Konstantinos Blazakis | Engineering | Research Excellance Award

Dr. Konstantinos Blazakis | Engineering | Research Excellance Award

Adjunct professor | Hellenic Mediterranean University | Greece

Dr. Konstantinos Blazakis is an electrical and computer engineer and AI researcher specializing in smart energy systems, renewable energy analytics, and advanced machine learning. His work integrates artificial intelligence, quantum machine learning, and power systems, with a strong focus on electricity theft detection, forecasting, and smart grid optimization. He has advanced academic training in electrical and computer engineering, smart grid measurement processing, and applied mathematics and physics, enabling a multidisciplinary approach to energy challenges. His professional background spans university-level teaching, EU-funded renewable energy and photovoltaic research projects, smart grid resilience studies, and contributions to industrial photovoltaic installations and power network design. His research interests include machine learning and deep learning for energy forecasting, smart meter data analytics, quantum neural networks, vehicle-to-grid modeling, and energy market analysis, as well as emerging nanoelectronic devices for next-generation sensing and computing. His work supports the development of resilient, intelligent, and low-carbon energy infrastructures.

Citation Metrics (Scopus)

120

100

80

60

40

20

0

Citations
107

Documents
11

h-index
4

        🟦 Citations    🟥 Documents    🟩 h-index


View Scopus Profile
View Google Scholar Profile

Featured Publications

Afera Halefom Teka | Engineering | Research Excellance Award

Mr. Afera Halefom Teka | Engineering | Research Excellance Award

Afera Halefom Teka | University of Chinese Academy of Sciences | Ethiopia

Mr. Afera Halefom Teka is a researcher specializing in cartography, geospatial analysis, hydrology, and land–environment interactions, with strong expertise in GIS, remote sensing, and water resources modeling. His work addresses land use change, hydrological processes, watershed vulnerability, and environmental sustainability across diverse landscapes. With experience in academic teaching, research leadership, and interdisciplinary collaborations, he contributes to evidence-based geospatial solutions for climate resilience, watershed management, and sustainable land–water governance. His research applies spatial modeling, multi-criteria evaluation, machine learning, and advanced cartographic visualization to examine land use dynamics, climate variability, soil erosion risk, groundwater potential, and environmental change detection. He has also taken part in international trainings, conferences, and collaborative projects advancing geospatial applications for disaster risk reduction and resource planning. His contributions have been recognized through academic distinctions, research committee leadership roles, competitive training selections, and conference acknowledgments.

Citation Metrics (Google Scholar)

1000

800

600

400

200

0

Citations
973

Documents
26

h-index
18

        🟦 Citations    🟥 Documents    🟩 h-index


View Google Scholar Profile

Featured Publications

Hongming Zhang | Engineering | Best Researcher Award

Assoc. Prof. Dr. Hongming Zhang | Engineering | Best Researcher Award

Academician | Beijing University of Posts and Telecommunications | China

Dr. Hongming Zhang is an accomplished Associate Professor at the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, China. He earned his Ph.D. in Electrical and Electronic Engineering from the University of Southampton under the supervision of Prof. Lajos Hanzo and Prof. Lie-Liang Yang, following his M.Sc. from Southampton, B.Eng. with Honors from City, University of London, and B.Eng. in Information Engineering from Nanjing University of Aeronautics and Astronautics. Before joining BUPT, he conducted postdoctoral research at Columbia University, contributing to advancements in wireless communication technologies. His research focuses on wireless communications, heterogeneous networking, underwater acoustics, and AI-driven optimization, particularly in areas such as federated learning, intelligent reflecting surfaces, and 6G network design. As a prolific and highly cited researcher, Dr. Zhang has co-authored more than forty IEEE journal papers in collaboration with leading international scholars. His publication record includes 59 documents cited by 967 other documents, totaling 1,207 citations. He has served as an Associate Editor for Electronics Letters and a Review Editor for Frontiers in Communications and Networks. His excellence has been recognized through numerous honors, including the Boosting Project Award for Young Talents from the China Association for Science and Technology, multiple IEEE Best Paper Awards, and the Science and Technology Awards from the China Institute of Communications and the Radio Association of China. His work bridges theory and application, advancing intelligent, energy-efficient communication systems and inspiring innovation within the global telecommunications community.

