his Ph.D. in Informatics at the University of Rennes I in France (1998), where he conducted groundbreaking research on spatio-temporal coding in neural networks. His educational journey also includes an M.Sc. in Telematics & Information Systems from SUPELEC, France (1994), and a B.Sc. in Electrical Engineering (Computer Hardware) from Sharif University of Technology in Tehran, Iran (1990).

Experience

👨‍🏫 Dr. Mozayani has been an Associate Professor at IUST since 1999, teaching undergraduate courses in electronic and electric circuits, and advanced graduate courses in fields like artificial neural networks, digital circuits synthesis, and distributed AI. He has also held visiting professor roles at Allameh Tabatabaee University and Tarbiat Modarres University, where he specialized in educational games and simulations for doctoral students. In administrative capacities, he has led multiple departments and centers at IUST, contributing to the growth of e-learning and technology innovation.

Research Focus

🔬 Dr. Mozayani’s research is centered on machine learning, multi-agent systems, and smart grid applications. He has led numerous projects on smart grid communication protocols, reinforcement learning, and the application of AI in predictive modeling and decision-making for health and energy sectors. His innovative work in hierarchical reinforcement learning has advanced the integration of machine learning in smart grid management and infrastructure.

Awards and Honors

🏆 Dr. Mozayani has supervised the IUST RoboCup team, which achieved notable successes, including a first-place win in the Rescue Virtual Robots competition at the Khwarizmi Young Award (2010) and a top-four ranking in the World RoboCup 2D football simulation (2013). He has also mentored award-winning student projects in digital library development, recognized by the Khwarizmi Young Award.

Publications – Top Notes

“Deployment of a Flexible Communication Protocol for Advanced Metering in Smart Grid” (IUST, 2023), cited by 5 articles Journal: Smart Grid Technologies.

“Algorithmic Trading on Financial Time Series Using Deep Reinforcement Learning” (IUST, 2022), cited by 10 articles Journal: Financial Technology & AI.

“Using Machine Learning Methods to Determine Factors Affecting COVID-19 Mortality Rates” (IUST, 2021), cited by 8 articles Journal: Health Informatics.

 

Robin Augustine | Artificial Intelligence | Excellence in Research

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Assoc. Prof. Dr. Robin Augustine | Artificial Intelligence | Excellence in Research

Associate Professor, Uppsala University, Sweden

🎓 Associate Professor Robin Augustine is a renowned expert in Medical Engineering and Microwave Technology, leading research at Uppsala University in Sweden. He heads the Microwaves in Medical Engineering Group at the Angstrom Laboratory, Department of Electrical Engineering, and serves as an Associate Editor for IET journals. His interdisciplinary work spans medical sensor development, bioelectromagnetic interactions, and innovative in-body communication technologies. Robin has collaborated globally as a visiting professor and researcher, focusing on advancements in medical engineering through impactful research projects.

Publication Profile

Scopus

Education

📚 Dr. Robin Augustine earned his Ph.D. in Electronics and Optronics Systems from Université de Paris Est Marne La Vallée, specializing in human tissue electromagnetic modeling and its implications for medical sensor design. He holds an MSc in Electronics Science with a focus on Robotics from Cochin University of Science and Technology, and a BSc in Electronics Science from Mahatma Gandhi University. His expertise is further strengthened by advanced training in Diagnostic and Therapeutic Applications of Electromagnetics from Politecnico di Torino, Italy.

Experience

💼 Robin’s career includes extensive experience as a senior lecturer and associate professor at Uppsala University, where he has been leading research in microwave applications for medical technology since 2011. He has held visiting professorships and research roles at institutions such as the Beijing Institute of Nanoenergy and Nanosystems and University Medical Center Maastricht, contributing to medical sensor innovation and orthopedic measurement systems. Robin has also worked internationally, including postdoctoral research in France, with expertise in antenna design, bioelectromagnetics, and microwave characterization.

Research Focus

🔬 Robin’s research focuses on medical engineering, bioelectromagnetics, and intra-body communication, including developing microwave-based sensors for diagnosing conditions like osteoporosis, skin cancer, and muscular atrophy. As a leader in the B-CRATOS and COMFORT projects, he explores body-centric technologies and in-body wireless communication to enhance medical diagnostics. His pioneering work addresses the integration of electromagnetic technology with healthcare, making strides in non-invasive monitoring systems.

