Dr Zaiqiao Meng

  • Lecturer (School of Computing Science)

telephone: 01413304271
email: Zaiqiao.Meng@glasgow.ac.uk

220B Sir Alwyn Williams Building, University of Glasgow, Glasgow, G12 8QN

Import to contacts

ORCID iDhttps://orcid.org/0000-0001-5374-0318

Biography

I currently hold the position of Lecturer (Assistant Professor) at the University of Glasgow, situated within the esteemed Information Retrieval Group and IDA section of the School of Computing Science. Additionally, I serve as an Affiliated Lecturer at the Language Technology Lab (LTL) at the University of Cambridge.

In my previous roles, I conducted research as a Postdoctoral Researcher at the Language Technology Lab (LTL) of the University of Cambridge and as a Postdoctoral Researcher at the Information Retrieval group of the University of Glasgow. 

I obtained my PhD in computer science from Sun Yat-sen University (SYSU) in December 2018. I also have been a visiting PhD student at the MINE lab of KAUST.
 
Currently, I am co-leading the Glasgow AI4BioMed Lab, focusing on research topics in Natural Language Processing, with a specific emphasis on LLMs, as well as Knowledge Extraction, Representation & Reasoning Learning, particularly within BioMedical applications. If you are interested in collaborating or pursuing a PhD with me, please refer to this post for more details.
 

 

Research interests

My research focuses on the intersection of machine learning, knowledge graphs, and natural language processing, with a current emphasis on biomedical applications.

  • Machine Learning
  • Geometric Deep Learning (Graph Neural Networks)
  • Knowledge Graph Construction, Utilisation and Reasoning
  • Natural Language Processing
  • Large Language Models
  • Recommender Systems
  • Healthcare Related Applications (e.g. Clinical Summarisation, Disease Outbreak Surveillance and Drug Discovery)

Publications

List by: Type | Date

Jump to: 2024 | 2023 | 2022 | 2021 | 2020 | 2019
Number of items: 28.

2024

Arslan Manzoor, M., AlBarri, S., Xian, Z., Meng, Z. , Nakov, P. and Liang, S. (2024) Multimodality representation learning: a survey on evolution, pretraining and its applications. ACM Transactions on Multimedia Computing, Communications, and Applications, 20(3), 74. (doi: 10.1145/3617833)

Tang, S., Meng, Z. and Liang, S. (2024) Dynamic co-embedding model for temporal attributed networks. IEEE Transactions on Neural Networks and Learning Systems, 35(3), pp. 3488-3502. (doi: 10.1109/TNNLS.2022.3193564) (PMID:35900994)

Fang, J., Meng, Z. and Macdonald, C. (2024) Enhancing Late Interaction with Informative Entities for Passage Retrieval. 46th European Conference on Information Retrieval (ECIR 2024): The First Knowledge-Enhanced Information Retrieval Workshop (KEIR@ECIR 2024), Glasgow, Scotland, 24-28 March 2024. (Accepted for Publication)

Chen, G., Li, X., Meng, Z. , Liang, S. and Bing, L. (2024) CLEX: Continuous Length Extrapolation for Large Language Models. In: 12th International Conference on Learning Representations, Vienna, Austria, 7-11 May 2024, (Accepted for Publication)

Cao, J., Fang, J., Meng, Z. and Liang, S. (2024) Knowledge graph embedding: a survey from the perspective of representation spaces. ACM Computing Surveys, (doi: 10.1145/3643806) (Early Online Publication)

Chen, X., Wang, Y., Fang, J., Meng, Z. and Liang, S. (2024) Heterogeneous graph contrastive learning with metapath-based augmentations. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(1), pp. 1003-1014. (doi: 10.1109/TETCI.2023.3322341)

Long, Z. , McCreadie, R. , Aragon Camarasa, G. and Meng, Z. (2024) LACVIT: A Label-aware Contrastive Fine-tuning Framework for Vision Transformers. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, 14-19 Apr 2024, (Accepted for Publication)

2023

Fu, Z., Zhang, M., Meng, Z. , Shen, Y., Buckeridge, D. and Collier, N. (2023) BAND: Biomedical Alert News Dataset. In: 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada, 20-27 February 2024, (Accepted for Publication)

Cao, P., Wang, Y., Zhang, Q. and Meng, Z. (2023) GenKIE: Robust Generative Multimodal Document Key Information Extraction. In: 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, 06-10 Dec 2023, pp. 14702-14713. (doi: 10.18653/v1/2023.findings-emnlp.979)

Fu, Z., Su, Y., Meng, Z. and Collier, N. (2023) Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization. In: 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, 06-10 Dec 2023, pp. 14621-14635. (doi: 10.18653/v1/2023.emnlp-main.903)

