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.

 

 

 

 

 

Eman Aldakheel | Artificial Intelligence | Best Researcher Award

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Assist Prof Dr. Eman Aldakheel | Artificial Intelligence | Best Researcher Award

Scopus Profile

Orcid Profile

Educational Details:

Dr. Eman Aldakheel holds a Doctor of Philosophy in Computer Science from the University of Illinois at Chicago, where her dissertation, titled “Deadlock Detector and Solver (DDS),” focused on developing solutions for deadlock issues in computer systems. She earned her Master of Science in Computer Science from Bowling Green State University in Ohio, with a thesis titled “A Cloud Computing Framework for Computer Science Education,” highlighting her interest in leveraging technology for educational advancement. Dr. Aldakheel completed her Bachelor of Science in Computer Science with Honors from Imam Abdulrahman bin Faisal University in Dammam, Saudi Arabia, laying the foundation for her career in academia and research.

Academic Experience:

Dr. Eman Aldakheel has an extensive teaching and training background, starting as an instructor at the New Horizons Institute in Khobar, Saudi Arabia, in 2007, where she trained students on ICDL and IC3 certifications and taught various computer-related courses. She later joined Imam Abdulrahman bin Faisal University (formerly Dammam University) as an instructor, teaching basic computer skills and Microsoft Office applications to students in the Geography department. She also taught computer basics to girls at Riyadh Al-Islam Schools, working with students from elementary to high school levels. From 2012 to 2020, Dr. Aldakheel served as a lecturer at Princess Nourah Bint Abdulrahman University, where she contributed as a research assistant on software engineering projects and taught object-oriented programming. Since Fall 2020, she has been an Assistant Professor at the same institution, teaching various computer science courses ranging from programming to natural language processing. Dr. Aldakheel effectively adapted to remote teaching tools like Blackboard, Teams, and Zoom during the COVID-19 pandemic, ensuring uninterrupted learning for her students.

Honors and Awards:

Dr. Eman Aldakheel has actively participated in prestigious academic workshops and conferences, including the CRA-Women Grad Cohort Workshop, which supports the professional development of women in computing. Her academic achievements have earned her multiple travel awards, including ACM’s SRC (Student Research Competition) Travel Award and the HPDC (High Performance Distributed Computing) Travel Award, both of which provided her with opportunities to present her research and engage with global experts in the field. These accolades reflect her commitment to advancing her knowledge and contributing to the broader academic community.

Service Activities:

Dr. Eman Aldakheel has played a pivotal role in fostering the growth and development of talented students at Princess Nourah Bint Abdulrahman University. She has been actively involved in planning programs and activities aimed at nurturing high-achieving students, ensuring they receive the support and opportunities needed to excel. Dr. Aldakheel designed and built the foundation for the “Foundations of Programming” (GN 044) course, recording its lectures to enhance learning accessibility. Additionally, she supervises the College of Computer and Information student magazine, encouraging student participation in scholarly activities. Her involvement extends to various committees, where she serves as a judge or supervisor for hackathons, contributing her expertise to inspire innovation and creativity among students.

Granted Projects:

Dr. Eman Aldakheel is actively involved in several significant research projects. In 2023, she contributed to the “Researchers Supporting Project” at Princess Nourah Bint Abdulrahman University, under project number PNURSP2023R409. She is also leading two research initiatives funded by the Deputyship for Research & Innovation, Ministry of Education in Saudi Arabia. The first, under project number RI-44-0618, focuses on the “Detection and Identification of Plant Leaf Diseases using YOLOv4,” running from November 2022 to May 2024. The second project, WE-44-0279, explores the “Use of Modern Machine Learning Techniques to Combat Extremism and the Role of Women,” also from November 2022 to May 2024. These projects highlight Dr. Aldakheel’s expertise in machine learning and its application to various fields, from agriculture to social issues.

Top Notable Publications

“Performance of Rime-Ice Algorithm for Estimating the PEM Fuel Cell Parameters”

Authors: Ismaeel, A.A.K., Houssein, E.H., Khafaga, D.S., Aldakheel, E.A., Said, M.

Year: 2024

Journal: Energy Reports

Citations: 3

“Outlier Detection for Keystroke Biometric User Authentication”

Authors: Ismail, M.G., Salem, M.A.-M., El Ghany, M.A.A., Aldakheel, E.A., Abbas, S.

Year: 2024

Journal: PeerJ Computer Science

Citations: 0

“Mobile-UI-Repair: A Deep Learning-Based UI Smell Detection Technique for Mobile User Interface”

Authors: Ali, A., Xia, Y., Navid, Q., Aldakheel, E.A., Khafaga, D.

Year: 2024

Journal: PeerJ Computer Science

Citations: 2

“Enhancing Security and Privacy in Distributed Face Recognition Systems through Blockchain and GAN Technologies”

Authors: Ghani, M.A.N.U., She, K., Rauf, M.A., Aldakheel, E.A., Khafaga, D.S.

Year: 2024

Journal: Computers, Materials and Continua

Citations: 0

“Detection and Identification of Plant Leaf Diseases using YOLOv4”

Authors: Aldakheel, E.A., Zakariah, M., Alabdalall, A.H.

Year: 2024

Journal: Frontiers in Plant Science

Citations: 1

“Performance of the Walrus Optimizer for Solving an Economic Load Dispatch Problem”

Authors: Said, M., Houssein, E.H., Aldakheel, E.A., Khafaga, D.S., Ismaeel, A.A.K.

Year: 2024

Journal: AIMS Mathematics

Citations: 2

“Efficient Analysis of Large-Size Bio-Signals Based on Orthogonal Generalized Laguerre Moments of Fractional Orders and Schwarz–Rutishauser Algorithm”

Authors: Aldakheel, E.A., Khafaga, D.S., Fathi, I.S., Hosny, K.M., Hassan, G.

Year: 2023

Journal: Fractal and Fractional

Citations: 1

“Performance of Osprey Optimization Algorithm for Solving Economic Load Dispatch Problem”

Authors: Ismaeel, A.A.K., Houssein, E.H., Khafaga, D.S., AbdElrazek, A.S., Said, M.

Year: 2023

Journal: Mathematics

Citations: 17

“CyberHero: An Adaptive Serious Game to Promote Cybersecurity Awareness”

Authors: Hodhod, R., Hardage, H., Abbas, S., Aldakheel, E.A.

Year: 2023

Journal: Electronics (Switzerland)

Citations: 3

Carrasquilla, M.D.L., Sun, M., Long, T., Huang, L., & Zheng, Y. (2024). Seismic anisotropy of granitic rocks from a fracture stimulation well at Utah FORGE using ultrasonic measurements. Geothermics, 123, 103129.

Carrasquilla, M.D.L., Parsons, J., Long, T., Zheng, Y., & Han, D.-H. (2023). Ultrasonic measurements of elastic anisotropy of granitic rocks for enhanced geothermal reservoirs. SEG Technical Program Expanded Abstracts, 2023-August, 79–83.

Carrasquilla, M.D.L., Costa, M.D.F.B., Souza, I.J.S., Amanajás, C.E., & Nunes, L.R.A. (2022). Geological, geophysical and mathematical analysis of synthetic bulk density logs around the world – Part II – The use of non-linear regression on empirical parameters estimation. Journal of Applied Geophysics, 206, 104838.

Carrasquilla, M.D.L., Carvalho, C.P., Costa, M.D.F.B., Amanajás, C.E., & Rautino, L. (2022). Geological, geophysical and mathematical analysis of synthetic bulk density logs around the world – Part I – The use of linear regression on empirical parameters estimation. Journal of Applied Geophysics, 204, 104733.