Annarosa Scalcione | Machine learning | Research Excellence Award

Dr. Annarosa Scalcione | Machine learning | Research Excellence Award

Politecnico di Torino | Italy

Dr. Annarosa Scalcione is an early-career biomedical engineer at Politecnico di Torino with research expertise in medical image analysis, radiomics, and artificial intelligence–based diagnostic support systems. Her work focuses on end-to-end radiomic frameworks for the automated classification and three-dimensional visualization of vertebral lesions, aiming to enhance accuracy, reproducibility, and clinical interpretability in spinal and musculoskeletal imaging. She is the co-author of a peer-reviewed journal article published in Engineering (MDPI), reflecting her contribution to interdisciplinary research at the intersection of biomedical engineering, computer vision, and clinical imaging. Her research activities involve collaboration with multidisciplinary teams of engineers, clinicians, and imaging experts, underscoring a strong capacity for cooperative scientific work. While at an early stage of her academic career, her research demonstrates clear translational and societal impact by supporting improved diagnostic workflows, facilitating data-driven clinical decision-making, and contributing to the advancement of intelligent healthcare technologies with potential benefits for patient outcomes.


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Abhilash Kancharla | Deep Learning | Editorial Board Member

Dr. Abhilash Kancharla | Deep Learning | Editorial Board Member

The University of Tampa | United States

Dr. Abhilash Kancharla is a researcher at the University of Tampa specializing in advanced computing and next-generation digital technologies, with expertise in edge computing, 6G networks, blockchain-based security and privacy, quantum machine learning, neural-inspired algorithms, and computational modeling of nanomaterials. He has published 23 peer-reviewed research articles, which have received 50 citations, and holds an h-index of 4, reflecting consistent academic impact in emerging interdisciplinary fields. His work is particularly notable for integrating intelligent learning models with secure communication architectures for future wireless networks, as well as applying computational intelligence to the analysis of self-healing materials. Through collaborations with 14 co-authors, he actively contributes to international research networks, fostering cross-disciplinary knowledge exchange. The broader social and technological impact of his research supports the development of secure, intelligent, and sustainable digital infrastructures, with relevance to future communication systems, smart technologies, and advanced material design.

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