Rania Hamdani | Computer science | Best Researcher Award

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Mrs. Rania Hamdani | Computer science | Best Researcher Award

Mrs. Rania Hamdani, University of Luxembourg, Luxembourg

Rania Hamdani is a research scientist specializing in operational research, data management, and cloud architecture for Industry 5.0. Based in Luxembourg, she is currently affiliated with the University of Luxembourg, where she explores advanced methodologies for integrating and managing heterogeneous data sources. She holds an engineering degree in Software Engineering and has extensive experience in software development, AI, and DevOps. Rania has worked on multiple industry and academic projects, publishing three research papers in Ontology-Driven Knowledge Management and Cloud-Edge AI. With a strong background in programming, cloud computing, and AI-driven solutions, she has contributed to platforms ranging from job recommendation systems to adaptive human-computer interaction systems. Her expertise includes Python, SpringBoot, Kubernetes, and Azure DevOps. She is also an active member of IEEE and other technical organizations, promoting innovation and knowledge-sharing in AI and cloud technologies. 🌍💻🔬

Publication Profile

Orcid

🎓 Education

Rania Hamdani holds an Engineering Degree in Software Engineering from the National Higher School of Engineers of Tunis (2021–2024), where she specialized in advanced design, service-oriented architecture, object-oriented programming, database management, and operational research. Prior to this, she completed a two-year preparatory cycle at the Preparatory Institute for Engineering Studies of Tunis (2019–2021), undertaking intensive coursework in mathematics, physics, and technology to prepare for engineering studies. She also earned a Mathematics-specialized Baccalaureate from Pioneer High School Bourguiba Tunis (2015–2019), graduating with honors. Throughout her academic journey, she gained expertise in artificial intelligence, machine learning, cloud computing, and DevOps methodologies. Her education provided a solid foundation in programming languages, data processing techniques, and full-stack development. Additionally, she holds multiple Microsoft certifications in Azure fundamentals, AI, data security, and compliance, reinforcing her expertise in cloud-based solutions and AI-driven applications. 📚🎓💡

💼 Experience

Rania Hamdani is a research scientist at the University of Luxembourg, where she focuses on integrating and managing heterogeneous data sources for cloud-based decision-making. Previously, she was a research intern at the same institution, contributing to Ontology-Driven Knowledge Management and Cloud-Edge AI, with three published papers. She also worked as a part-time software engineer at CareerBoosts in Quebec (2021–2025), specializing in Python, Azure DevOps, Docker, and test automation. She gained industry experience through internships at Qodexia (Paris), Sagemcom (Tunisia), and Tunisie Telecom, working on smart recruitment platforms, employee management systems, and server monitoring solutions using SpringBoot, Angular, and PostgreSQL. Her technical expertise spans full-stack development, DevOps, AI-driven applications, and cloud computing. She has contributed to major projects, including an adaptive human-computer interaction system, a job recommendation system, and a problem-solving platform, demonstrating her versatility in research and software engineering. 🚀🖥️🔍

🏆 Awards & Honors

Rania Hamdani has been recognized for her outstanding contributions to AI-driven cloud computing and operational research. She received excellence awards during her engineering studies at the National Higher School of Engineers of Tunis and was among the top-performing students in her Mathematics-specialized Baccalaureate. Her research papers in Ontology-Driven Knowledge Management and Cloud-Edge AI have been acknowledged in academic circles, contributing to the advancement of Industry 5.0 technologies. She has also earned multiple Microsoft certifications in cloud and AI fundamentals, reinforcing her technical expertise. As an active member of IEEE and the Youth and Science Association, she has been involved in technology outreach and innovation-driven initiatives. Her leadership in ENSIT Junior Enterprise as a project manager further showcases her ability to lead and contribute to tech communities. These recognitions highlight her dedication to research, software development, and cloud-based AI applications. 🏅📜🌟

🔬 Research Focus

Rania Hamdani’s research focuses on operational research, data management, cloud-edge AI, and Industry 5.0 applications. She specializes in ontology-driven knowledge management, exploring methodologies for integrating heterogeneous data sources to optimize cloud-based decision-making processes. Her work includes artificial intelligence, machine learning, reinforcement learning, and human-computer interaction systems. She has contributed to projects involving job recommendation systems, adaptive human-computer interaction platforms, and cloud-based problem-solving platforms. Rania is particularly interested in scalable cloud architectures, leveraging technologies like FastAPI, Kubernetes, Docker, and Azure DevOps to build efficient AI-powered solutions. Her research also integrates graph databases, Apache Airflow, and big data analytics for enhanced data processing. By combining AI and cloud computing, she aims to develop innovative, data-driven solutions for automation, decision support, and optimization in various industrial applications. Her expertise bridges the gap between theoretical research and real-world software engineering. ☁️🤖📊

