Prof. Saad Aljlil | Engineering | Best Researcher Award

Prof. Saad Aljlil | Engineering | Best Researcher Award

Prof. Saad Aljlil | Chief Researcher | King Abdulaziz City for Science and Technology | Saudi Arabia

Prof. Saad A. Aljlil is a distinguished research professor at the King Abdulaziz City for Science and Technology (KACST), Saudi Arabia, specializing in sustainability, membrane technology, and water and environmental engineering. His research focuses on advanced desalination and water treatment technologies, wastewater purification, membrane synthesis, adsorption processes, and the integration of renewable energy systems for sustainable water management. Prof. Aljlil has made significant contributions to developing ceramic and polymeric membranes, nanocomposite materials, and hybrid desalination systems that enhance water purification efficiency while minimizing environmental impact. His work extends to smart water networks, solar-driven desalination, greywater reuse, and innovative applications of artificial intelligence in membrane distillation and water resource optimization. A highly cited researcher, Prof. Aljlil has achieved 1,079 citations in Scopus across 44 documents with an h-index of 19, and 1,397 citations on Google Scholar with an h-index of 20 and i10-index of 23. His interdisciplinary approach bridges chemical engineering, nanotechnology, and sustainability to address critical challenges in clean water access and environmental preservation.

Publication Profile

Scopus | ORCID | Google Scholar

Featured Publications

Ali, A., Macedonio, F., Drioli, E., Aljlil, S. A., & Alharbi, O. A. (2013). Experimental and theoretical evaluation of temperature polarization phenomenon in direct contact membrane distillation. Chemical Engineering Research and Design, 91(10), 1966–1977.

Quist-Jensen, C. A., Macedonio, F., Conidi, C., Cassano, A., Aljlil, S. A., Alharbi, O. A., & Drioli, E. (2016). Direct contact membrane distillation for the concentration of clarified orange juice. Journal of Food Engineering, 187, 37–43.

Fontananova, E., Bahattab, M. A., Aljlil, S. A., Alowairdy, M., Rinaldi, G., Vuono, D., & Drioli, E. (2015). From hydrophobic to hydrophilic polyvinylidenefluoride (PVDF) membranes by gaining new insight into material properties. RSC Advances, 5(69), 56219–56231.

Park, C. H., Tocci, E., Fontananova, E., Bahattab, M. A., Aljlil, S. A., & Drioli, E. (2016). Mixed matrix membranes containing functionalized multiwalled carbon nanotubes: Mesoscale simulation and experimental approach for optimizing dispersion. Journal of Membrane Science, 514, 195–209.

Sedighi, M., Aljlil, S. A., Alsubei, M. D., Ghasemi, M., & Mohammadi, M. (2018). Performance optimisation of microbial fuel cell for wastewater treatment and sustainable clean energy generation using response surface methodology. Alexandria Engineering Journal, 57(4), 4243–4253.

 

Sihwan Kim | Biomedical Engineering | Best Researcher Award

Dr. Sihwan Kim | Biomedical Engineering | Best Researcher Award

Ph.D., Seoul National University, South Korea

🌟 Dr. Sihwan Kim is a dedicated researcher specializing in medical image processing, artificial intelligence, and medical physics. He is currently associated with Seoul National University, where his innovative work combines machine learning and advanced imaging techniques to revolutionize healthcare solutions. With a strong academic background and extensive professional experience, Dr. Kim is recognized as an emerging leader in his field.

Publication Profile

Education

🎓 Dr. Kim earned his Ph.D. in Applied Bioengineering from Seoul National University, Republic of Korea, in February 2025. He holds a dual Bachelor of Science degree in Manufacturing Systems and Design Engineering from the University of Northumbria at Newcastle (UK) and Seoul National University of Science and Technology (Korea), obtained in 2018.

Experience

🔬 Dr. Kim has contributed significantly as a Research Scientist at the Biomedical Research Institute, Seoul National University Hospital. His expertise spans medical imaging with machine learning and deep learning applications, focusing on CT, MRI, and nano-biological imaging. He has also completed five Korean government research projects and one industry-sponsored project.

Awards and Honors

🏆 Dr. Kim is a valued member of prestigious organizations such as the Radiological Society of North America (RSNA), the International Commission on Radiological Protection (ICRP), and the Korean Society of Imaging Informatics in Medicine (KSIIM). His groundbreaking contributions, particularly in AI-driven segmentation workflows, have earned him accolades across the scientific community.

Research Focus

💡 Dr. Kim’s research revolves around medical image processing, leveraging artificial intelligence to enhance the efficiency and accuracy of diagnostic tools. His recent work introduced a novel fully-automated audit and self-correction algorithm using MeshCNN and generative AI, significantly impacting clinical applications through innovative segmentation techniques.

Conclusion

🌐 Dr. Sihwan Kim is a trailblazer in applying artificial intelligence to medical imaging, with his work poised to improve healthcare practices globally. His dedication to research excellence and groundbreaking contributions exemplify his potential as a transformative figure in the field.

Publications

Advanced AI Techniqes for Automated Segmentation in Medical Imaging, Bioengineering, MDPI.

Cited by: 8

MeshCNN Applications in 3D Topology Analysis,  Journal of Medical Physics Research.

Cited by: 5

Uncertainty Measurement in 3D-Mesh Surfaces, Korean Journal of Radiological Science.

Cited by: 3

Hybrid Models in Medical Imaging,  Journal of AI-Driven Healthcare Research.

Cited by: 4

Deep Learning in Nano-Biological Imaging,  International Journal of Biomedical Research.

Cited by: 1