Alfredo Dimo | Biotechnology | Research Excellence Award

Mr. Alfredo Dimo | Biotechnology | Research Excellence Award

Campus Bio Medico University of Rome | Italy

Mr. Alfredo Dimo is an emerging researcher at Fondazione Policlinico Universitario Campus Bio-Medico, Rome, Italy, specializing in biomedical engineering with a strong focus on wearable sensor technologies, 3D-printed sensing devices, and human movement analysis for clinical and rehabilitation applications. His research interests include smart wearable systems, biomechanical motion tracking, and sensor-based health monitoring. He possesses strong research skills in sensor design, prototyping, data acquisition, and experimental validation for healthcare environments. Mr. Dimo’s innovative contributions have earned recognition through peer-reviewed publications and research excellence acknowledgments in biomedical instrumentation. According to Scopus, he has published 9 documents, received 63 citations, and achieved an h-index of 5, demonstrating growing impact and promise in translational biomedical research. Overall, his work supports advancements in personalized healthcare and next-generation wearable medical technologies.

 

Citation Metrics (Scopus)

63
45
30
15
0

Citations

63

Documents

9

h-index

5

Citations

Documents

h-index

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Featured Publications

 

Yao GE | Electrical and Electronics Engineering | Young Scientist Award

Dr. Yao GE | Electrical and Electronics Engineering | Young Scientist Award

Research Fellow | Nanyang Technological University | Singapore

Dr. Yao Ge, a leading researcher at Nanyang Technological University, Singapore, has made significant contributions to advanced wireless communication systems, with research interests spanning secure precoding for ISAC systems, XL-RIS-aided near-field MIMO, OTFS-RSMA, and affine frequency division multiplexing in high-mobility and doubly-dispersive channels. His research skills include multiuser interference management, next-generation multiplexing techniques, and performance optimization of wireless networks. Dr. Ge’s work has earned him 743 citations across 57 documents, with an h-index of 14, highlighting his impactful contributions to the field. He has also been recognized for his innovative approaches in wireless communications through various awards and honors. Overall, his research advances both theoretical understanding and practical applications in secure, high-capacity, and efficient communication systems.

 

Citation Metrics (Scopus)

743
600
400
200
0

Citations

743

Documents

57

h-index

14

Citations

Documents

h-index

View Scopus Profile View Google Scholar Profile View ResearchGate Profile

Featured Publications


Receiver design for OTFS with a fractionally spaced sampling approach


– IEEE Transactions on Wireless Communications, 2021 (Citations: 129)


OTFS signaling for uplink NOMA of heterogeneous mobility users


– IEEE Transactions on Communications, 2021 (Citations: 93)


STAR-RIS aided integrated sensing and communication over high mobility scenarios


– IEEE Transactions on Communications, 2024 (Citations: 52)

 

Vladimir Levchenko | Nanotechnology | Excellence in Research Award

Prof. Vladimir Levchenko | Nanotechnology | Excellence in Research Award

Professor | Taizhou University | China

Prof. Vladimir A. Levchenko is a distinguished researcher in materials science, tribology, and advanced surface engineering, with expertise in developing corrosion-resistant, self-healing, and high-performance multilayer coatings. His research focuses on enhancing mechanical, thermal, and tribological properties of coatings using innovative deposition techniques such as HiPIMS and dynamic Diels–Alder chemistry. His research interests include wear resistance, adhesion improvement, surface modification, and high-performance materials for industrial applications, while his skills cover coating design, materials characterization, tribological testing, and surface analysis. Recognized for his impactful contributions to the field, Prof. Levchenko’s work is highly cited, with Scopus metrics of 634 citations across 57 documents and an h-index of 9, reflecting significant scholarly influence and leadership in surface science and tribology research.

 

Citation Metrics (Scopus)

634
500
350
200
0

Citations

634

Documents

57

h-index

9

Citations

Documents

h-index

View Scopus Profile

Featured Publications

 

Awele Okolie | Artificial Intelligence | Research Excellence Award

Ms. Awele Okolie | Artificial Intelligence | Research Excellence Award

Data Analyst Intern | Wentworth Institute of Technology | United States

Ms. Awele Okolie is an emerging researcher in Machine Learning and Artificial Intelligence, with a strong focus on socially impactful, data-driven research. Her work spans food insecurity prediction, financial fraud detection, healthcare analytics, traffic safety modeling, and explainable AI, demonstrating applied innovation across public policy and safety-critical domains. Her research interests include predictive modeling, explainable machine learning, spatiotemporal analysis, and AI-driven decision systems, supported by skills in data analytics, statistical modeling, and real-world dataset integration. Her scholarly contributions show growing recognition, with Google Scholar metrics of 41 citations, 14 documents, and an h-index of 5, while Scopus citations, documents, and h-index are not provided. Overall, her work reflects a strong commitment to transparent, ethical, and high-impact artificial intelligence research.

 

Citation Metrics (Google Scholar)

41
30
20
10
0

Citations

41

Documents

14

h-index

5

Citations

Documents

h-index

View Google Scholar Profile  View ResearchGate Profile

Featured Publications


Predicting food insecurity across US census tracts: A machine learning analysis using the USDA Food Access Research Atlas

– International Journal of Science and Research Archive, 17(2), 1156-1172, 2025 (Citations: 11)


An Explainable XGBoost Framework for Detecting Fraudulent Financial Transactions

– Journal of Scientific Research and Reports, 31(12), 244-255, 2025 (Citations: 6)


Spatiotemporal analysis and predictive modeling of traffic accidents in Boston: Insights for advancing Vision Zero initiatives

– International Journal of Science and Research Archive, 17(1), 528-543, 2025 (Citations: 6)


Machine learning approaches for predicting 30-day hospital readmissions: Evidence from Massachusetts healthcare data

– World Journal of Advanced Research and Reviews, 28(1), 1-12, 2025 (Citations: 6)