 

Publication Top Notes

Adaptive human-computer interaction for industry 5.0: A novel concept, with comprehensive review and empirical validation

 

John Mutinda | Deep learning | Best Researcher Award

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Mr. John Mutinda | Deep learning | Best Researcher Award

Mr. John Mutinda, USTC china, China

John Kamwele Mutinda is a passionate researcher currently pursuing an MSc in Machine Intelligence at the African Institute for Mathematical Sciences in Senegal. He holds a previous MSc in Mathematical Sciences from AIMS Rwanda and a BSc in Statistics from South Eastern Kenya University, where he graduated with First Class Honours. His research interests include statistical modeling, data science, and machine learning. John has significant teaching experience, having mentored high school students in mathematics and science. He has received several scholarships and awards, including the African Master’s in Machine Intelligence Scholarship. 🌍📊💻

Publication profile

Google Scholar


Education Background

Mr. John Kamwele Mutinda is currently pursuing his MSc in Machine Intelligence at the African Institute for Mathematical Sciences in Senegal (2022-2023). He previously earned an MSc in Mathematical Sciences from AIMS Rwanda, achieving an impressive cumulative GPA of 84.5/100 (Very Good Pass). John completed his BSc in Statistics at South Eastern Kenya University, graduating with First Class Honours and a GPA of 75.78/100. He also excelled in his Kenya Certificate of Secondary Education (KCSE) at Katwanyaa High School, obtaining a GPA of 67/84 (B+). 🎓📚🌍

 

Research Experience

Mr. John Kamwele Mutinda has actively contributed to significant research projects. In 2022, he modeled the impact of meteorological and air pollution parameters on COVID-19 transmission in the Western Cape Province of South Africa. He also applied Principal Component Analysis (PCA) within the health sector that same year. In 2020, John focused on modeling the human population growth rate in Kitui County, Kenya. His earlier work in 2019 involved time series modeling of infant child mortality rates in Kitui County. These experiences highlight his strong analytical skills and commitment to impactful research. 📊🌍📈

 

Teaching and Mentoring Experience

John Kamwele Mutinda has an extensive background in teaching and mentoring. In 2021, he provided tutorial services in Mathematics, Physics, and Chemistry at Katwanyaa High School, helping high school students excel academically. The previous year, he supported students in Mathematics, Agriculture, and Chemistry. His mentoring journey began in 2019, guiding students in Mathematics and Chemistry. In 2018, he taught Mathematics at Katwanyaa High School, and in 2017, he mentored students in Mathematics, Physics, and Agriculture. His commitment to education started as early as 2016 when he tutored Mathematics and Physics at Itheuni Secondary School. 📚👨‍🏫✨

 

Work Experience

John Kamwele Mutinda has diverse work experience in education and electoral roles. In 2021, he served as an Assistant Teacher and Departmental Assistant at Katwanyaa High School, where he was responsible for teaching, setting, supervising, and marking exams. He also acted as the Deputy Presiding Officer for the Independent Electoral and Boundaries Commission during the Machakos County senatorial elections. In 2019, he worked as an Enumeration Officer for the Kenya National Bureau of Statistics, conducting household and establishment surveys. Previously, in 2017, he was a Polling Clerk, responsible for verifying voters and counting votes during the general elections. In 2016, he was a Board of Management Teacher at Itheuni Secondary School, performing similar teaching duties. 📚🗳️👨‍🏫

 

Awards, Honours & Certificates

John Kamwele Mutinda has received numerous accolades for his academic and professional achievements. In 2023, he was awarded the prestigious African Master’s in Machine Intelligence Scholarship, funded by Facebook and Google, at the African Institute for Mathematical Sciences in Senegal. He also received the Next Einstein Initiative Master’s Scholarship Award in 2021. His educational accomplishments include a Certificate of Completion in Business Management from ESMT Germany and multiple Certificates of Merit in R, STATA, and SPSS from KESAP Research Centre. He has participated in various Mathematics Olympiads, earning certificates for his outstanding performance. 🎓🏆📜

