Mehmet Yilmaz | Artificial Neural Networks | Best Researcher Award

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Mr. Mehmet Yilmaz | Artificial Neural Networks | Best Researcher Award

Mr, Mehmet Yilmaz, Kayseri University, Turkey

Mehmet Yilmaz is a lecturer in the Department of Architecture and Urban Planning at Kayseri University, Turkey. With an academic background in Geomatic Engineering from Erciyes University, he brings expertise in geotechnical engineering, real estate valuation, and geographic information systems (GIS) to his role. Currently pursuing his doctorate, Mr. Yilmaz’s teaching and research contributions focus on engineering applications in urban environments, including courses on land measurement, urban information systems, and property law. His work is dedicated to exploring innovative solutions in GIS and urban planning, addressing practical challenges in real estate valuation and geotechnical engineering.

PROFILE

Orcid Profile

Educational Details

Mr. Mehmet Yilmaz is a faculty member at Kayseri University, Turkey, where he specializes in engineering and urban planning. He is currently pursuing his Doctorate in Geomatic Engineering at Erciyes University’s Institute of Science (Fen Bilimleri Enstitüsü), continuing his journey in the same field in which he obtained both his postgraduate degree (2019-2021) and undergraduate degree (2007-2012). This solid academic foundation has equipped him with specialized skills in geographic information systems, geotechnical engineering, and real estate valuation.

Professional Experience

Since 2018, Mr. Yilmaz has served as a lecturer at Kayseri University in the Tomarza Mustafa Akıncıoğlu Vocational School of Architecture and Urban Planning. He previously taught at Erciyes University in the same department (2017-2018). Throughout his career, he has taught a wide array of courses, including Land Measurement, Expropriation Techniques, Real Estate Law, Urban Information Systems, and Real Estate Valuation Techniques, as well as foundational courses such as Mathematics and Basic Law. His commitment to teaching and hands-on field knowledge has contributed to his expertise in applied engineering and planning education.

Research Interests

Mr. Yilmaz’s research interests span several critical areas within engineering and urban planning, including geotechnical engineering, real estate valuation, geographic information systems (GIS), and image processing. His research has previously focused on topics such as property tax loss in mass valuation, as exemplified by his postgraduate thesis, which investigated the impacts of mass valuation on tax losses in the Kayseri region. This study highlights his interest in the integration of GIS and valuation techniques to address real-world urban planning challenges.

Top Notable Publications

Mehmet Yilmaz (2024)
Title: Hiperspektral görüntülerde Relief-F algoritması ile band seçimi
Source: Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi
Publication Date: 2024-04-02
DOI: 10.28948/ngumuh.1408200

Mehmet Yilmaz (2023)
Title: Investigation of Real Estate Tax Leakage Loss Rates with ANNs
Source: Buildings
Publication Date: 2023-09-28
DOI: 10.3390/buildings13102464
ISSN: 2075-5309

Mehmet Yilmaz (2021)
Title: Determination of Housing Prices with Mass Appraisal in Turkey
Source: Ankara V. International Scientific Research Congress
Publication Date: 2021-10-18
(Conference abstract, no DOI provided)

Conclusion

Mr. Mehmet Yilmaz’s academic background, teaching experience, research interests, certifications, and publication record collectively establish him as a dedicated researcher in the fields of geomatics, urban planning, and real estate valuation. His interdisciplinary approach, integrating advanced technologies like GIS, hyperspectral imaging, and neural networks, is noteworthy for solving real-world challenges in property valuation and urban information systems. Given these qualifications, Mr. Yilmaz is a strong candidate for the Research for Best Researcher Award, with demonstrated potential for further contributions to his field.

 

 

 

 

 

 

 

Xiao-Yong Zhang | AI-Driven | Best Researcher Award

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Prof. Xiao-Yong Zhang | AI-Driven | Best Researcher Award

Prof. Xiao-Yong Zhang, Shanghai Jiao Tong University School of Medicine, China

Dr. Xiao-Yong Zhang is a leading expert in medical imaging, with a special focus on using MRI and AI to advance diagnostic technology for brain health. He has held esteemed positions across top institutions in China and the U.S., contributing to neuroimaging through his roles as an editor, committee member, and principal investigator of high-impact research projects. Dr. Zhang’s innovative work in the quantitative detection of neuroinflammation and Alzheimer’s biomarkers underscores his commitment to advancing neurological diagnostics and personalized medicine.

