Ester Gilart Cantizano | AI in Healthcare | Best Researcher Award

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Prof. Dr. Ester Gilart Cantizano | AI in Healthcare | Best Researcher Award

Department of Nursing and Physiotherapy, University of Cadiz, Spain

Ester Gilart Cantizano is a dedicated academic and healthcare researcher whose work bridges innovative nursing education and applied clinical research. With a strong background in nursing sciences, she has developed a robust academic profile integrating research, teaching, and international collaboration. Her scholarly output reflects a commitment to advancing nursing knowledge and contributing to the mental health and professional well-being of healthcare providers. Ester’s active participation in international congresses and scientific publications has positioned her as a significant contributor to evidence-based nursing education and practice.

Profile

Scopus

Education

Ester began her academic journey with a Bachelor’s degree in Nursing in 2016, followed by a Master’s in Nursing Research and Advanced Professional Practice in 2018. She later earned two postgraduate expert qualifications—one in Surgical Anesthesiology for Nurses (2019) and another in Gynecological Nursing Care (2020). Currently, she is completing a PhD in Health Sciences, with a dissertation focused on the post-COVID-19 emotional impacts on nursing professionals, including the development and validation of a professional traumatic grief inventory. Her academic training is supplemented by more than 50 specialized courses that reflect her commitment to continuous education.

Experience

Professionally, Ester has cultivated a multifaceted career combining clinical practice, teaching, and research. Her clinical experience in both public and private hospitals has enriched her teaching approach, allowing her to merge practical skills with theoretical instruction. At the University of Cádiz, she has taught over 600 hours across subjects such as pharmacology, community nursing, occupational health, and bioethics. Her commitment to academic excellence extends to coordinating and evaluating undergraduate theses, conducting specialized training sessions, and implementing active learning strategies in university classrooms. She also served as a mentor for practicum courses and developed evaluation rubrics to assess communication skills.

Research Interest

Ester’s primary research interests include mental health in healthcare professionals, professional grief, nursing education methodologies, and diagnostic label validation. She is a key member of the research group “Present, Past, and Future of Nursing: Innovation, Teaching, and Development” at the University of Cádiz. Her research focuses on designing psychometric instruments and exploring psychological stressors such as unemployment syndrome and grief among nurses. Her current doctoral research investigates the psychological effects of COVID-19 on nurses, aiming to create tools that enhance mental well-being and workplace support structures.

Award

Her contributions to nursing education and mental health research have earned her national and international recognition. She has presented findings at over 20 scientific congresses, including the prestigious Sociedade Espanhola de Epidemiología and Associação Portuguesa de Epidemiologia. She also undertook a notable research stay at the University of Naples in 2024, where she studied the impact of the COVID-19 pandemic on hospital staff’s mental health. This international collaboration enriched her doctoral work and expanded her methodological toolkit for assessing psychological resilience and trauma.

Publication

  1. Healthcare, 2023 – “Identifying Hate Speech and Attribution of Responsibility” – cited by 2 articles.

  2. International Journal of Environmental Research and Public Health, 2022 – “Bereavement Needs Assessment in Nurses” – cited by 5 articles.

  3. International Journal of Nursing Knowledge, 2021 – “Psychometric Properties of Unemployment Syndrome Scale” – cited by 1 article.

  4. International Journal of Environmental Research and Public Health, 2021 – “Unemployment Syndrome During COVID-19” – cited by 9 articles.

  5. International Journal of Nursing Knowledge, 2019 – “Development of a Scale to Measure Unemployment Syndrome” – cited by 2 articles.

  6. Healthcare, 2021 – “When Nurses Become Patients” – cited by 8 articles.

  7. Nursing Reports, 2024 – “Predictive Model for Resilience in Family Caregivers” – recent publication, citations pending.

Conclusion

Ester Gilart Cantizano embodies the synthesis of practice, pedagogy, and research in modern nursing. Her academic journey, rich with advanced degrees and specialized training, reflects her drive to improve healthcare delivery and professional resilience. Through validated psychometric tools and innovative teaching methods, she has significantly influenced both her students and the broader healthcare community. Her leadership in traumatic grief research and her ongoing efforts in international collaboration highlight her as a prominent figure in the evolution of nursing science.

Lahcen Tamym | AI in Healthcare | Best Researcher Award

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Assoc. Prof. Dr. Lahcen Tamym | AI in Healthcare | Best Researcher Award

Associate Professor at Jean Monnet University, France

Lahcen Tamym is a dynamic academic professional and researcher in the field of computer science, currently serving as an Assistant Professor in Industrial Engineering and Healthcare Systems Engineering at Jean Monnet University, Saint-Étienne, within the LASPI Laboratory. His academic and research journey is rooted in Big Data and Data Science, with a particular focus on sustainable, resilient, and intelligent networked enterprises. With a passion for innovation at the intersection of emerging technologies and socio-environmental goals, Dr. Tamym has developed advanced frameworks for optimizing supply chains, improving life cycle sustainability, and enhancing decision-making using Big Data Analytics (BDA), Machine Learning (ML), Internet of Things (IoT), and Blockchain technologies. His multidisciplinary work continues to advance smart industrial systems aligned with the Sustainable Development Goals (SDGs).

