Mohammed Aseeri | IoT (Internet of Things) Analytics | Best Researcher Award

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Prof Dr. Mohammed Aseeri | IoT (Internet of Things) Analytics | Best Researcher Award

King Abdulaziz city for science and technology KACST | Saudi Arabia

EARLY ACADEMIC PURSUITS 🎓

Prof. Mohammed Aseeri embarked on his academic journey with a strong foundation in Electrical and Computing Engineering. He earned his Bachelor’s degree from King Abdulaziz University, Jeddah, Saudi Arabia, in 1995, followed by a Master’s degree in 1998. His curiosity for deeper technological understanding led him to the University of Kent, UK, where he achieved his Ph.D. in Electronics and Communications Engineering in 2003. These formative academic experiences not only provided him with extensive knowledge in electrical engineering and technology but also laid the groundwork for his future career in research and innovation.

PROFESSIONAL ENDEAVORS 💼

Throughout his distinguished career, Prof. Aseeri has held numerous prominent roles in both academic and industrial sectors. He has served as a Research Professor at the King Abdulaziz City of Science and Technology (KACST), where he is currently leading in the Future Economics sector. His extensive experience spans over 25 years, and he has held leadership positions in various organizations. This includes being a founder of multiple startup companies such as Advanced Future Tech Company, Future Event Company, and Insightful Data Company. His role as a key contributor to national initiatives such as Saudi Arabia’s Vision 2030 and national security programs further emphasizes his deep commitment to the development of both local and international technological landscapes.

CONTRIBUTIONS AND RESEARCH FOCUS  ON IoT (Internet of Things) Analytics🔬

Prof. Aseeri has been instrumental in shaping innovation in several domains, including technology transfer, industrial research, and product development. He has spearheaded multiple R&D projects with international partners, driving advancements in the Future Economics sector. His research has contributed significantly to the fields of wireless sensors, connectivity, and digital innovation. He has supervised numerous projects and students, mentoring the next generation of researchers. His work has been marked by a passion for integrating local capabilities with international expertise, ultimately aiming for sustainable technology solutions that align with global trends.

IMPACT AND INFLUENCE 🌍

Prof. Aseeri’s influence extends beyond academic research and into real-world applications. His leadership in the National Security Program and contributions to Saudi Arabia’s Vision 2030 demonstrate his integral role in shaping national strategies. His impact is further seen in the numerous partnerships he has cultivated with international organizations, which have led to successful collaborations. As a mentor, speaker, and advisor, he has helped shape the direction of innovation in the Kingdom and globally, fostering a culture of research excellence and technological growth.

ACADEMIC CITATIONS AND RECOGNITIONS 📚

With over 100 published research papers, Prof. Aseeri’s contributions to academic literature have been recognized by prestigious international journals and conferences. His expertise in electronics, communications, and engineering has earned him several awards and certificates, including the Ministry of Communications and Information Technology Award for Digital Innovation in 2021 and the Federation of Arab Scientific Research Councils award for innovation in 2019. His work continues to be cited in numerous academic circles, underlining his lasting influence in the field of engineering and technology.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Prof. Aseeri’s legacy is one built on fostering collaboration, pioneering research, and strategic leadership in both academic and industrial domains. His ongoing commitment to the development of local talent, particularly through his leadership roles at KACST and in various startups, ensures that his influence will continue for years to come. Moving forward, his future contributions are expected to play a key role in advancing technological innovation, driving economic transformation in Saudi Arabia, and fostering deeper international research cooperation. His continuous dedication to innovation and sustainable development is shaping the future of technology in the region and beyond.

LEADERSHIP AND COLLABORATIONS 🌐

As a seasoned leader, Prof. Aseeri has excelled at building effective teams and fostering collaborations across local and international platforms. His leadership extends to several advisory committees, boards, and industry collaborations. He has been pivotal in guiding organizations towards strategic planning and technology implementation. By fostering partnerships across academia, industry, and government sectors, he is helping pave the way for groundbreaking developments in research and innovation, aligning with his mission to build sustainable capabilities for the future.