 

Publication Top Notes

  • Covid-19 impact analysis: assessing African sectors-commodity, service, manufacturing, and education using mixed model approach – Cited by 1, 2023 🦠📊
  • African Institute for Mathematical Sciences (AIMS), Rwanda – Cited by 1, 2023 🇷🇼
  • Stock price prediction using combined GARCH-AI models – Cited by 0, 2024 📈🤖
  • Enhancing Obesity Detection Through SMOTE-based Classification Models: A comparative Study – Cited by 0, 2024 🏋️‍♂️🔍
  • Rainfall Pattern in Kenya: Bayesian Non-parametric Model Based on the Normalized Generalized Gamma Process – Cited by 0, 2024 🌧️📉
  • Capital Asset Pricing Model: A Renewed Application on S&P 500 Index – Cited by 0, 2024 💹📈
  • Spatial Regression Modeling of Child Survival on the Distribution of Births and Deaths in Kenya Based on the Kenya Demographic and Health Survey (KDHS) 2022 – Cited by 0, 2024 👶🌍
  • Exploring the Role of Dimensionality Reduction in Enhancing Machine Learning Algorithm Performance – Cited by 0, 2024 ⚙️📉
  • Modeling the Impact of Air Pollution and Meteorological Variables on COVID‐19 Transmission in Western Cape, South Africa – Cited by 0, 2024 🌫️🦠

 

Chao-Ming Wang | Computer Vision | Best Researcher Award

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Prof Dr. Chao-Ming Wang | Computer Vision | Best Researcher Award

Professor, National Yunlin University of Science and Technology, Taiwan

Chao-Ming Wang is a distinguished Professor at the Department of Digital Media Design at National Yunlin University of Science and Technology (YunTech) in Yunlin County, Taiwan. With a rich background in computer science and engineering, Dr. Wang has been a pivotal figure in advancing the fields of signal processing, computer vision, tech art, and interactive multimedia design. His career spans several prestigious institutions, reflecting his commitment to both research and education. 🌟

Publication Profile

Strengths for the Award:

  1. Extensive Experience and Expertise: Dr. Chao-Ming Wang has a distinguished academic and professional background in computer science and information engineering, with degrees from National Chiao Tung University and a career spanning over four decades. His long-term commitment and extensive experience in his field are significant assets.
  2. Leadership and Contributions: His roles as the Head of the Department of Digital Media Design and Director of the Design-led Innovation Center at National Yunlin University of Science and Technology highlight his leadership and ability to influence academic and research directions. His presidency at the Taiwan Society of Basic Design and Art further showcases his impact on the broader research community.
  3. Research Focus: Dr. Wang’s research interests in signal processing, computer vision, tech art, and interactive multimedia design align with cutting-edge technologies and applications. His work in healthcare design applications is particularly relevant, given the increasing focus on integrating technology with healthcare.
  4. Professional Recognition: His long tenure as a senior specialist and faculty member at reputable institutions demonstrates his respected standing in the academic community. His ongoing involvement in significant research areas suggests a sustained impact and relevance in his field.

Areas for Improvement:

  1. Recent Research Output: While Dr. Wang has a notable background, recent updates on his research output or significant publications could provide a clearer picture of his current contributions. Ensuring visibility through recent high-impact publications or citations might enhance his candidacy.
  2. Broader Research Impact: Expanding the scope of his research to include more interdisciplinary collaborations or applications in emerging fields could strengthen his position. Highlighting any groundbreaking projects or innovations developed under his leadership would be beneficial.
  3. Visibility and Outreach: Increasing his presence in international conferences, journals, and collaborative research projects could amplify his contributions. Engaging more actively with global research communities and platforms may enhance his visibility.

Conclusion:

Dr. Chao-Ming Wang is a strong candidate for the Research for Best Researcher Award due to his extensive experience, leadership roles, and relevant research interests in computer vision, tech art, and interactive multimedia design. His contributions to the field, particularly in healthcare design, underscore his impact. Addressing areas for improvement, such as recent research output and broader visibility, could further bolster his candidacy. Overall, his distinguished career and ongoing research make him a noteworthy contender for this award.

