🎓 Education
Dr. Zhonghua Liu pursued his Ph.D. in Pattern Recognition and Intelligent Systems from Nanjing University of Science and Technology 🎓 in 2011, under the guidance of Prof. Zhong Jin. He also holds an M.S. degree in Computer Software and Theory from Xihua University (2005), mentored by Prof. Xinwei Liu. His strong educational foundation has shaped his expertise in artificial intelligence and computational learning.
💼 Experience
Dr. Liu has a diverse and dynamic academic career spanning over two decades. Since July 2023, he has been a Professor at Zhejiang Ocean University 🏛️. Before this, he was a Professor at Henan University of Science and Technology (2021–2023) and an Associate Professor at the same university from 2005 to 2020. His international exposure includes working as a Visiting Scholar at the University of Technology Sydney (2015–2016) 🌏. His research collaborations extend to Xidian University and China Airborne Missile Academy, where he contributed significantly to machine learning and image recognition advancements.
🏆 Awards and Honors
Dr. Liu has received numerous awards for his contributions to academia and research. He was recognized as an Excellent Teacher at Henan University of Science and Technology (2012) 🍎 and received the Second Award for Teaching Quality in 2013. In recognition of his research, he was honored as an Outstanding Postdoctoral Researcher in Henan Province (2013) and was designated Luoyang Youth Academic and Technical Leader in 2014 🏅.
🔬 Research Focus
Dr. Liu specializes in Pattern Recognition, Image Processing, and Machine Learning 📊. His work revolves around transfer learning, domain adaptation, sparse representation, and dimensionality reduction. His research aims to enhance artificial intelligence techniques for image analysis and classification, bridging the gap between theoretical advancements and real-world applications.
🔖 Conclusion
Dr. Zhonghua Liu is a leading researcher and educator in the field of machine learning and pattern recognition. His extensive academic career, research contributions, and funded projects underscore his expertise in subspace learning, sparse representation, and image processing. With a strong international presence, impactful publications, and numerous awards, Dr. Liu continues to shape the landscape of artificial intelligence and computational intelligence research 🏆
📚 Publications
Discriminative transfer regression for low-rank and sparse subspace learning
Engineering Applications of Artificial Intelligence, 2024
DOI: 10.1016/j.engappai.2024.108445
Domain adaptive learning based on equilibrium distribution and dynamic subspace approximation
Expert Systems with Applications, 2024, Vol. 249
DOI: 10.1016/j.eswa.2024.123673
Robust manifold discriminative distribution adaptation for transfer subspace learning
Expert Systems with Applications, 2023, Vol. 238
DOI: 10.1016/j.eswa.2023.122117
Manifold transfer subspace learning based on double relaxed discriminative regression
Artificial Intelligence Review, 2023, Vol. 56(1), pp. 959-981
DOI: 10.1007/s10462-023-10404-7
Discriminative sparse least square regression for semi-supervised learning
Information Sciences, 2023, Vol. 636
DOI: 10.1016/j.ins.2023.118903
Dynamic classifier approximation for unsupervised domain adaptation
Signal Processing, 2023, Vol. 206
DOI: 10.1016/j.sigpro.2023.108915
Robust sparse low-rank embedding for image dimension reduction
Applied Soft Computing, 2021, Vol. 113
DOI: 10.1016/j.asoc.2021.20211129
Structured optimal graph-based sparse feature extraction for semi-supervised learning
Signal Processing, 2020, Vol. 170
DOI: 10.1016/j.sigpro.2020.107456
Discriminative low-rank preserving projection for dimensionality reduction
Applied Soft Computing, 2019, Vol. 85
DOI: 10.1016/j.asoc.2019.105908
Nonnegative low-rank representation-based manifold embedding for semi-supervised learning
Knowledge-Based Systems, 2017, Vol. 136
DOI: 10.1016/j.knosys.2017.07.019