Awards and Honours

🏆 Dr. Augustine’s impactful research has attracted numerous grants and awards, including significant EU funding for projects like PERSIMMON and DIAMPS. He has secured research funding from bodies such as the Swedish Research Council, Vinnova, and the Foundation for Strategic Research, supporting his innovative work on body communication systems and medical diagnostics. His research has earned recognition through the Swedish Excellence Grant for Young Researchers and multiple grants for advancing medical engineering solutions.

Publication Top Notes

Biphasic lithium iron oxide nanocomposites for enhancement in electromagnetic interference shielding properties

Rotation insensitive implantable wireless power transfer system for medical devices using metamaterial-polarization converter

Improving burn diagnosis in medical image retrieval from grafting burn samples using B-coefficients and the CLAHE algorithm

 

slimane arbaoui | Artificial Intelligence | Young Scientist Award

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Mr. slimane arbaoui | Artificial intellegence | Young Scientist Award

Cube-SDC team, INSA Strasbourg, University of Strasbourg , 24 Bd de la Victoire, Strasbourg, 67000, France, insa strasbourg, France

Slimane Arbaoui is a dedicated final-year Computer Science student at École Supérieure en Informatique (ESI) in Sidi Bel Abbess, Algeria, specializing in Android application development and machine learning. 🎓 His skills span Java-based Android development, data integration, and advanced problem-solving in software, alongside a versatile understanding of multiple programming languages, including Python and Kotlin. Slimane has applied his AI knowledge to impactful projects, even authoring a research paper. 📚 Known for his innovation and strong analytical skills, Slimane is passionate about tackling real-world challenges with technology.

Publication Profile

Scopus

Education

Slimane completed his State Engineering and Master’s degrees in Computer Science at ESI SBA in 2023. 🎓 His academic journey has strengthened his technical expertise and provided a foundation in both theoretical and applied computing, with a focus on machine learning, mobile app development, and web technologies.

Experience

During his internship at INSA-Strasbourg, France 🇫🇷, Slimane applied machine learning to improve battery health prediction, developing models that track and identify factors contributing to battery degradation. At CNAS in Algeria, he gained practical insights into network database applications and web app development. 💻 As a freelancer on Upwork, Slimane developed Android applications and managed web back-end services, demonstrating his versatility in real-world projects.

Research Focus

Slimane’s research interests center on artificial intelligence and machine learning, with a special focus on NLP applications, sentiment analysis, and health data prediction. 🧠 His projects include sentiment analysis and fake news detection in Arabic language datasets, alongside health management applications that leverage data-driven insights to enhance service quality. His work in battery health prediction highlights his proficiency in machine learning model development and evaluation.

Awards and Honours

Slimane holds several certifications, including Microsoft Certified: Azure Fundamentals and the Android Basics Nanodegree. 🏅 His achievements in AI include completing courses on deep learning and machine learning through Kaggle and Coursera, which demonstrate his commitment to continuous learning and professional development.

Publication Top Notes

Dual-model approach for one-shot lithium-ion battery state of health sequence prediction

SOCXAI: Leveraging CNN and SHAP Analysis for Battery SOC Estimation and Anomaly Detection

Data-driven strategy for state of health prediction and anomaly detection in lithium-ion batteries

 

 

MOHORA FEIDA MALEBATJA | Health Sciences | Best Researcher Award

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Ms. MOHORA FEIDA MALEBATJA | Health Sciences | Best Researcher Award

Lecturer, Sefako Makgatho Health Sciences University, South Africa

🌍 Mohora Feida Malebatja is an accomplished Lecturer in Environmental and Occupational Health Sciences at Sefako Makgatho Health Sciences University, with a dedication to advancing public health through research and education. As a PhD candidate in Public Health, she brings a wealth of experience from her previous roles in epidemiology and water and sanitation management, demonstrating her commitment to improving health outcomes across South Africa.

Publication Profile

ORCID

Education

🎓 Mohora holds a master’s degree in Public Health, specializing in Environmental and Occupational Health, from the University of Pretoria, alongside a BSc Hons in Environmental Technology. Her foundational studies in Community Water Services from the University of Limpopo have anchored her expertise in health sciences and environmental protection.

Experience

🧑‍🏫 Before entering academia, Mohora served as an Epidemiologist, a Water and Sanitation Manager, and in Water Boards oversight roles, contributing significantly to public health efforts. She now supervises master’s research students and actively participates in academic committees, underscoring her leadership and dedication to student success and curriculum development.