 NOTABLE PUBLICATIONS 📑

Numerical analysis of MIM nano-rectenna with metasurface for infrared energy harvesting
    • Authors: Rmili, H., Yahyaoui, A., Yousaf, J., Hakim, B., Sobahi, N.
    • Journal: Alexandria Engineering Journal
    • Year: 2024
An Integrated 100-GHz FMCW Imaging Radar for Low-Cost Drywall Inspection
    • Authors: Naghavi, S.M.H., Taba, M.T., Aseeri, M., Afshari, E.
    • Journal: IEEE Transactions on Microwave Theory and Techniques
    • Year: 2024
24.4 Sub-THz Ruler: Spectral Bistability in a 235GHz Self-Injection-Locked Oscillator for Agile and Unambiguous Ranging
    • Authors: Naghavi, S.M., Taba, M.T., Tabatabavakili, A., Cathelin, A., Afshari, E.
    • Conference: Digest of Technical Papers – IEEE International Solid-State Circuits Conference
    • Year: 2024
DBSCAN-Based Malicious Node Detection to Secure Wireless Sensor Networks
    • Authors: Ahmed, M.R., Myo, T., Aseeri, M.A., Al Baroomi, B., Kaiser, M.S.
    • Conference: ACM International Conference Proceeding Series
    • Year: 2023
Electromagnetic Signature of Hilbert Curve-Based Chipless RFID Tags Using Numerical Analysis
    • Authors: Zaqumi, M.N., Ladhar, L., Rmili, H., Lalbakhsh, A., Aseeri, M.
    • Conference: Mediterranean Microwave Symposium
    • Year: 2023

Changjiang Liu | Remote sensing | Best Researcher Award

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Dr. Changjiang Liu | Remote sensing | Best Researcher Award

Xinjiang Normal University, China

Author Profiles 📚

Scopus

Orcid

Early Academic Pursuits 🎓

Dr. Changjiang Liu’s academic journey centers on the field of cartography and geographic information systems (GIS). His early pursuits focused on understanding the intricacies of remote sensing and its applications to environmental monitoring. This foundation laid the groundwork for his subsequent research on water environment extraction in arid regions, specifically lakes and reservoirs, using advanced remote sensing techniques. His work over the past five years has contributed significantly to the understanding of water dynamics in such challenging environments.

Professional Endeavors 💼

Dr. Liu’s professional career has been marked by continuous engagement with cutting-edge research in remote sensing applications, particularly in the context of arid areas. He has secured various research grants, including the Open Project of Xinjiang Laboratory of Lake Environment and Resources in Arid Zone, and the Xinjiang Uygur Autonomous Region Natural Science Foundation. These projects have allowed him to explore the relationship between water quality, quantity, and environmental changes, contributing to the advancement of remote sensing technologies in resource management.

Contributions and Research Focus 🔬

Dr. Liu’s primary research focuses on the remote sensing of water environments, especially in arid regions. His studies examine the spatiotemporal variations in water quality and quantity in lakes and reservoirs, emphasizing the role of shallow water bottom reflection and its impact on remote sensing data. By developing radiative transfer simulations, he has made significant strides in enhancing the accuracy of water monitoring. Additionally, his work on quantifying the radiation transmission mechanism in shallow water environments has improved the understanding of water behavior in arid areas.

Impact and Influence 🌍

Dr. Liu’s research has had a profound impact on the scientific community, with 10 SCI papers as the first author and numerous collaborations with international researchers. His work has been widely cited (913 times), reflecting its importance and influence in the fields of remote sensing and environmental science. His papers in prestigious journals like Journal of Cleaner Production and Science of the Total Environment have contributed to advancing knowledge on water quality monitoring, environmental protection, and sustainable resource management in arid regions.

Academic Cites 📚

Dr. Liu has an H-Index of 16, which reflects the citation impact of his published work. With a total of 29 papers, his research is well-regarded in the field of environmental sciences, particularly in remote sensing. His influential articles continue to shape the discourse on water quality monitoring, environmental management, and the utilization of GIS and remote sensing technologies to assess and manage natural resources.