PROFILE

Orcid  Profile

Educational Details

Ph.D. in Medical Imaging (2007), Fourth Military Medical University, Xi’an, China

Master of Medicine (M.Med.) in Radiological Sciences (2004), Fourth Military Medical University, Xi’an, China

Bachelor of Science (B.S.) in Biomedical Engineering (1998), Fourth Military Medical University, Xi’an, China

Professional Experience

Professor (2024–Present), Shanghai Jiao Tong University School of Medicine

Associate Professor (2017–2024), Fudan University

Research Associate (2014–2016), Vanderbilt University, under Dr. John C. Gore

Postdoctoral Fellow (2009–2014), Georgia Institute of Technology and Emory University, under Dr. Xiaoping P. Hu

Engineer/Lecturer (2007–2009), Fourth Military Medical University

Research Interests

Magnetic Resonance Imaging (MRI): Developing visualization techniques for brain microenvironments.

Deep Learning Algorithms: Creating AI-driven diagnostic tools to improve the detection and understanding of neurological diseases.

Grants

Quantitative Detection of Neuroinflammation using Hydroxyl Proton Transfer MRI
(2022–2025) | National Natural Science Foundation of China (NSFC) | Principal Investigator

Imaging Biomarkers for Alzheimer’s Disease
(2020–2021) | Fudan-Cambridge collaboration | Principal Investigator

Glioma Genotyping using CEST-NOE MRI
(2020–2023) | Shanghai Science and Technology Committee (STCSM) | Principal Investigator

Label-Free NOE MR Imaging of Choline Phospholipids
(2019–2022) | National Natural Science Foundation of China (NSFC) | Principal Investigator

Global Analysis of Brain Functional and Metabolic Networks
(2018–2022) | Subproject of Shanghai Municipal Science and Technology Major Project | Principal Investigator

Memberships

Organization for Human Brain Mapping (OHBM) (since 2022)

Institute of Electrical and Electronics Engineers (IEEE) (since 2021)

American Association for the Advancement of Science (AAAS) (since 2016)

International Society for Magnetic Resonance (ISMRM) (since 2010)

Top Notable Publications

Zhang, Xiao-Yong et al. “HiFi-Syn: Hierarchical granularity discrimination for high-fidelity synthesis of MR images with structure preservation.” Medical Image Analysis, November 2024. DOI: 10.1016/j.media.2024.103390

Zhang, Xiao-Yong et al. “Resting State Brain Networks under Inverse Agonist versus Complete Knockout of the Cannabinoid Receptor 1.” ACS Chemical Neuroscience, April 17, 2024. DOI: 10.1021/acschemneuro.3c00804

Authors. “Benchmarking spatial clustering methods with spatially resolved transcriptomics data.” Nature Methods, April 2024. DOI: 10.1038/s41592-024-02215-8

Authors. “A neural signature for the subjective experience of threat anticipation under uncertainty.” Nature Communications, February 20, 2024. DOI: 10.1038/s41467-024-45433-6

Authors. “A Convolutional Neural Network Model for Distinguishing Hemangioblastomas From Other Cerebellar-and-Brainstem Tumors Using Contrast-Enhanced MRI.” Journal of Magnetic Resonance Imaging, 2024. DOI: 10.1002/jmri.29230

Zhang, Xiao-Yong et al. “CQformer: Learning Dynamics Across Slices in Medical Image Segmentation.” IEEE Transactions on Medical Imaging, 2024. DOI: 10.1109/TMI.2024.3477555

Authors. “A-GCL: Adversarial graph contrastive learning for fMRI analysis to diagnose neurodevelopmental disorders.” Medical Image Analysis, December 2023. DOI: 10.1016/j.media.2023.102932

Authors. “Downregulation of mGluR1-mediated signaling underlying autistic-like core symptoms in Shank1 P1812L-knock-in mice.” Translational Psychiatry, October 25, 2023. DOI: 10.1038/s41398-023-02626-9

Authors. “A neural signature for the subjective experience of threat anticipation under uncertainty.” Preprint, September 22, 2023. DOI: 10.1101/2023.09.20.558716

Conclusion

Professor Xiao-Yong Zhang’s extensive research in MRI, deep learning diagnostics, and successful collaborations place him as an exemplary candidate for the Research for Best Researcher Award. His contributions to medical imaging innovation, demonstrated research leadership, and commitment to interdisciplinary collaborations reflect the award’s values and criteria.