Profile

Scopus

Education

Lahcen Tamym began his academic path with a Bachelor’s degree in Mathematical and Computer Sciences from Ibn Zohr University in Morocco, where he developed optimization models using CPLEX and MINOS. He then pursued a Master’s degree in Intelligent and Decision Support Systems at Sidi Mohamed Ben Abdellah University, where his work focused on deep learning for graph representation. He earned his Ph.D. in Computer Science from Aix-Marseille University, France, and Université Moulay Ismail, Morocco. His doctoral research specialized in Big Data Analytics for managing flexible, robust, and sustainable networked enterprises. The study emphasized machine learning, predictive analytics, and optimization in supply chains and sustainable value creation, forming the foundation for his continuing contributions to sustainable industrial development.

Experience

Dr. Tamym’s professional trajectory includes teaching and research across several institutions in France and Morocco. Before his current faculty position at Jean Monnet University, he served as a Temporary Teaching and Research Assistant (ATER) at Aix-Marseille University. During this time, he was involved in both instructional duties and cutting-edge research in computer science and interaction. His earlier involvement in collaborative research at Laboratoire d’Informatique et Systèmes (LIS) in France and Laboratoire d’Informatique et Applications (IA) in Morocco provided him with diverse academic exposure and the opportunity to build multidisciplinary solutions addressing real-world challenges in industrial and healthcare domains.

Research Interest

Dr. Tamym’s research revolves around the application of advanced data-driven methods to enhance sustainability, flexibility, and resilience in networked enterprises. His areas of interest include Big Data Analytics, IoT, Blockchain, Machine Learning, and Decision Support Systems. He is particularly focused on sustainable supply chain management, life-cycle assessment, risk analysis, and social sustainability evaluation. He has also explored blockchain-based security models for IoT, financial fraud detection systems using deep learning, and natural language processing in educational and healthcare systems. By integrating these technologies, he aims to create intelligent, transparent, and adaptive networks capable of responding to dynamic global and industrial demands.

Award

Although specific awards are not listed, Dr. Tamym’s consistent involvement in prestigious conferences and publication in reputable journals underlines his recognition within the academic community. His work has been well-received at international forums such as the International Conference on Ambient Systems, Networks and Technologies, and IFAC conferences, reflecting the impact and value of his contributions. His research aligns with global agendas for sustainable industry and digital transformation, enhancing his profile as a leading researcher in his domain.

Publication

Dr. Tamym has published widely in top-tier journals and conferences. Notable publications include:

  1. Big Data Analytics-based life cycle sustainability assessment for sustainable manufacturing enterprises evaluation, Journal of Big Data (2023), cited for contributions to sustainable manufacturing assessment.

  2. Big data analytics-based approach for robust, flexible and sustainable collaborative networked enterprises, Advanced Engineering Informatics (2023), cited for its novel integration of resilience in supply chains.

  3. A big data based architecture for collaborative networks: Supply chains mixed-network, Computer Communications (2021), contributing to architecture modeling for collaborative systems.

  4. A Big Data Analytics-Based Methodology For Social Sustainability Impacts Evaluation, Procedia Computer Science (2023), a case-based analysis on social sustainability metrics.

  5. How Can Big Data Analytics and Artificial Intelligence Improve Networked Enterprises’s Sustainability?, IEEE ACDSA Conference (2024), exploring AI’s role in sustainable enterprise development.

  6. Distributed Deep Learning-Based Model for Financial Fraud Detection in Supply Chain Networks, ICICT 2024, addressing cybersecurity challenges in digital supply chains.

  7. The Use of AI in E-Learning Recommender Systems: A Comprehensive Survey, Procedia Computer Science (2023), examining AI’s applications in personalized learning.

Conclusion

Lahcen Tamym stands at the forefront of interdisciplinary research, bridging data science and sustainable systems engineering. His academic contributions are rooted in practical application, ensuring that intelligent technologies directly impact the design and operation of industrial and healthcare systems. With a forward-looking vision aligned with Industry 5.0 principles and the SDGs, his research continues to influence the development of smart, ethical, and eco-efficient networks. Dr. Tamym’s commitment to fostering data-driven innovation across domains positions him as a transformative figure in the evolving landscape of sustainable and resilient enterprise systems.

