Dr. Annarosa Scalcione | Machine Learning | Research Excellence Award

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Dr. Annarosa Scalcione | Machine Learning | Research Excellence Award 

Dr. Annarosa Scalcione | Machine Learning | Polytechnic University of Turin | Italy

Dr. Annarosa Scalcione is a female biomedical engineer with a strong interdisciplinary background in biomedical instrumentation, sensor-based health monitoring, medical imaging, and digital healthcare solutions, combining engineering rigor with clinical relevance. She completed advanced academic training in biomedical engineering at Politecnico di Torino, with specialization in biomedical instrumentation and sensor systems, supported by foundational education in biomedical engineering from the same institution, where her academic work focused on sustainable biomaterials and applied medical technologies. Her professional experience includes roles as a Junior Application Consultant contributing to the digitalization of hospital clinical and administrative processes, operating room specialist engagement within medical institutions, and academic teaching collaboration supporting undergraduate engineering education. Dr. Annarosa Scalcione has led and contributed to multiple applied and experimental research projects, including the design of a web-based neonatal monitoring platform integrating sensor-derived growth data, dynamic visualization, personalized alerts aligned with international health standards, and telemedicine functionalities. Her research portfolio also includes experimental biomechanics studies using mobile sensors to evaluate neuromuscular performance, automated classification of spinal lesions from medical imaging using machine learning and radiomics, and advanced image segmentation methodologies applied to neurological datasets.

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Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | Research Excellence Award

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Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | Research Excellence Award 

Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | University of Oradea | Romania

Prof. Dr. Cornelia Aurora Gyorod is a senior academic and internationally recognized researcher in Computer Science and Information Technology, specializing in database systems, data mining, expert systems, and large-scale data-driven computing architectures that underpin modern intelligent and sensing-based systems. She holds a Ph.D. in Computer Science from the University of Oradea and currently serves as a Professor in the Faculty of Electrical Engineering and Information Technology, Department of Computers and Information Technology, where she has demonstrated long-standing excellence in teaching, research, and academic leadership. Her educational background is complemented by advanced professional certifications in project management, project evaluation, and enterprise database technologies, reflecting her strong methodological and organizational competence. Her professional experience spans progressive academic roles including junior assistant, assistant professor, lecturer, associate professor, and full professor, during which she has been responsible for delivering core and advanced courses such as Databases, Expert Systems, Computer Programming, Advanced Database Systems, and Data Warehousing, alongside supervising undergraduate, master’s, and doctoral research. Her strengths for this award include a strong international research profile, with 70+ peer-reviewed publications, primarily indexed in Scopus and IEEE-affiliated venues, accumulating 800+ citations and an established Scopus Author ID and ORCID record.

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Featured Publications

Assist. Prof. Dr. Ali Alfayly | Machine Learning | Best Researcher Award

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Assist. Prof. Dr. Ali Alfayly | Machine Learning | Best Researcher Award 

Assist. Prof. Dr. Ali Alfayly | Machine Learning | Public Authority of Applied Education and Training | Kuwait

Assist. Prof. Dr. Ali Hussain Alfayly, SMIEEE, is a highly accomplished Kuwaiti academic and researcher serving as an Assistant Professor in the Department of Computer Science at the College of Basic Education, Public Authority for Applied Education and Training (PAAET), Kuwait, where he has established himself as a prominent contributor to the fields of computer science, artificial intelligence, cybersecurity, robotics, and educational technologies. He earned his Ph.D. in Computer Science from the University of Plymouth in the United Kingdom, building on his earlier M.Sc. in Advanced Computer Science from the University of Manchester, an M.Sc. in Computer and Network Technology, and a B.Sc. in Computer and Network Technology, both from Northumbria University. His professional career includes serving as Lecturer and Lab Demonstrator at the University of Plymouth in the United Kingdom and as a Network Engineer at Kuwait International Bank, experiences that equipped him with both academic and industry perspectives. Dr. Ali Hussain Alfayly’s research interests encompass Explainable Artificial Intelligence, Machine Learning, UAV systems, cybersecurity and network management, robotics, intelligent systems, and educational technology, reflecting a multidisciplinary approach aimed at solving real-world challenges.

