Assist Prof Dr. Huiyun Zhang | Deep learn Awards | Best Researcher Award
Assist Prof Dr. Huiyun Zhang, Henan University, China
Dr. Huiyun Zhang holds an M.S. and Ph.D. in Computer Application Technology and Pattern Recognition and Intelligence Systems, respectively, from Qinghai Normal University. She is currently an Assistant Professor at the School of Software, Henan University, China. Dr. Zhang’s research focuses on deep learning and speech emotion recognition (SER), where she has developed advanced models like MA-CapsNet-DA and CENN, integrating capsule networks, attention mechanisms, and Bi-LSTM to enhance SER accuracy. Her previous role as a research assistant at Baylor University provided valuable interdisciplinary experience. With over 20 publications in top-tier journals, Dr. Zhang has made significant contributions to the field, addressing challenges such as overfitting and model robustness. Her work, combined with her commitment to mentoring and interdisciplinary collaboration, underscores her impactful role in advancing both research and education.
Professional Profile:
Orcid
Suitability for the Award
- Innovative Research:
- Dr. Zhang’s development of advanced deep learning models for SER represents significant innovation. Her work on MA-CapsNet-DA and CENN addresses critical challenges in speech emotion recognition, enhancing the accuracy and robustness of these systems.
- Research Impact:
- Her publications in reputable journals and conferences reflect her substantial contributions to the field of deep learning and SER. Her research has practical implications for emotion recognition technology, which is increasingly relevant in various applications.
- Leadership and Collaboration:
- Her experience as an Assistant Professor and her role in interdisciplinary research collaborations underscore her leadership and influence in the field. Her work at Baylor University and Henan University demonstrates her commitment to advancing research and fostering academic growth.
- Educational Contributions:
- Dr. Zhang’s involvement in mentoring and educational projects highlights her dedication to advancing knowledge and supporting the next generation of researchers in artificial intelligence and machine learning.
Summary of Qualifications
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Educational Background:
- M.S. in Computer Application Technology (Qinghai Normal University, 2020).
- Ph.D. in Pattern Recognition and Intelligence Systems (Qinghai Normal University, 2024).
- Her educational background reflects a strong foundation in both technology and computer science, culminating in advanced research in pattern recognition and intelligence systems.
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Professional Experience:
- Assistant Professor, School of Software, Henan University, China.
- Research Assistant, Data Science and Artificial Intelligence Program, Baylor University, USA (one year).
- Her current role as an Assistant Professor involves advancing research in deep learning and speech emotion recognition (SER). Her previous research assistantship at Baylor University provided valuable interdisciplinary experience.
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Research Focus and Contributions:
- Dr. Zhang’s research is centered on speech emotion recognition (SER), deep learning, and data science. She has developed innovative models such as MA-CapsNet-DA and CENN, which integrate capsule networks, attention mechanisms, and Bi-LSTM to enhance SER accuracy.
- Her work addresses challenges such as overfitting and model robustness, contributing novel metrics and techniques to improve SER systems.
- Published over 20 papers in top-tier journals including Expert Systems with Applications and Knowledge-Based Systems, reflecting her significant impact in her field.
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Contributions to Research and Development:
- Dr. Zhang’s innovations in deep learning architectures for SER, including capsule networks and attention mechanisms, are cutting-edge contributions that advance the field.
- Her role as a visiting scholar and collaboration with Baylor University have broadened her research perspectives and fostered interdisciplinary projects.
Publication Top Notes:
“An Improved Capsule Network for Speech Emotion Recognition” (2022), a book chapter in Communications in Computer and Information Science.
“Research on Speech Emotion Recognition Method Based A-CapsNet” (2022), published in Applied Sciences.
“Attention-Based Convolution Skip Bidirectional Long Short-Term Memory Network for Speech Emotion Recognition” (2021), published in IEEE Access.
These publications demonstrate her advanced research in SER and deep learning models, with notable contributions to improving recognition accuracy and model performance.
Conclusion
Assistant Prof. Dr. Huiyun Zhang is highly suitable for the Best Researcher Award due to her significant contributions to speech emotion recognition and deep learning. Her innovative research, extensive publication record, and active role in academic and community engagement demonstrate her excellence and impact in her field. Dr. Zhang’s work not only advances theoretical understanding but also addresses practical challenges in emotion recognition technology, making her an outstanding candidate for this prestigious award.