Prof. Dr. Beatriz Defez | Sensors | Research Excellence Award

Professor | Valencia Polytechnic University | Spain

Beatriz Defez García is an accomplished scholar whose work bridges engineering graphics, materials science, acoustic behavior, assistive technologies, and advanced computational modeling. Her research notably spans finite-element analysis of ceramic materials, acoustic characterization of engineered structures, fluid–solid interactions, and the development of innovative navigation systems to support individuals with visual impairments. She has made influential contributions to the fields of human–machine interaction, sensory guidance technologies, telemedicine, and computer-assisted image segmentation, particularly in dermatological applications. Her scholarship encompasses collaborative, interdisciplinary projects addressing societal and industrial needs through engineering innovation. With a strong record of productivity, she has authored 30 Scopus-indexed documents and accumulated 188 citations in Scopus, reflecting an h-index of 7, while her Google Scholar profile reports 486 citations, an h-index of 11, and an i10-index of 11, demonstrating the sustained visibility and relevance of her research. Her most widely cited studies include pioneering prototypes for real-time assistive navigation, analytical and experimental investigations of bubble and drop oscillations, and advanced techniques for usability evaluation in digital learning environments. Across her publications, Defez García integrates computational methods, experimental validation, and user-centered design principles to advance engineering solutions that improve material performance, enhance accessibility, and support health-related digital transformation. Her recent work also highlights growing contributions in telemedicine, sustainable digitalization, and biomedical image processing, reinforcing her role as a multidisciplinary researcher shaping both technological innovation and applied scientific practice.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

Dunai, L., Fajarnes, G. P., Praderas, V. S., Defez Garcia, B., & Lengua, I. (2010). Real-time assistance prototype—A new navigation aid for blind people. IECON Annual Conference on IEEE Industrial Electronics Society, 1–6.

Milne, A. J. B., Defez, B., Cabrerizo-Vílchez, M., & Amirfazli, A. (2014). Understanding (sessile/constrained) bubble and drop oscillations. Advances in Colloid and Interface Science, 203, 22–36.

Dunai, L., Peris-Fajarnés, G., Lluna, E., & Defez, B. (2013). Sensory navigation device for blind people. The Journal of Navigation, 66(3), 349–362.

Fraile-Garcia, E., Ferreiro-Cabello, J., Defez, B., & Peris-Fajanes, G. (2016). Acoustic behavior of hollow blocks and bricks made of concrete doped with waste-tire rubber. Materials, 9(12), 962.

Maria, M. S., Silvia, A. N., Beatriz, D. G., Andrew, D., & Guillermo, P. F. (2022). Health care in rural areas: Proposal of a new telemedicine program assisted from the reference health centers, for sustainable digitization and its contribution to carbon reduction. Heliyon, 8(7).

Mr. HaoFei Chen | Sensor Hardware | Young Innovator Award

Mr. HaoFei Chen | Nanjing University of Science and Technology | China

Chen Haofei is a dynamic researcher specializing in wearable intelligent systems, sensor technology, and machine learning-based recognition models. His research primarily focuses on developing advanced wearable sign language recognition systems for the hearing-impaired, integrating multidisciplinary expertise in kinematic modeling, sensor layout optimization, adaptive algorithm development, and system validation. His work aims to enhance communication accessibility through innovative sensor fusion and data-driven algorithms, achieving recognition accuracies above Ninety Percent. Chen’s technical expertise spans instrumentation science, signal acquisition, data optimization, embedded system design, and intelligent data processing using neural networks and particle swarm optimization. His studies demonstrate a strong commitment to bridging theoretical modeling with real-world application, particularly in high-impact environments such as overpressure explosion testing and multi-dimensional data acquisition. Chen has published influential research articles that contribute significantly to the fields of intelligent measurement and human-computer interaction. According to Scopus, he has 3 citations across 2 indexed documents with an h-index of 1, reflecting the emerging academic influence of his early-stage work. His research outputs are also indexed on Google Scholar, indicating growing international visibility and recognition.

Featured Publication

Chen, H. (2025). Biomechanical feature extraction for robust sign language recognition with applications. Molecular & Cellular Biomechanics, 22(3), 1322.

Chen, H., & Di, C. (2025). Lightweight sign language intelligent recognition model based on improved R-C3D. Egyptian Informatics Journal, Elsevier.