Technical Skills 🛠️

With a strong background in remote sensing and GIS, Dr. Liu possesses advanced technical skills in radiative transfer simulation, spatial data analysis, and environmental monitoring using remote sensing technologies. His expertise extends to the application of these techniques for analyzing water quality, quantity, and the environmental impacts of shallow water reservoirs and lakes. Dr. Liu’s contributions to technical advancements in these areas have enhanced the accuracy of environmental assessments in arid regions.

Teaching Experience 🍎

As a lecturer at Xinjiang Normal University, Dr. Liu imparts his knowledge and expertise to students, fostering a new generation of researchers and professionals in the fields of cartography, remote sensing, and GIS. His teaching experience includes guiding students through complex topics such as environmental monitoring, remote sensing analysis, and geographic information system applications, emphasizing both theoretical and practical aspects.

Legacy and Future Contributions 🔮

Dr. Liu’s legacy lies in his pioneering work in the application of remote sensing for environmental monitoring in arid regions. His research has contributed to the development of more accurate techniques for assessing water quality and quantity in challenging environments. Moving forward, Dr. Liu is poised to make continued contributions to the field, with ongoing research projects that aim to refine remote sensing methodologies and improve sustainable water management practices. His future work will undoubtedly further the understanding of arid region water systems, with broad applications for resource management and environmental protection.

Top Noted Publications 📖

An Advanced Spatiotemporal Fusion Model for Suspended Particulate Matter Monitoring in an Intermontane Lake
    • Authors: Zhang, F.; Duan, P.; Jim, C.Y.; Johnson, V.C.; Liu, C.; Chan, N.W.; Tan, M.L.; Kung, H.-T.; Shi, J.; Wang, W.
    • Journal: Remote Sensing
    • Year: 2023
Determining the main contributing factors to nutrient concentration in rivers in arid northwest China using partial least squares structural equation modeling
    • Authors: Wang, W.; Zhang, F.; Zhao, Q.; Liu, C.; Jim, C.Y.; Johnson, V.C.; Tan, M.L.
    • Journal: Journal of Environmental Management
    • Year: 2023
High-Resolution Planetscope Imagery and Machine Learning for Estimating Suspended Particulate Matter in the Ebinur Lake, Xinjiang, China
    • Authors: Pan Duan; Fei Zhang; Changjiang Liu; Mou Leong Tan; Jingchao Shi; Weiwei Wang; Yunfei Cai; Hsiang-Te Kung; Shengtian Yang
    • Journal: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
    • Year: 2023
Reconstruction of Sentinel Images for Suspended Particulate Matter Monitoring in Arid Regions
    • Authors: Duan, P.; Zhang, F.; Jim, C.-Y.; Tan, M.L.; Cai, Y.; Shi, J.; Liu, C.; Wang, W.; Wang, Z.
    • Journal: Remote Sensing
    • Year: 2023
Remote sensing for chromophoric dissolved organic matter (CDOM) monitoring research 2003–2022: A bibliometric analysis based on the web of science core database
    • Authors: Li, Z.; Zhang, F.; Shi, J.; Chan, N.W.; Tan, M.L.; Kung, H.-T.; Liu, C.; Cheng, C.; Cai, Y.; Wang, W. et al.
    • Journal: Marine Pollution Bulletin
    • Year: 2023

Yanjie Zhu | Algorithm Development | Best Researcher Award

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Prof. Yanjie Zhu | Algorithm Development | Best Researcher Award

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China

👨‍🎓Professional Profiles

🔬 Summary

Prof. Yanjie Zhu is a renowned expert in fast magnetic resonance imaging (MRI) and its applications in medical diagnostics. He specializes in developing innovative imaging techniques through machine learning, deep learning, and model-driven methods. As a Professor at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, he leads cutting-edge research projects focused on cardiovascular imaging, brain health, and intelligent diagnostic tools.