Fang, J., Meng, Z. and Macdonald, C. (2023) KGPR: Knowledge Graph Enhanced Passage Ranking. In: 32nd ACM International Conference on Information and Knowledge Management, Birmingham, UK, 21-25 Oct 2023, (Accepted for Publication)

Wu, B., Meng, Z. and Liang, S. (2023) Dynamic Bayesian contrastive predictive coding model for personalized product search. ACM Transactions on the Web, (doi: 10.1145/3609225) (Early Online Publication)

Fang, J., Wang, X., Meng, Z. , Xie, P., Huang, F. and Jiang, Y. (2023) MANNER: A Variational Memory-Augmented Model for Cross Domain Few-Shot Named Entity Recognition. In: 61st Annual Meeting of the Association for Computational Linguistics (ACL '23), Toronto, Canada, 9-14 July 2023, (doi: 10.18653/v1/2023.acl-long.234)

Liu, S., Meng, Z. , Macdonald, C. and Ounis, I. (2023) Graph neural pre-training for recommendation with side information. ACM Transactions on Information Systems, 41(3), 74. (doi: 10.1145/3568953)

Yuan, Z., Hu, S., Vulic, I., Korhonen, A. and Meng, Z. (2023) Can Pretrained Language Models (Yet) Reason Deductively? In: 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), Dubrovnik, Croatia, 2-6 May 2023, pp. 1447-1462. (doi: 10.18653/v1/2023.eacl-main.106)

Wang, Y., Chen, X., Fang, J., Meng, Z. and Liang, S. (2023) Enhancing conversational recommendation systems with representation fusion. ACM Transactions on the Web, 17(1), 6. (doi: 10.1145/3577034)

Chen, G., Liu, F., Meng, Z. and Liang, S. (2023) Revisiting Parameter-Efficient Tuning: Are We Really There Yet? In: 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Abu Dhabi, 7-11 Dec 2022, pp. 2612-2626.

2022

Meng, Z. et al. (2022) BioCaster in 2021: automatic disease outbreaks detection from global news media. Bioinformatics, 38(18), pp. 4446-4448. (doi: 10.1093/bioinformatics/btac497) (PMID:35900173) (PMCID:PMC9477518)

Meng, Z. , Liu, F., Shareghi, E., Su, Y., Collins, C. and Collier, N. (2022) Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models. In: 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), Dublin, Ireland, 22-27 May 2022, pp. 4798-4810.

Wang, Y., Xin, X., Meng, Z. , Jose, J. M. , Feng, F. and He, X. (2022) Learning Robust Recommenders Through Cross-Model Agreement. In: ACM Web Conference 2022, Lyon, France, 25-29 April 2022, pp. 2015-2025. ISBN 9781450390965 (doi: 10.1145/3485447.3512202)

Liang, S., Luo, Y. and Meng, Z. (2022) Profiling users for question answering communities via flow-based constrained co-embedding model. ACM Transactions on Information Systems, 40(2), 34. (doi: 10.1145/3470565)

2021

Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I. (2021) Variational Bayesian representation learning for grocery recommendation. Information Retrieval, 24(4-5), pp. 347-369. (doi: 10.1007/s10791-021-09397-1)

2020

Meng, Z. , Mccreadie, R. , Macdonald, C. and Ounis, I. (2020) Exploring Data Splitting Strategies for the Evaluation of Recommendation Models. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 681-686. ISBN 9781450375832 (doi: 10.1145/3383313.3418479)

Meng, Z. et al. (2020) BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 588-590. ISBN 9781450375832 (doi: 10.1145/3383313.3411524)

Huang, H., Meng, Z. and Liang, S. (2020) Recurrent neural variational model for follower-based influence maximization. Information Sciences, 528, pp. 280-293. (doi: 10.1016/j.ins.2020.04.023)

Liu, S., Ounis, I. , Macdonald, C. and Meng, Z. (2020) A Heterogeneous Graph Neural Model for Cold-Start Recommendation. In: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China, 25-30 Jul 2020, pp. 2029-2032. ISBN 9781450380164 (doi: 10.1145/3397271.3401252)

2019

Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I. (2019) Variational Bayesian Context-aware Representation for Grocery Recommendation. In: 13th ACM Conference on Recommender Systems (RecSys19) - CARS 2019 Workshop, Copenhagen, Denmark, 16-20 Sept 2019,

Meng, Z. , Liang, S., Fang, J. and Xiao, T. (2019) Semi-supervisedly Co-embedding Attributed Networks. In: Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 08-14 Dec 2019,

This list was generated on Thu Apr 25 14:50:18 2024 BST.
Jump to: Articles | Conference or Workshop Item | Conference Proceedings
Number of items: 28.