Research Focus

🔬 Mohora’s research is centered on Environmental Health, Water Quality, Occupational Hygiene, Mental Health, Environmental Toxicology, Climate Change, and Air Quality. Her projects have included evaluating microbiological water quality impacts on children’s health and developing environmental health interventions for women in Gauteng.

Awards and Honors

🏆 Mohora’s accomplishments include her role as an occupational and health safety representative and her involvement in esteemed mentorship programs like the British Academy Mentorship and the New Generation of Academics Programme. Her impact in health sciences is also seen in her numerous manuscript reviews and grant assessments.

Publication Top Notes

Link 1: The Impact of Environmental Factors on Public Health – Published in Applied Sciences, 2023. [Cited by: 5 articles] (https://www.mdpi.com/2076-3417/14/19/9152)

Link 2: Evaluating Occupational Health Risks in Urban Areas – Published in Healthcare, 2023. [Cited by: 3 articles] (https://www.mdpi.com/2227-9032/12/20/2090)

Link 3: Assessing Mental Health Impacts of Environmental Exposure – Published in International Journal of Environmental Research and Public Health, 2023. [Cited by: 4 articles] (https://www.mdpi.com/1660-4601/20/1/598)

Md. Sajeebul Islam Sk. | Natural Language Processing | Excellence in Research

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Mr. Md. Sajeebul Islam Sk. | Natural Language Processing | Excellence in Research

Research Assistant, BRAC University, Bangladesh

Md. Sajeebul Islam Sk. is a passionate researcher in machine intelligence, focusing on creating computational models that enhance our understanding of text, audio, image, and video data. With a solid foundation in Mathematics and core Machine Learning principles, Sajeebul has centered his work on solving intricate challenges in text and audio comprehension. Currently, as a Research Assistant at BRAC University, he continues to refine his skills in Natural Language Processing (NLP) and Computer Vision, embodying a commitment to applying mathematical insights to practical machine learning applications. 🌐📊

Publication Profile

ORCID

Education

Sajeebul holds a Master’s in Computer Science & Engineering from BRAC University, completed in 2023 with a CGPA of 3.83/4.00. His academic journey began with a Bachelor of Science in Mathematics from Khulna University, where he achieved a CGPA of 3.05/4.00. 📚🎓

Experience

Sajeebul is currently serving as a Research Assistant at the Department of Computer Science & Engineering, BRAC University, where he has been since January 2024. In this role, he focuses on advancing research in NLP and Computer Vision, leveraging his expertise in deep learning and machine learning to explore innovative solutions. 🖥️🔬

Research Focus

His research interests lie in the realms of Natural Language Processing, Machine and Deep Learning, and Computer Vision, with a particular emphasis on wavelet analysis techniques. Through his work, Sajeebul aims to expand the frontiers of computational understanding in human-computer interaction. 💡🔍

Awards and Honours

Sajeebul’s academic journey is distinguished by several scholarships and recognitions. He was awarded the BRAC University Thesis Scholarship in May 2023 and multiple Academic Merit Scholarships in 2023 and 2022. In his early years, he achieved the 1st merit position in the Biology Olympiad in Khulna and received government scholarships for academic excellence. 🏆🎖️

Publications (Top Notes)

Unveiling personality traits through Bangla speech using Morlet wavelet transformation and BiG, published in Natural Language Processing Journal, 2024, DOI link, cited by several recent studies on wavelet transformation in NLP applications.

Bangla Speech Personality Traits Data, dataset available on Mendeley Data, 2024, Dataset link, widely accessed by NLP researchers

 

 

Murad Njoum | CyberSecurity | Cybersecurity Achievement Award

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Dr. Murad Njoum | CyberSecurity | Cybersecurity Achievement Award

Lecturer, BirZeit University, Palestine, State of

📘 Murad Subhi Njoum is a dedicated lecturer in the Computer Science Department at Birzeit University, known for his expertise in data structures, Java programming, and cybersecurity. With over a decade of teaching experience, he has developed courses that engage students in programming and foundational computer science concepts. Murad is currently pursuing a Ph.D. in Computer Science at UKM, Malaysia, where he specializes in the field of steganography within cybersecurity, having published several papers that contribute to advancements in data security.

Publication Profile

Google Scholar

Education:

🎓 Murad holds a Master’s degree in Scientific Computing with a focus on Computer Science, graduating with distinction. His academic journey continues as a Ph.D. candidate at Universiti Kebangsaan Malaysia (UKM), Malaysia, where he expands his research on steganography and data security.

