Mr. Sumit Hassan Eshan | Smart Antenna | Young Researcher Award

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Mr. Sumit Hassan Eshan | Smart Antenna | Young Researcher Award

Lead Technical Engineer | Contessa Solutions and Consultants Ltd | Bangladesh

Mr. Sumit Hassan Eshan is a Bangladeshi researcher and engineering professional whose scholarly contributions span smart antennas, nanomaterial-based biomedical sensing, wireless power transfer, terahertz communication, and advanced materials for next-generation wireless systems. His research integrates materials science with electromagnetic design, focusing on nano-engineered antennas using graphene, carbon nanotubes, and transition-metal dichalcogenides for medical diagnostics, on-body sensing, and 6G terahertz applications. Eshan has authored 12 peer-reviewed publications, including four journal papers and eight conference papers across respected SCI and Scopus-indexed venues. One of his works was highlighted on the front cover of a Q1 journal, showcasing the novelty of his contributions to nanomaterial-enabled antennas for cancer detection. His citation record demonstrates his growing academic influence, with 76 citations, an h-index of 6, and an i10-index of 4 on Google Scholar, and 54 citations with an h-index of 5 on Scopus. Eshan’s research covers interdisciplinary domains such as wireless power amplification, nanomaterial spin-coating techniques, biomedical on-body antenna systems, and efficient THz structures for future communication technologies. His continuous engagement as a peer reviewer for prominent engineering journals further reflects his expertise in antenna design, wireless communication, applied electromagnetics, and emerging materials. With a strong foundation in experimental and simulation-based design using CST Studio Suite, Eshan aims to advance innovative antenna technologies that bridge healthcare diagnostics and next-generation wireless systems. His scholarly record positions him as a promising early-career researcher contributing impactful solutions at the intersection of engineering, materials science, and biomedical sensing.

Profiles

Scopus | ORCID | Google Scholar | LinkedIn | ResearchGate

Featured Publications

Hasan, R. R., Jasmine, J., Saleque, A. M., Eshan, S. H., Tusher, R. T. H., Zabin, S., Nowshin, N., Rahman, M. A., & Tsang, Y. H. (2023). Spin coated multi-walled carbon nanotube patch antenna for breast cancer detection. Advanced Materials Technologies, 8(20), 1–13. (Q1, cited)

Anowar, T. I., Hasan, R. R., Eshan, S. H., & Foysal, M. (2025). Enhanced wireless power transfer system using integrated RF amplification. Results in Engineering. (Q1, cited)

Hasan, R. R., Saha, S., Eshan, S. H., Basak, R., Ivan, M. N. A. S., Saleque, A. M., Tusher, R. T. H., Zabin, S., Rahman, M. A., & Tsang, Y. H. (2024). A compact spin-coated graphene UWB antenna for breast tumor detection. Advanced Engineering Materials. (Q1, cited)

Roy, A., Bhuiyan, M. R., Islam, M. A., Saha, P., Eshan, S. H., Hasan, R. R., & Basak, R. (2024). Tungsten disulfide based wearable antenna in terahertz band for sixth generation applications. Telecommunication Computing Electronics and Control, 22(2), 545–555. (Scopus, cited)

Lia, L., Zishan, M. S. R., Eshan, S. H., & Hasan, R. R. (2024). Graphene based terahertz patch antenna for breast tumor detection. Telecommunication Computing Electronics and Control, 22(5), 1073–1082. (Scopus, cited)

Dr. Xiaofeng Liu | Wireless Communication | Best Researcher Award

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Dr. Xiaofeng Liu | Wireless Communication | Best Researcher Award

Dr. Xiaofeng Liu | Lecture | Yancheng Teachers University | China

Dr. Xiaofeng Liu is a dedicated researcher and lecturer in Artificial Intelligence with a strong background in wireless communications, machine learning, and statistical inference. His research primarily focuses on developing advanced algorithms for massive MIMO systems, channel estimation, and machine learning-driven communication models. Dr. Liu has significantly contributed to the integration of statistical learning frameworks in communication system design, particularly through innovations like correlated hybrid message passing and generative diffusion models for channel estimation. His collaborative work with experts from leading research laboratories has produced high-impact publications in IEEE journals, reflecting both theoretical advancement and practical application in intelligent communication systems. His inventive contributions are further evident in several granted Chinese invention patents related to MIMO positioning, channel modeling, and beamspace communications. Dr. Liu’s research achievements are widely recognized, with his publications indexed in Scopus and Google Scholar, accumulating over 135 citations, an h-index of 6, and an i10-index of 5. His scholarly record demonstrates consistent contributions to next-generation wireless communication technologies, bridging the gap between deep learning models and complex signal processing challenges.

