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I am currently a research fellow at City University of Hong Kong (Dongguan). I obtained my PhD degree from the Department of Computer Science at City University of Hong Kong under the supervison of Prof. Kay Chen Tan, in 2021.
I am leading the AI Healthcare group in Machine Intelligence and Nature-Inspired Computing Lab (MIND).
My research interests lie in Artificial Intelligence, Medical Image Analysis, Bioinformatics, Data Mining, and Machine Learning. I have published 30+ research papers in highly reputable journals and conference proceedings, including IEEE TPAMI/TNNLS/TBME/TEVC/TETCI, PLoS CB, BIB, Bioinformatics, BMC Bioinformatics, ACM MM, BIBM, IJCNN.

Email address:  huang.za[at]cityu-dg[dot]edu[dot]cn.​
Google Scholar Page
ORCID iD: 0000-0001-9974-148X

Recent News

  • [2024.07] One paper on causal inference for medical image classification is accepted by ACM MM, see you in ​Melbourne, Australia]

  • [2024.03] One paper on spatiotemporal hybrid attentive graph network for CAD is accepted by IEEE TETCI​

  • [2024.03] One paper on heterogeneous structured federated learning is accepted by IJCNN, see you in Yokohama

  • [2024.03] One paper on asymmetric source-free unsupervised domain adaptation is accepted by IEEE CAI, see you in Singapore

  • [2024.03] Pleased to be selected for participating the final contest in CIS Student Grand Competition 2024, whic will be held in WCCI

  • [2023.12] Pleased to be appointed as an Associate Editor for IEEE Transactions on Cognitive and Developmental Systems (IEEE TCDS)

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Research Overview

AI healthcare aims to revolutionize various aspects of the healthcare industry, including computer-aided diagnosis, medical image analysis, and big data for personalized healthcare.

Selected Publications

  1. Z.-A. Huang, R. Liu, Z. Zhu, K. C. Tan, Multitask Learning for Joint Diagnosis of Multiple Mental Disorders in Resting-State fMRI, IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2022.3225179, 2022 (Early Access)

  2. Z.- A. Huang, Y. Hu, R. Liu, X. Xue, Z. Zhu, L. Song, K. C. Tan, Federated Multi-Task Learning for Joint Diagnosis of Multiple Mental Disorders on MRI Scans. IEEE Transactions on Biomedical Engineering, vol. 70, no. 4, pp. 1137-1149, 2022

  3. Z.-A. Huang, Z. Zhu, C. H. Yau, K. C. Tan, Identifying autism spectrum disorder from resting-state fMRI using deep belief network, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 7, pp. 2847-2861, 2020

  4. Z.-A. Huang, J. Zhang, Z. Zhu, E. Q. Wu, K. C. Tan, Identification of Autistic Risk Candidate Genes and Toxic Chemicals via Multilabel Learning, IEEE Transactions on Neural Networks and Learning Systems, vol. 32, no. 9, pp. 3971-3984, 2020

  5. Y. Hu, Z.-A. Huang, R. Liu, X. Xue, X. Sun, L, Song, K. C. Tan, Source Free Semi-Supervised Transfer Learning for Diagnosis of Mental Disorders on fMRI Scans, IEEE Transactions on Pattern Analysis and Machine Intelligence, doi: 10.1109/TPAMI.2023.3298332, 2023 (Early Access)

  6. R. Liu, Z.-A. Huang*(Correspondence), Y. Hu, Z. Zhu, K.-C. Wong, K. C. Tan, Spatial–Temporal Co-Attention Learning for Diagnosis of Mental Disorders From Resting-State fMRI Data, IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2023.3243000, 2023 (Early Access)

  7. R. Liu, Z.-A. Huang*(Correspondence), Y. Hu, Z. Zhu, K.-C. Wong, K. C. Tan, Attention-like Multimodality Fusion with Data Augmentation for Diagnosis of Mental Disorders using MRI, IEEE Transactions on Neural Networks and Learning Systems, doi: 10.1109/TNNLS.2022.3219551, 2022 (Early Access)

  8. M. Yang, Z.-A. Huang# (Equal contributions), W. Zhou, J. Ji, J. Zhang, S. He, Z. Zhu, MIX-TPI: A flexible prediction framework for TCR-pMHC interactions based on multimodal representations, Bioinformatics, btad475, 2023

  9. M. Yang#, Z.-A. Huang# (Equal contributions), W. Gu, K. Han, W. Pan, X. Yang, Z. Zhu, Prediction of biomarker–disease associations based on graph attention network and text representation. Briefings in Bioinformatics, vol. 23, no. 5, article no. bbac298, 2022

  10. Z.-H, You#, Z.-A. Huang# (Equal contributions), Z. Zhu, G.-Y. Yan, Z.-W. Li, Z. Wen, and X. Chen, PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction, PLoS Computational Biology, vol. 13, no. 3, artical no. e1005455, 2017 (selected as ESI Highly Cited Paper)

  11. Y.-A. Huang, K. C. C. Chan, Z.-H. You, P. Hu, L. Wang, Z.-A. Huang* (correspondence), Predicting microRNA–disease associations from lncRNA–microRNA interactions via Multiview Multitask Learning, Briefings in Bioinformatics, bbaa133, 2020 

  12. Z.-A. Huang, Z. Wen, Q. Deng, Y. Chu, Y. Sun, and Z. Zhu, LW-FQZip 2: a parallelized reference-based compression of FASTQ files, BMC Bioinformatics, vol. 18, no. 1, pp. 179:1-179:8, 2017

  13. Z.-A. Huang, X. Chen, Z. Zhu, H. Liu, G.-Y. Yan, Z.-H. You, and Z. Wen, PBHMDA: Path-based human microbe-disease association prediction, Frontiers in Microbiology, vol. 8, article no. 233, 2017

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