🎓 Education

Prof. Zhu earned his Ph.D. in Circuits and Systems from the Shanghai Institute of Technical Physics, Chinese Academy of Sciences, China (2006-2011). He also holds a B.S. in Electronic Engineering and Information Science from the University of Science and Technology of China, Hefei (2002-2006).

🏫 Professional Experience

Prof. Zhu has a distinguished academic career at the Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, where he progressed from Assistant Professor (2011-2015) to Associate Professor (2015-2020), and is currently a Professor (2020-present). Additionally, he served as a Visiting Scholar (2017-2018) at Harvard Medical School and Beth Israel Deaconess Medical Center, Boston, MA, under the guidance of Reza Nezafat.

📚 Academic Contributions

Prof. Zhu has published several impactful papers in the field of MRI and medical imaging. Notable works include:

  • “Online reconstruction of fast dynamic MR imaging using deep low-rank plus sparse network,” IEEE CBMS, 2022.
  • “k-space based reconstruction method for wave encoded bSSFP sequence,” CECIT, 2021.
  • “Quantification of pectinate muscles inside left atrial appendage from CT images using fractal analysis,” ICMIPE, 2021.
  • Myocardial Edema Imaging – A Comparison of Three Techniques, ISMRM 2018 (Power Pitch, Magna Cum Laude Merit Award).

🔍 Research Interests

Prof. Zhu’s research interests revolve around model-driven fast MRI techniques, generative model-based adaptive MRI methods, and diffusion tensor and edema imaging for myocardial and brain tissue. He is also focused on intelligent diagnosis for the early detection of stroke-related plaques and other cardiovascular conditions.

💻 Technical Skills

Prof. Zhu is highly skilled in MRI imaging techniques, including fast MRI, cardiac MRI, and brain MRI. He also excels in deep learning and AI-based image reconstruction methods, along with proficiency in medical imaging software and model-driven approaches. His expertise in data analysis and computational methods has contributed to advancing medical applications.

👨‍🏫 Teaching Experience

Throughout his career, Prof. Zhu has mentored and taught graduate students and professionals in the fields of MRI technology, medical imaging, and computational healthcare methods. His research-driven approach has helped develop comprehensive educational materials that support the training of professionals in advanced imaging systems.

📖Top Noted Publications

RS-MOCO: A deep learning-based topology-preserving image registration method for cardiac T1 mapping

Authors: Chiyi Huang, Longwei Sun, Dong Liang, Haifeng Liang, Hongwu Zeng, Yanjie Zhu
Journal: Computers in Biology and Medicine
Year: 2024

High-Frequency Space Diffusion Model for Accelerated MRI

Authors: Chentao Cao, Zhuo-Xu Cui, Yue Wang, Shaonan Liu, Taijin Chen, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: IEEE Transactions on Medical Imaging
Year: 2024

SPIRiT-Diffusion: Self-Consistency Driven Diffusion Model for Accelerated MRI

Authors: Zhuo-Xu Cui, Chentao Cao, Yue Wang, Sen Jia, Jing Cheng, Xin Liu, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: IEEE Transactions on Medical Imaging
Year: 2024

A Two-Stage Generative Model with CycleGAN and Joint Diffusion for MRI-based Brain Tumor Detection

Authors: Wenxin Wang, Zhuo-Xu Cui, Guanxun Cheng, Chentao Cao, Xi Xu, Ziwei Liu, Haifeng Wang, Yulong Qi, Dong Liang, Yanjie Zhu
Journal: IEEE Journal of Biomedical and Health Informatics
Year: 2024

High efficiency free-breathing 3D thoracic aorta vessel wall imaging using self-gating image reconstruction

Authors: Caiyun Shi, Congcong Liu, Shi Su, Haifeng Wang, Xin Liu, Hairong Zheng, Dong Liang, Yanjie Zhu
Journal: Magnetic Resonance Imaging
Year: 2024

Physics-Driven Deep Learning Methods for Fast Quantitative Magnetic Resonance Imaging

Authors: Yanjie Zhu, Jing Cheng, Zhuo-Xu Cui, et.al.
Journal: IEEE Signal Processing Magazine
Year: 2023