Yueyang Zheng | Artificial Intelligence | Best Researcher Award

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Mr. Yueyang Zheng | Artificial Intelligence | Best Researcher Award

Student at Qingdao University of Science and Technology, China

yueyang zheng is a student at qingdao university of science and technology, specializing in sound event detection (SED). Their research focuses on recognizing sound events in audio, including detecting overlapping occurrences, known as polyphonic event detection. Passionate about audio signal processing, they are dedicated to advancing machine learning techniques for improved accuracy in real-world acoustic environments. With a strong technical foundation and keen interest in artificial intelligence, yueyang aims to contribute innovative solutions to SED challenges. Their academic journey is driven by curiosity and a commitment to enhancing audio analysis through cutting-edge computational methods. 🚀🎶🔍

Professional Profile

Education & Experience 🎓📚

  • 🎓 Qingdao University of Science and Technology – Pursuing studies in sound event detection
  • 🎧 Research Focus – Specialized in polyphonic sound event detection
  • 🖥️ Machine Learning & AI – Implementing computational techniques for audio processing
  • 🔍 Signal Processing – Enhancing SED accuracy using advanced methodologies

Professional Development 🚀📖

yueyang zheng is actively engaged in research and development in sound event detection (SED), focusing on polyphonic event detection where multiple sounds overlap. Their work involves applying deep learning techniques, neural networks, and signal processing strategies to improve recognition accuracy. Constantly learning, they participate in academic conferences, workshops, and online courses to stay updated on the latest advancements in audio AI. With hands-on experience in machine learning frameworks and sound classification models, yueyang is committed to pushing the boundaries of SED. Their goal is to contribute to real-world applications such as environmental monitoring, smart devices, and audio surveillance. 🎶📊🖥️

Research Focus 🔬🎵

yueyang zheng’s research is centered on Sound Event Detection (SED), particularly in recognizing overlapping sound events (polyphonic event detection). Their interests lie in:

  • 🤖 Deep Learning in Audio Processing – Leveraging AI models for improved sound recognition
  • 🔊 Acoustic Scene Analysis – Understanding complex sound environments
  • 🛠️ Neural Network Architectures – Developing models for real-time event detection
  • 📡 Real-world Applications – Implementing SED in smart devices, security, and healthcare
  • 🎤 Speech & Environmental Sound Processing – Enhancing automated sound analysis in noisy environments

Awards & Honors 🏆🎖️

  • 🏅 Best Student Research Award – Recognized for outstanding contributions to sound event detection
  • 🏆 Academic Excellence Scholarship – Honored for top performance in AI and machine learning studies
  • 🎤 Best Paper Presentation – Awarded at a conference for innovative approaches in audio recognition
  • 📚 Research Grant Recipient – Received funding support for SED-related research
  • 🥇 Hackathon Winner – Secured first place in an AI-based audio processing competition

Publication Top Notes

  • Title: ASiT-CRNN: A method for sound event detection with fine-tuning of self-supervised pre-trained ASiT-based model
  • Authors: Yueyang Zheng, Rui Zhang, Shukui Atito, Shiqing Yang, Wei Wang, Yuning Mei
  • Journal: Digital Signal Processing
  • Year: 2025
  • DOI: 10.1016/j.dsp.2025.105055
  • ISSN: 1051-2004
  • Abstract: This paper discusses the ASiT-CRNN model, designed for sound event detection. It leverages fine-tuning of a self-supervised pre-trained ASiT-based model, which enhances the performance of sound event recognition tasks. The authors explore advanced methods for sound event detection, improving both accuracy and computational efficiency in real-world applications.

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.