Experience:

👨‍🏫 With over ten years of teaching experience, Murad has instructed courses in data structures, Java programming, and cybersecurity, and has provided foundational knowledge in Linux, C programming, and introductory computer science. His role at Birzeit University allows him to contribute to the academic growth of his students while fostering a collaborative learning environment.

Research Focus:

🔍 Murad’s primary research focus lies in steganography within cybersecurity, exploring innovative techniques for enhancing data security. His ongoing research aims to develop new methods that improve the reliability and security of steganographic techniques, contributing to the broader field of secure information technology.

Awards and Honors:

🏆 Throughout his career, Murad has achieved significant recognition in the academic field, notably for his contributions to cybersecurity and education. He continues to strive for excellence in both research and teaching.

Publication Top Notes:

“Steganographic Techniques in Secure Data Transmission,” Journal of Information Security, 2021, focusing on improved data concealment methodologies. Cited by various articles in the field for its technical advancement in data security.

“Applications of Steganography in Cybersecurity,” Cybersecurity Journal, 2022, discussing practical implementations of steganography for enhanced data protection. Recognized widely for its relevance to practical applications in secure data handling.

“Innovations in Data Concealment Using Steganographic Methods,” Security and Data Privacy, 2023, detailing advancements in steganography. Cited frequently for its contributions to modern steganographic applications and data privacy measures.

 

saeedeh shahbazi | Detection | Best Researcher Award

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Ms. saeedeh shahbazi | Detection | Best Researcher Award

researcher, cttc, Spain

👩‍🔬 Saeedeh Shahbazi is a dedicated researcher at the Centre Tecnològic de Telecomunicacions de Catalunya (CTTC), where she specializes in land deformation monitoring. With a strong academic foundation in geophysics and physics, she is also pursuing her PhD at UPC. Saeedeh’s work is driven by innovative approaches to urban area studies using cutting-edge techniques in remote sensing and data analysis.

Publication Profile

ORCID

Education

🎓 Saeedeh holds a Master of Science degree in Geophysics and a Bachelor’s in Physics. Currently, she is furthering her expertise as a PhD candidate at UPC, focusing on geospatial technologies and urban land deformation.

Experience

💼 As a researcher in the Geomatics unit at CTTC, Saeedeh has made significant strides in using Persistent Scatterer Interferometry (PSI) to assess land deformation. She has developed a Python software tool that enables fast, user-friendly post-processing for differential deformation mapping, contributing to urban planning and infrastructure safety.

Research Focus

🔍 Saeedeh’s research revolves around remote sensing and land deformation, particularly focusing on urban areas. Her work with Sentinel-1 data and EGMS products is geared towards detecting building damage risks through detailed deformation analysis. She is committed to improving land monitoring techniques with innovative tools and methodologies.

Awards and Honors

🏆 Saeedeh has not highlighted specific awards, but her ongoing contributions in the RASTOOL project and her automated software tool for deformation analysis stand out as major professional accomplishments.

Publication Top Notes

📄 Constraints on the hydrogeological properties and land subsidence through GNSS and InSAR measurements and well data in Salmas plain, northwest of Urmia Lake, Iran (2021) was published in Hydrogeology Journal and has contributed to subsidence studies. DOI
📄 From EGMS Data to a Differential Deformation Map For Buildings at Continent Level (2024) explores deformation mapping and was published in Procedia Computer Science. DOI
📄 Detection of buildings with potential damage using differential deformation maps (2024), published in ISPRS Journal of Photogrammetry and Remote Sensing, provides insights into building damage detection techniques. DOI
📄 Computing and Sharing the Differential Deformation of the Ground at a Continental Level Using Public EGMS Data (2023) was presented at Environmental Science Proceedings, contributing to large-scale land deformation assessments. DOI
📄 From European Ground Motion Service to Differential Deformation Map for Buildings (2024), published in IGARSS, advances automated building deformation detection techniques. DOI

 

Young-Chan Lee | Generative AI | Excellence in Research

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Prof. Young-Chan Lee | Generative AI | Excellence in Research

Professor, Dongguk University, South Korea

🌟 Dr. Young-Chan Lee is a distinguished professor at Dongguk University, Korea, where he has been serving since 2004. With a rich academic and leadership background, he also holds key roles such as Dean of the Continuing Education Institute and the Institute of Ecology Education. Dr. Lee’s contributions extend globally, including positions at universities in Vietnam and Malaysia. His dedication to information systems and management science has earned him a stellar reputation in both academia and industry.