 

Education

Dr. Wang earned his B.Sc. (1980), M.Sc. (1982), and Ph.D. (1993) degrees in Computer Science and Information Engineering from National Chiao Tung University, Hsinchu, Taiwan. His academic journey laid a solid foundation for his extensive contributions to the field. 🎓

Experience

From 1982 to 2003, Dr. Wang served as a senior specialist at the National Chung Shan Institute of Science and Technology. He then joined Yuan Ze University as a faculty member from 2003 to 2008. In 2008, he moved to YunTech, where he held leadership roles, including Head of the Department of Digital Media Design (2010-2013) and Director of the Design-led Innovation Center (2016-2017). He also served as President of the Taiwan Society of Basic Design and Art from 2010 to 2013. 🏛️

Research Focus

Dr. Wang’s research interests are diverse and include signal processing, computer vision, tech art, and interactive multimedia design. His work aims to integrate technological advancements with creative applications, particularly in healthcare design. 🔬💻

Awards

Dr. Wang’s contributions to the field have been recognized with various awards and honors throughout his career. His innovative research and leadership in academia have established him as a leading figure in his areas of expertise. 🏆

Publications

 

Jiasheng Ni | Intelligent perception technology | Best Researcher Award

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Prof. Jiasheng Ni | Intelligent perception technology | Best Researcher Award

Prof. Jiasheng Ni, the Faculty of Optoelectronics, Qilu University of Technology, China

Prof. Jiasheng Ni, a renowned expert in optoelectronics, holds a Ph.D. and serves as Executive Deputy Director at Qilu University of Technology. With a prolific career spanning prestigious roles globally, including Senior Visiting Scholar in Australia, Ni’s research focuses on intelligent detection, laser, and fiber optic sensing technologies. With over a dozen projects led and numerous publications, Ni’s contributions in optics earned him awards like Shandong Provincial Science and Technology Progress Award. His expertise encompasses areas like intelligent optoelectronic detection, high-performance lasers, and secure IoT. Ni’s journey reflects dedication and excellence in advancing optical sciences. 🌟🔬👨‍💼

 

Publication Profile

scopus

Education

Ni’s academic journey includes enriching experiences at prestigious institutions worldwide, including the University of New South Wales and Tianjin University, culminating in a Ph.D. in Optical Engineering. His academic pursuits are complemented by hands-on industry experience, reflecting a holistic approach to knowledge dissemination and application. Ni’s educational background underscores his dedication to bridging the gap between academia and industry, shaping the next generation of optoelectronic innovators. 🌐🔍

 

Research Focus

Prof. Jiasheng Ni’s research focus encompasses a wide array of cutting-edge topics in the field of optoelectronics. He specializes in intelligent optoelectronic detection technology, high-performance lasers, and fiber-optic sensing innovations, including secure IoT applications. Ni’s expertise extends to areas such as fiber-optic well logging, seismic detectors, marine sensing, and perimeter security technology. With a keen interest in advancing optical sciences, his contributions have led to significant breakthroughs in distributed fiber optic acoustic sensing systems and high-resolution temperature sensors. Ni’s dedication to pioneering research is reflected in his extensive publication record and leadership roles in professional societies. 🌐🔬🚀

 

Publication Top Notes

  1. “Distributed fiber optic acoustic sensing system intrusion full event recognition based on 1-D MFEWnet” by Dong, L., Zhao, W., Huang, S., Jia, Z., Ni, J. (2024) 🌐
    • Cited by: 0
  2. “High Spatial-Resolved φ-OTDR System Based on Differential Pulse Width Sequence Technique” by Wang, M., Qu, J., Qu, S., Shang, Y., Ni, J. (2024) 🌐
    • Cited by: 0
  3. “Study on the mechanism of fiber-optic hot-wire sensing based on DFB-FL thermally induced chirp effect” by Zhuang, Y., Zhang, X., Hong, Y., Ni, J., Song, Z. (2024) 🌐
    • Cited by: 0
  4. “Research progress of crystalline Raman yellow lasers” by Jiang, P., Ding, X., Guo, J., Ni, J., Yao, J. (2024) 🌐
    • Cited by: 1
  5. “An intelligent crash recognition method based on 1DResNet-SVM with distributed vibration sensors” by Yi, J., Shang, Y., Wang, C., Zhao, Y., Ni, J. (2023) 🌐
    • Cited by: 3
  6. “Intrusive and non-intrusive microflow measurement based on distributed optical fiber acoustic sensing” by Du, Y., Shang, Y., Wang, C., Zhao, Y., Ni, J. (2023) 🌐
    • Cited by: 1