Professional Profile: ORCID | Scopus

Selected Publications

  1. Detection of Fault Events in Software Tools Integrated with Human–Computer Interface Using Machine Learning, 2025 – Citations: 5

  2. Citizens’ Satisfaction Factors in E-Government Services: An Empirical Study from Kuwait, 2024 – Citations: 8

  3. Extended Technology Acceptance Model for Multimedia-Based Learning in Higher Education, 2022 – Citations: 12

  4. Challenges of Applying Semantic Web Approaches on E-Government Web Services: Survey, 2021 – Citations: 15

Aurélie Cools | Deep Neural Networks | Best Researcher Award

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Aurélie Cools | Deep Neural Networks | Best Researcher Award

Ms. Aurélie Cools, University of Mons, Belgium.

Aurélie Cools is a Ph.D. candidate in Engineering Sciences at the University of Mons (UMons), specializing in deep neural networks and dimensionality reduction for CBIR search engines. She holds dual Master’s degrees: Civil Engineering in Computer Science and Management (Summa Cum Laude) and Management Engineering (Magna Cum Laude), showcasing her expertise in software engineering, business analytics, and optimization. Alongside her research, she contributes as a teaching assistant at UMons. With a strong foundation in Python, SQL, and PyTorch, Aurélie is multilingual and adept at problem-solving, team management, and communication. 🌟👩‍💻📚

Publication Profile

Orcid

Education and Experience

Education 📘

  • Ph.D. in Engineering Sciences
    • Institution: University of Mons (UMons), Polytechnic Faculty
    • Thesis Topic: CBIR search engine with deep neural networks and dimensionality reduction methods
    • Duration: 2021 – Present
  • Master’s in Civil Engineering (Summa Cum Laude)
    • Institution: UMons, Polytechnic Faculty
    • Specialization: Software Engineering and Business Intelligence
    • Duration: 2018 – 2021
  • Master’s in Management Engineering (Magna Cum Laude)
    • Institution: UCL Mons
    • Specialization: Business Analytics – Logistics and Transportation
    • Duration: 2015 – 2017
  • Bachelor’s in Management Engineering (Cum Laude)
    • Institution: UCL Mons
    • Duration: 2012 – 2015

Experience 💼

  • Teaching Assistant & Ph.D. Student
    • Institution: UMons
    • Duration: September 2021 – Present
  • Credit Analyst
    • Institution: CPH Bank, La Louvière
    • Duration: July 2017 – August 2021
  • Student Worker
    • Institution: Colruyt Group, Mons
    • Duration: March 2013 – December 2016

Suitability For The Award

Ms. Aurélie Cools is an outstanding candidate for the Best Researcher Award, combining academic excellence with impactful research. Currently pursuing a Ph.D. in Engineering Sciences at the University of Mons, her work on CBIR systems using deep neural networks and dimensionality reduction demonstrates innovation and technical expertise. With dual Master’s degrees in Civil and Management Engineering earned with high honors, Aurélie excels in both research and practical applications. Her proficiency in programming, data analysis, and problem-solving, coupled with strong communication skills, makes her a deserving nominee.

Professional Development

Aurélie excels in the realms of engineering and management, leveraging cutting-edge techniques like deep neural networks and dimensionality reduction. 📊💡 Her research bridges technical and analytical fields, emphasizing CBIR technologies for efficient image retrieval. With years of experience as a teaching assistant, she fosters innovation and critical thinking among students. Aurélie’s blend of programming skills in Python, SQL, and PyTorch, coupled with proficiency in tools like MongoDB and Excel, enhances her adaptability in diverse challenges. A polyglot and skilled communicator, she thrives in team management, problem-solving, and delivering impactful solutions. 🚀🌍✨

Research Focus

Aurélie’s research focuses on developing advanced Content-Based Image Retrieval (CBIR) systems, leveraging deep neural networks and cutting-edge dimensionality reduction techniques to enhance image search and analysis efficiency. Her interdisciplinary approach combines software engineering, artificial intelligence, and data science for innovative solutions. 🖼️🤖📊 With a keen interest in the practical applications of CBIR, such as medical imaging or multimedia management, Aurélie contributes to expanding the potential of machine learning in real-world scenarios. Her expertise lies at the intersection of engineering precision and computational intelligence, making her a significant contributor to AI-driven image processing. 🌟🔍📈

Publication Top Notes

  • A New Comparative Study of Dimensionality Reduction Methods in Large-Scale Image Retrieval (2022) 📚 | Published: 2022-05-13
  • A Comparative Study of Reduction Methods Applied on a Convolutional Neural Network (2022) 📖 | 🗓️ Published: 2022-04-28