Articles

Arslan Manzoor, M., AlBarri, S., Xian, Z., Meng, Z. , Nakov, P. and Liang, S. (2024) Multimodality representation learning: a survey on evolution, pretraining and its applications. ACM Transactions on Multimedia Computing, Communications, and Applications, 20(3), 74. (doi: 10.1145/3617833)

Tang, S., Meng, Z. and Liang, S. (2024) Dynamic co-embedding model for temporal attributed networks. IEEE Transactions on Neural Networks and Learning Systems, 35(3), pp. 3488-3502. (doi: 10.1109/TNNLS.2022.3193564) (PMID:35900994)

Cao, J., Fang, J., Meng, Z. and Liang, S. (2024) Knowledge graph embedding: a survey from the perspective of representation spaces. ACM Computing Surveys, (doi: 10.1145/3643806) (Early Online Publication)

Chen, X., Wang, Y., Fang, J., Meng, Z. and Liang, S. (2024) Heterogeneous graph contrastive learning with metapath-based augmentations. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(1), pp. 1003-1014. (doi: 10.1109/TETCI.2023.3322341)

Wu, B., Meng, Z. and Liang, S. (2023) Dynamic Bayesian contrastive predictive coding model for personalized product search. ACM Transactions on the Web, (doi: 10.1145/3609225) (Early Online Publication)

Liu, S., Meng, Z. , Macdonald, C. and Ounis, I. (2023) Graph neural pre-training for recommendation with side information. ACM Transactions on Information Systems, 41(3), 74. (doi: 10.1145/3568953)

Wang, Y., Chen, X., Fang, J., Meng, Z. and Liang, S. (2023) Enhancing conversational recommendation systems with representation fusion. ACM Transactions on the Web, 17(1), 6. (doi: 10.1145/3577034)

Meng, Z. et al. (2022) BioCaster in 2021: automatic disease outbreaks detection from global news media. Bioinformatics, 38(18), pp. 4446-4448. (doi: 10.1093/bioinformatics/btac497) (PMID:35900173) (PMCID:PMC9477518)

Liang, S., Luo, Y. and Meng, Z. (2022) Profiling users for question answering communities via flow-based constrained co-embedding model. ACM Transactions on Information Systems, 40(2), 34. (doi: 10.1145/3470565)

Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I. (2021) Variational Bayesian representation learning for grocery recommendation. Information Retrieval, 24(4-5), pp. 347-369. (doi: 10.1007/s10791-021-09397-1)

Huang, H., Meng, Z. and Liang, S. (2020) Recurrent neural variational model for follower-based influence maximization. Information Sciences, 528, pp. 280-293. (doi: 10.1016/j.ins.2020.04.023)

Conference or Workshop Item

Fang, J., Meng, Z. and Macdonald, C. (2024) Enhancing Late Interaction with Informative Entities for Passage Retrieval. 46th European Conference on Information Retrieval (ECIR 2024): The First Knowledge-Enhanced Information Retrieval Workshop (KEIR@ECIR 2024), Glasgow, Scotland, 24-28 March 2024. (Accepted for Publication)

Conference Proceedings

Chen, G., Li, X., Meng, Z. , Liang, S. and Bing, L. (2024) CLEX: Continuous Length Extrapolation for Large Language Models. In: 12th International Conference on Learning Representations, Vienna, Austria, 7-11 May 2024, (Accepted for Publication)

Long, Z. , McCreadie, R. , Aragon Camarasa, G. and Meng, Z. (2024) LACVIT: A Label-aware Contrastive Fine-tuning Framework for Vision Transformers. In: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2024), Seoul, Korea, 14-19 Apr 2024, (Accepted for Publication)

Fu, Z., Zhang, M., Meng, Z. , Shen, Y., Buckeridge, D. and Collier, N. (2023) BAND: Biomedical Alert News Dataset. In: 38th AAAI Conference on Artificial Intelligence (AAAI-24), Vancouver, Canada, 20-27 February 2024, (Accepted for Publication)

Cao, P., Wang, Y., Zhang, Q. and Meng, Z. (2023) GenKIE: Robust Generative Multimodal Document Key Information Extraction. In: 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, 06-10 Dec 2023, pp. 14702-14713. (doi: 10.18653/v1/2023.findings-emnlp.979)

Fu, Z., Su, Y., Meng, Z. and Collier, N. (2023) Biomedical Named Entity Recognition via Dictionary-based Synonym Generalization. In: 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP 2023), Singapore, 06-10 Dec 2023, pp. 14621-14635. (doi: 10.18653/v1/2023.emnlp-main.903)