Giulia Iaconi | AI in Healthcare | Best Researcher Award

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Dr. Giulia Iaconi | AI in Healthcare | Best Researcher Award

PhD Student at University of Genoa, Italy

Giulia Iaconi is a passionate and driven PhD student at the Università degli Studi di Genova, where she is pursuing her doctoral studies in Science and Technology for Electronics and Telecommunications Engineering, with a specialization in Electromagnetism, Electronics, and Telecommunications. Her academic foundation in biomedical and neuroengineering provides her with a unique interdisciplinary approach to address complex challenges in biomedical signal processing and computational neuroscience. Her journey reflects a dedicated pursuit of innovation, especially at the intersection of engineering, healthcare, and data science, where she leverages computational tools and machine learning to advance diagnostic and rehabilitation methods. Giulia’s commitment to applying technology to improve human health has guided her academic and research efforts, culminating in multiple scholarly contributions and participation in prominent interdisciplinary projects aimed at advancing digital health solutions.

Profile

Orcid

Education

Giulia began her academic career at the Alma Mater Studiorum of Bologna, where she obtained her bachelor’s degree in Biomedical Engineering. Her undergraduate thesis focused on exploring bradykinesia in Parkinson’s disease patients through neural models, highlighting her early interest in neuroscience and computational approaches. She later pursued a master’s degree in Neuroengineering from the University of Genoa, where her thesis delved into developing a computational model of the cortico-hippocampal circuit to characterize in vitro experimental dynamics. These educational experiences equipped her with a strong foundation in signal processing, systems modeling, and neurobiological applications. Currently, she is in the final phase of her PhD, during which she continues to deepen her expertise in electronic and telecommunication engineering within biomedical contexts, contributing meaningfully to both academic research and applied innovations.

Experience

Giulia’s research experience spans various domains of biomedical engineering, with a particular focus on digital image processing, data analysis, and machine learning as supportive tools in diagnosis, classification, and rehabilitation. As part of the STORMS (Solution Towards Occupational Rehabilitation for Multiple Sclerosis) project, she worked as an engineer responsible for the design and development of serious games aimed at cognitive assessment and rehabilitation of multiple sclerosis patients. Her interdisciplinary collaborations have enabled her to integrate technological solutions with clinical practices, offering digital innovations to healthcare. Through her involvement in this and other initiatives, she has demonstrated proficiency in implementing supervised learning models, analyzing clinical datasets, and creating user-friendly rehabilitation platforms.

Research Interest

Giulia’s research interests lie at the convergence of computational neuroscience, biomedical signal processing, and intelligent healthcare systems. She is particularly invested in the development of machine learning algorithms and digital tools that enhance early diagnosis and personalized rehabilitation. Her work often involves constructing computational models that replicate brain circuitry behavior or employing image and signal processing to extract meaningful clinical insights. She is passionate about building systems that are not only technically robust but also accessible and impactful in clinical settings. Her recent work has emphasized the integration of these techniques into remote healthcare applications, such as telerehabilitation systems that assist in motor recovery monitoring for neurological patients.

Award

Giulia Iaconi is a strong candidate for the Best Researcher Award due to her continued excellence in research, particularly in biomedical engineering applications that merge computational tools with real-world clinical impact. Her contributions to digital health through machine learning and image processing have advanced diagnostic accuracy and patient rehabilitation techniques. Her interdisciplinary work, both in academia and in applied research projects like STORMS, has set a high benchmark in innovation-led healthcare engineering. Her scholarly achievements, active engagement in engineering communities such as IEEE, and ability to collaborate across disciplines collectively demonstrate her outstanding merit in research and development.

Publication

Giulia has published several impactful research articles that showcase her expertise and innovative contributions. Some of her notable publications include:

“Supervised learning algorithms for liver fibrosis classification using ultrasound images,” published in Electronics, 2023 – cited by 6 articles.

“Analysis of event-related potentials in multiple sclerosis rehabilitation: A case study,” in Biomedical Signal Processing and Control, 2022 – cited by 9 articles.

“Computational modeling of the cortico-hippocampal circuit for neurodynamics interpretation,” in Frontiers in Computational Neuroscience, 2023 – cited by 4 articles.

“Digital biomarkers in telehealth systems for cognitive assessment,” published in Sensors, 2022 – cited by 5 articles.

“Development of serious games for neurological rehabilitation,” in Journal of Medical Systems, 2021 – cited by 7 articles.

“Feature extraction from EEG signals for attention deficit assessment,” in IEEE Access, 2023 – cited by 3 articles.

“Artificial intelligence in biomedical imaging: A review on liver disease diagnostics,” in Diagnostics, 2022 – cited by 6 articles.

Conclusion

In conclusion, Giulia Iaconi exemplifies a new generation of researchers who are reshaping biomedical engineering through the application of cutting-edge technologies. Her deep academic grounding, coupled with her research innovation in neuroengineering and digital health, makes her a promising contributor to the future of intelligent healthcare systems. Her collaborative efforts, scholarly publications, and real-world project involvement reflect her commitment to enhancing patient outcomes using data-driven solutions. Through her doctoral studies and beyond, Giulia continues to push the boundaries of what technology can achieve in medical science, making her an ideal nominee for the Best Researcher Award.