I am Menghui Zhou, a second-year PhD student in the Pervasive Computing group at the University of Sheffield, UK, working under the supervision of Prof. Po Yang. I hold a bachelor’s degree from the School of Computer Science and Engineering at Sun Yat-sen University, and a master’s degree from the School of Software at Yunnan University, where I worked closely with Prof. Yun Yang and Prof. Po Yang.
My research primarily focuses on interpretable machine learning and its applications in healthcare and smart agriculture.
Please drop me an email if you are interested in collaborating with me.
🔥 News
- 2025.05: 🎉🎉 One paper was accepted by the journal Engineering Applications of Artificial Intelligence.
- 2024.12: 🎉🎉 Four papers were accepted by the International Conference on Bioinformatics and Biomedicine (BIBM).
📝 Selected Publications
As the First Author:
Menghui Zhou, Xulong Wang, Tong Liu, Yun Yang, Po Yang
- IEEE Transactions on Knowledge and Data Engineering (TKDE), 2024
- This paper proposes a novel multi-task learning framework, MAGPP, which integrates an automatically learned temporal relation graph and sparse group Lasso to improve Alzheimer’s disease progression prediction using MRI data.
Automatic Temporal Relation in Multi-Task Learning
Menghui Zhou, Po Yang
- ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2023
- This paper proposes AutoTR, a novel automatic temporal relation mechanism for multi-task learning that directly learns complex and asymmetric temporal relations between tasks from data leading to improved prediction performance and high efficiency.
Robust Temporal Smoothness in Multi-Task Learning
Menghui Zhou, Yu Zhang, Yun Yang, Tong Liu, Po Yang
- AAAI Conference on Artificial Intelligence (AAAI), 2023
- The paper proposes two Robust Temporal Smoothness (RoTS) frameworks for multi-task learning that jointly capture temporal smoothness across tasks and detect outlier tasks, outperforming traditional smoothness-based methods without increasing computational complexity.
BIBM 2024Learning Interpretable Continuous Representation for Alzheimer’s Disease Classification;
Menghui Zhou, Mingxia Wang, Yu Zhang, Zhipeng Yuan, Vitaveska Lanfranchi, Po Yang;
Published in 2024 IEEE International Conference on Bioinformatics and BiomedicineNCA 2023Efficient multi-task learning with adaptive temporal structure for progression prediction;
Menghui Zhou, Yu Zhang, Tong Liu, Yun Yang, Po Yang;
Published in Neural Computing and ApplicationsCIKM 2022Multi-task Learning with Adaptive Global Temporal Structure for Predicting Alzheimer’s Disease Progression;
Menghui Zhou, Yu Zhang, Tong Liu, Yun Yang, Po Yang;
Published in The 31st ACM International Conference on Information & KnowledgeMSN 2021Modeling disease progression flexibly with nonlinear disease structure via multi-task learning;
Menghui Zhou, Xulong Wang, Yun Yang, Fengtao Nan, Yu Zhang, Jun Qi, Po Yang;
Published in The 17th International Conference on Mobility, Sensing and Networking
As the Corresponding Author:
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EAAI 2025Joint image synthesis and fusion with converted features for Alzheimer’s disease diagnosis;
Zhaodong Chen, Mingxia Wang, Fengtao Nan, Yun Yang, Shunbao Li, Menghui Zhou*, Jun Qi, Hanwen Wang, Po Yang*;
Published in Engineering Applications of Artificial Intelligence -
BIBM 2024Adaptive Multi-Cognitive Objective Temporal Task Approach for Predicting AD Progression;
Xuanhan Fan, Menghui Zhou*, Yu Zhang, Jun Qi, Yun Yang, Po Yang*;
Published in 2024 IEEE International Conference on Bioinformatics and Biomedicine -
KBS 2024Informative relationship multi-task learning: Exploring pairwise contribution across tasks’ sharing knowledge;
Xiangchao Chang, Menghui Zhou*, Xulong Wang, Yun Yang, Po Yang*;
Published in Knowledge-Based Systems
🎖 Honors and Awards
- 2024 BIBM Travel Grant
- 2023 EPSRC Scholarship, UK
- 2022 China National Scholarship