Fang, J., Meng, Z. and Macdonald, C. (2023) KGPR: Knowledge Graph Enhanced Passage Ranking. In: 32nd ACM International Conference on Information and Knowledge Management, Birmingham, UK, 21-25 Oct 2023, (Accepted for Publication)

Fang, J., Wang, X., Meng, Z. , Xie, P., Huang, F. and Jiang, Y. (2023) MANNER: A Variational Memory-Augmented Model for Cross Domain Few-Shot Named Entity Recognition. In: 61st Annual Meeting of the Association for Computational Linguistics (ACL '23), Toronto, Canada, 9-14 July 2023, (doi: 10.18653/v1/2023.acl-long.234)

Yuan, Z., Hu, S., Vulic, I., Korhonen, A. and Meng, Z. (2023) Can Pretrained Language Models (Yet) Reason Deductively? In: 17th Conference of the European Chapter of the Association for Computational Linguistics (EACL 2023), Dubrovnik, Croatia, 2-6 May 2023, pp. 1447-1462. (doi: 10.18653/v1/2023.eacl-main.106)

Chen, G., Liu, F., Meng, Z. and Liang, S. (2023) Revisiting Parameter-Efficient Tuning: Are We Really There Yet? In: 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP 2022), Abu Dhabi, 7-11 Dec 2022, pp. 2612-2626.

Meng, Z. , Liu, F., Shareghi, E., Su, Y., Collins, C. and Collier, N. (2022) Rewire-then-Probe: A Contrastive Recipe for Probing Biomedical Knowledge of Pre-trained Language Models. In: 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022), Dublin, Ireland, 22-27 May 2022, pp. 4798-4810.

Wang, Y., Xin, X., Meng, Z. , Jose, J. M. , Feng, F. and He, X. (2022) Learning Robust Recommenders Through Cross-Model Agreement. In: ACM Web Conference 2022, Lyon, France, 25-29 April 2022, pp. 2015-2025. ISBN 9781450390965 (doi: 10.1145/3485447.3512202)

Meng, Z. , Mccreadie, R. , Macdonald, C. and Ounis, I. (2020) Exploring Data Splitting Strategies for the Evaluation of Recommendation Models. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 681-686. ISBN 9781450375832 (doi: 10.1145/3383313.3418479)

Meng, Z. et al. (2020) BETA-Rec: Build, Evaluate and Tune Automated Recommender Systems. In: 14th ACM Conference on Recommender Systems (RecSys 2020), 22-26 Sep 2020, pp. 588-590. ISBN 9781450375832 (doi: 10.1145/3383313.3411524)

Liu, S., Ounis, I. , Macdonald, C. and Meng, Z. (2020) A Heterogeneous Graph Neural Model for Cold-Start Recommendation. In: 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2020), Xi'an, China, 25-30 Jul 2020, pp. 2029-2032. ISBN 9781450380164 (doi: 10.1145/3397271.3401252)

Meng, Z. , McCreadie, R. , Macdonald, C. and Ounis, I. (2019) Variational Bayesian Context-aware Representation for Grocery Recommendation. In: 13th ACM Conference on Recommender Systems (RecSys19) - CARS 2019 Workshop, Copenhagen, Denmark, 16-20 Sept 2019,

Meng, Z. , Liang, S., Fang, J. and Xiao, T. (2019) Semi-supervisedly Co-embedding Attributed Networks. In: Thirty-third Conference on Neural Information Processing Systems (NeurIPS 2019), Vancouver, Canada, 08-14 Dec 2019,

This list was generated on Thu Apr 25 14:50:18 2024 BST.

Supervision

  • Dong, Shen
    A Knowledge-Free Language Model for Data-to-Text Generation
  • Fang, Jinyuan
    Adversarial Attacks and Defenses on Multi-Relational Graphs
  • Meng, Zhaohan
    Heterogeneous entity representation learning for knowledge graph in biomedical science
  • Zhang, Xi
    Generative Multi-modal BioMedical Natural Language Modelling

Teaching

  • Recommender Systems (H / M) (COMPSCI4075 / COMPSCI5091 (23-24))
  • Introduction to Data Science and Systems (M) (COMPSCI5089(23-24))
  • Recommender Systems (H / M) (COMPSCI4075 / COMPSCI5091 (22-23))
  • Introduction to Data Science and Systems (M) (COMPSCI5089(22-23)) 
  • Recommender Systems (H / M) (COMPSCI4075 / COMPSCI5091 (21-22))