Profile : Scopus | ORCID 

Featured Publications 

Zhang, H., Yang, L.-L., & Hanzo, L. (2016). Performance analysis of OFDM systems in dispersive indoor power line channels. IET Communications. [Cited by 35]

Zhang, H., Jiang, C., & Hanzo, L. (2019). Linear precoded index modulation. IEEE Transactions on Communications. [Cited by 120]

Zhang, H., & Hanzo, L. (2020). Federated learning assisted multi-UAV networks. IEEE Transactions on Vehicular Technology. [Cited by 90]

Jiang, H., Xiong, B., & Zhang, H. (2023). Hybrid far- and near-field modeling for RIS assisted V2V channels. IEEE Transactions on Wireless Communications. [Cited by 45]

Zhang, H., et al. (2024). Space-time shift keying aided OTFS modulation for orthogonal multiple access. IEEE Transactions on Communications. [Cited by 20]

Belkacem Bekhiti | Engineering | Best Researcher Award

Prof. Belkacem Bekhiti | Engineering | Best Researcher Award

Prof. Belkacem Bekhiti | Institute of Aeronautics and Space Studies, University of Blida | Algeria

Dr. Bekhiti Belkacem is a distinguished academic and researcher in control theory, robotics, and aerospace engineering, currently serving as a Lecturer at the Institute of Aeronautics and Space Studies, Blida University 1, Algeria. His expertise spans guidance, navigation, and control systems, integrating theoretical modeling with real-world aerospace applications. He holds a Doctorate in Electrical Engineering with a specialization in Automatic Control from the University of Boumerdes, a Magister in Advanced Control of Complex Systems from the National Polytechnic School, Oran, a Master’s in Automatic Control from the University of Djelfa, and an Engineering degree in Electrical Engineering from Boumerdes. His career includes teaching positions at Blida and Djelfa Universities, collaboration with the Algerian Air Agency, and supervision of advanced student projects in UAVs, satellite control, and robotics. His research focuses on MIMO control, matrix polynomial theory, robotic modeling, nonlinear adaptive control, and intelligent aerospace system design, merging classical automation with artificial intelligence and fractional-order control. He has authored several books and numerous international publications, presented his work at major conferences, and earned recognition for his contributions to intelligent control and aerospace systems. His influence extends across the Algerian and international research communities, where he continues to inspire innovation and academic excellence in modern control and aeronautical engineering.

Profile : Google Scholar 

Featured Publications 

  • Bekhiti, B. (2015). On the theory of λ-matrices based MIMO control system design. Control and Cybernetics.

  • Bekhiti, B. (2017). Intelligent block spectral factors relocation in a quadrotor UAV. International Journal of Scientific Computing (IJSCC).

  • Bekhiti, B. (2018). On λ-matrices and their applications in MIMO control systems design. International Journal of Mathematical and Computational Intelligence (IJMIC).

  • Bekhiti, B. (2020). On the block decomposition and spectral factors of λ-matrices. Control and Cybernetics.

  • Bekhiti, B. (2020). Internal stability improvement of a natural gas centrifugal compressor. Journal of Natural Gas Science and Engineering.

Shangshang Wu | Engineering | Best Researcher Award

Dr. Shangshang Wu | Engineering | Best Researcher Award

Tianjin university | China

Wu Shangshang is a mechanical engineer pursuing her Ph.D. at the School of Mechanical Engineering, Tianjin University in China, where she also completed her B.S. and M.S. in Mechanical Engineering. Her research focuses on underwater gliders, emphasizing hydrodynamic identification, motion behavior analysis, and front-end data processing for acoustic communication. Since her master’s studies, she has worked as a graduate researcher, contributing to both experimental sea trials and theoretical modeling, and has published journal articles and conference papers in marine robotics, acoustics, and signal processing. Wu’s doctoral work advances model-based and data-driven methods to improve hydrodynamic prediction and control under uncertain underwater conditions, supporting the development of reliable seabed vehicles and underwater communication systems. She collaborates closely with colleagues at Tianjin University, including researchers such as Guangwei Lv and Shaoqiong Yang, and her early contributions are gaining citations. Her interests also include neural network–based hybrid modeling, online estimation, and mitigating the effects of environmental factors like sea currents and noise on underwater navigation and sensor performance. While no specific awards are publicly documented, Wu shows strong potential in combining experimental insights with computational techniques to enhance the design, control, and stability of underwater gliders.

Profile : Scopus| ORCID  

Featured Publications

AuthorLastName, A. A., & AuthorLastName, B. B. Model and data-driven hydrodynamic identification and prediction for underwater gliders. Physics of Fluids.

AuthorLastName, A. A., & AuthorLastName, B. B. An enhanced variational mode decomposition method for processing hydrodynamic data of underwater gliders. Measurement.

AuthorLastName, A. A., & AuthorLastName, B. B. Multi-body modelling and analysis of the motion platform for underwater acoustic dynamic communication. Applied Mathematical Modelling.