Publication Profile

Google Scholar | ORCID

Featured Publications 

Liu, X., Gong, X., & Fu, X. (2025). Activity detection and channel estimation based on correlated hybrid message passing for grant-free massive random access. Entropy.

Fu, X., Gong, X., Liu, X., Sun, R., Shen, Q., & Gao, X. (2025). Beamspace multi-ACB for mMTC in massive MIMO system. IEEE Transactions on Vehicular Technology.

Gong, X., Liu, X., Lu, A. A., Gao, X., Xia, X. G., Wang, C. X., & You, X. (2025). Digital twin of channel: Diffusion model for sensing-assisted statistical channel state information generation. IEEE Transactions on Wireless Communications.

Gong, X., Lu, A. A., Fu, X., Liu, X., Gao, X., & Xia, X. G. (2023). Semisupervised representation contrastive learning for massive MIMO fingerprint positioning. IEEE Internet of Things Journal.

Liu, X., Wang, W., Gong, X., Fu, X., Gao, X., & Xia, X. G. (2023). Structured hybrid message passing based channel estimation for massive MIMO-OFDM systems. IEEE Transactions on Vehicular Technology.

Abimbola Efunogbon | 5G Networks | Best Researcher Award

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Dr. Abimbola Efunogbon |5G Networks | Best Researcher Award

PhD Candidate, University of Bedfordshire, United Kingdom

Dr. Bims Efunogbon is an innovative and people-centric leader with over 15 years of expertise in software engineering, cloud computing, and AI-driven infrastructure. Based in Bedford, UK, she has successfully built and managed distributed engineering teams across remote environments, delivering cutting-edge solutions in developer tools, automation, and cloud architectures. With a strong foundation in digital transformation, she combines strategic oversight with deep technical proficiency to streamline operations and drive business growth. Passionate about AI/ML, DevOps, and cybersecurity, Dr. Efunogbon continues to leverage her expertise to modernize platforms and enhance engineering best practices.

Publication Profile

Scopus

🎓 Education

Dr. Efunogbon holds a PhD in Machine Learning (2024) from the University of Bedfordshire, where she conducted advanced research in AI and network optimization. She also earned an MSc in Computing & Entrepreneurship from the same university, blending technical expertise with business acumen. Her academic journey began with a BSc in Chemical & Polymer Engineering from Lagos State University, Nigeria, providing her with a strong analytical and problem-solving foundation. Additionally, she has completed specialized training in SOA & Service-Oriented Computing and holds certifications in Microsoft Visual Basic.NET and Accounting (Bookkeeping, SAGE).

💼 Experience

With a career spanning over a decade, Dr. Efunogbon has demonstrated exceptional leadership in managing cross-functional engineering teams, overseeing cloud infrastructure, and implementing DevOps practices. She excels in process automation, AI/ML applications, and high-performance computing, enabling seamless integration of innovative solutions across multiple industries. Her expertise includes strategic technology implementation, cloud computing, and agile methodologies, ensuring operational excellence and efficiency. She has successfully led remote engineering teams, coached talent, and driven digital transformation initiatives in various sectors, reinforcing her role as a key industry expert.

🏆 Awards and Honors

Dr. Efunogbon has received numerous accolades for her outstanding contributions, including the Outstanding Staff of the Year (2011) and Best Canvasser of the Year at Debenhams (2009). She was also recognized as the Best Female Engineering Student by APWEN (2001), highlighting her academic excellence and leadership in STEM fields.

🔬 Research Focus

Dr. Efunogbon’s research revolves around AI-driven network optimization, cloud computing, and MLOps. Her work primarily explores the orchestration of 5G network sub-slicing using machine learning in fully virtualized environments, ensuring enhanced performance and efficiency. She is passionate about leveraging emerging technologies to create scalable, intelligent, and secure infrastructure solutions that drive digital transformation.

🔍 Conclusion

Dr. Bims Efunogbon is a dynamic leader, researcher, and innovator dedicated to driving digital transformation and AI-powered solutions. With a strong background in software engineering, cloud computing, and machine learning, she continues to shape the future of AI-driven network optimization and engineering leadership. Her contributions to academia and industry reinforce her commitment to technological excellence and operational efficiency. 🚀

📚 Publications

Optimal 5G Network Sub-Slicing Orchestration in a Fully Virtualised Smart Company Using Machine Learning – Future Internet (2025) Read Here
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