Publication Profile

ORCID

Education

🎓 Dr. Lee completed his Ph.D. in Management Science from Sogang University in 2003, specializing in data mining, system dynamics, and e-commerce strategy. He also holds an M.A. in Management Science from the same institution, where he concentrated on multi-objective decision-making models, and a B.A. in Business Administration with a focus on finance, econometrics, and management science.

Experience

💼 Over his career, Dr. Lee has taken on leadership roles at Dongguk University, including Dean of the School of Business Administration and Office of International Affairs. He has also worked internationally as an Adjunct Professor at Ton Duc Thang University in Vietnam and as a Senior Researcher at INTI International University in Malaysia. His academic career is complemented by editorial roles in several prestigious journals.

Research Focus

🔬 Dr. Lee’s research interests lie in data mining, machine learning for business analytics, knowledge management, system dynamics, and fintech innovation. He is particularly known for applying systems thinking and multi-criteria decision-making to tackle complex business and management challenges.

Awards and Honours

🏆 Dr. Lee has received numerous accolades, including multiple Best Paper Awards from leading associations such as the Korea Association of Information Systems. His work has also earned recognition on a global scale, including the Most Cited Paper Award from Elsevier and the Top Downloaded Paper Award from Wiley.

Publication Top Notes

Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes Through Service-Dominant Logic and Artificial Intelligence Device Use Acceptance Perspectives

Ethical AI in Financial Inclusion: The Role of Algorithmic Fairness on User Satisfaction and Recommendation

Enhancing Financial Advisory Services with GenAI: Consumer Perceptions and Attitudes through SDL and AIDUA Perspectives

 

 

Jean-Marc LAHEURTE | RFID technologies | Best Researcher Award

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Prof. Jean-Marc LAHEURTE | RFID technologies | Best Researcher Award

Professor, Laboratoire ESYCOM Université Gustave Eiffel, France

Jean-Marc Laheurte is a renowned professor and researcher in the field of electrical engineering, specializing in antennas and RFID technologies. With a long career in academia and industry, he is currently the Director of the ESYCOM Laboratory at the University Gustave Eiffel in France. His work has significantly contributed to the development of RFID technologies and antenna research. He has co-authored several books, over 80 journal papers, and holds two patents related to RFID innovations 📡.

Publication Profile

ORCID

Education 🎓

Jean-Marc Laheurte earned his M.Sc. and Ph.D. degrees in electrical engineering from the University of Nice, France, in 1989 and 1992, respectively. He further pursued the Habilitation à Diriger les Recherches in 1997, solidifying his expertise in advanced research and supervision. His educational path includes time spent as a Research Assistant at École Polytechnique Fédérale de Lausanne and a Post-Doctoral Researcher at the University of Michigan 🌍.

Experience 🏫

From 1993 to 2002, Jean-Marc Laheurte served as an Associate Professor at the University of Nice Sophia Antipolis, followed by a professorship at the University Gustave Eiffel, where he has led the ESYCOM Laboratory since 2014. He also had a stint in the private sector as an RF Senior Engineer at Tagsys, France, in 2011-2012, where he contributed to RFID system developments 📡. His leadership extends to organizing courses across Europe in the European School of Antennas and managing the Antennas Committee at the French Microwave Conference (JNM) for a decade 🏆.

Research Focus 🔬

Jean-Marc Laheurte’s research is focused on advanced antennas, particularly their integration into various materials, RFID technologies, and civil engineering infrastructure monitoring. His work extends into RFID localization and the electromagnetic characterization of materials, with applications ranging from logistics to healthcare. He is at the forefront of exploring antennas in lossy materials such as human bodies and construction materials 🚧.

Awards and Honors 🏅

Jean-Marc Laheurte has received recognition for his contributions to electrical engineering, particularly in antenna and RFID technology research. His leadership of the ESYCOM Laboratory and involvement in organizing key antenna and microwave conferences in Europe highlights his influence in the field. His patents on RFID technologies also emphasize his role as an innovator 📜.

Publications Top Notes 📚

“Comparison of UHF RFID Loop Matching Antennas Based on Various Substrate-Metal Material Combinations,” IEEE Transactions on Antennas and Propagation, cited by 55 articles (2017).

“Power Optimized Waveforms for Wireless Power Transmission,” Journal of Electromagnetic Waves and Applications, cited by 35 articles (2019).