Dr. Annarosa Scalcione | Machine Learning | Research Excellence Award

Posted on 06/01/2026 by Global Sensor Awards

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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Featured Publication

An End-to-End Radiomic Framework for Automatic Vertebral Lesion Classification and 3D Visualization

– Eng, 2026

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

Posted on 16/09/2025 by Global Sensor Awards

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

Detection of Fault Events in Software Tools Integrated with Human–Computer Interface Using Machine Learning, 2025 – Citations: 5
Citizens’ Satisfaction Factors in E-Government Services: An Empirical Study from Kuwait, 2024 – Citations: 8
Extended Technology Acceptance Model for Multimedia-Based Learning in Higher Education, 2022 – Citations: 12
Challenges of Applying Semantic Web Approaches on E-Government Web Services: Survey, 2021 – Citations: 15

Ms. Rachel Stephen Mollel | Machine Learning Awards | Best Scholar Award

Posted on 15/11/2024 by Global Sensor Awards

Ms. Rachel Stephen Mollel | Machine Learning Awards | Best Scholar Award

Ms. Rachel Stephen Mollel, University of Strathclyde, United Kingdom

Rachel Stephen Mollel is a Ph.D. student in Electrical and Electronic Engineering at the University of Strathclyde, UK. Her research focuses on machine learning, explainable AI, energy demand-side management, smart metering, and non-intrusive load monitoring (NILM). She holds a Master of Engineering from Arkansas Tech University, USA, and a Bachelor’s degree in Telecommunication Engineering from Visvesvaraya Technological University, India. Rachel has contributed significantly to the energy sector, exploring the role of smart meters in reducing energy costs and enhancing communication between energy providers and consumers. Her recent work, which investigates the potential of NILM to reveal hidden demand flexibility in residential energy consumption, has been published in various peer-reviewed journals and conferences. Additionally, she is actively involved in improving the interpretability of NILM models to enhance algorithm performance. Her contributions have been recognized with a Commonwealth Scholarship in 2020.

Professional Profile:

ORCID

Summary of Suitability for the Best Scholar Award:

Rachel Stephen Mollel is a highly suitable candidate for the Best Research Scholar Award based on her significant contributions to the fields of machine learning, explainable AI, and energy demand-side management. As a PhD student at the University of Strathclyde, her research aims to address critical energy issues through innovative approaches like Non-Intrusive Load Monitoring (NILM), which helps uncover hidden demand flexibility in residential energy consumption.

Education:

2021 – Present: PhD in Electrical and Electronic Engineering, University of Strathclyde, UK
2010 – 2012: Master of Engineering, Arkansas Tech University, USA (GPA: 3.75/4.0)
2006 – 2010: Bachelor’s degree in Telecommunication Engineering, Visvesvaraya Technological University, India (First Class)

Work Experience:

2011 – 2012: Graduate Assistant, Arkansas Tech University, USA
Assisted in the Digital Logic and Robotics Course & Lab; delivered tutorials, graded lab reports and exams, and supported the development of course materials under faculty supervision.
2014 – 2020: Assistant Lecturer, University of Dar es Salaam, Tanzania
Delivered lectures, prepared and graded exams in Control Systems Engineering and Fundamentals of Electrical Engineering. Supervised undergraduate student projects, practical training, and fieldwork. Managed various administrative duties, such as student registration and coordination of departmental examinations.