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

Biography

I am a Lecturer (Assistant Professor) at the University of Glasgow, 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.

Previously, 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 have also been a visiting PhD student at the MINE lab of KAUST.

My research topics includes, Natural Language Processing, Information Retrieval, LLMs, AI Agents, as well as Knowledge (Graphs) Extraction, Representation & Reasoning Learning, particularly within BioMedical applications (AI4Biomedicine).

Currently, I am co-leading the Glasgow AI4BioMed Lab, where we work on natural language processing, knowledge graphs, language models, and more to extract and infer biomedical knowledge. If you are interested in collaborating or pursuing a PhD with me, please refer to this post for more details.

For a list of publications please see Google Scholar.
Personal website: https://mengzaiqiao.github.io/

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
AI Agents
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: 37.

2024

Fang, J., Meng, Z. and Macdonald, C. (2024) TRACE the Evidence: Constructing Knowledge-Grounded Reasoning Chains for Retrieval-Augmented Generation. In: Empirical Methods in Natural Language Processing Conference 2024, Miami, FL, USA, 12-16 Nov 2024, (Accepted for Publication)

Zhang, M., Meng, Z. and Collier, N. (2024) Can We Instruct LLMs to Compensate for Position Bias? In: Empirical Methods in Natural Language Processing Conference 2024, Miami, FL, USA, 12-16 Nov 2024, (Accepted for Publication)

Meng, Z., Liu, S., Liang, S., Jani, B. and Meng, Z. (2024) Heterogeneous biomedical entity representation learning for gene-disease association prediction. Briefings in Bioinformatics, 25(5), bbae380. (doi: 10.1093/bib/bbae380) (PMID:39154194) (PMCID:PMC11330343)

Yi, X., Liu, S., Wu, Y., McCloskey, D. and Meng, Z. (2024) BPP: a platform for automatic biochemical pathway prediction. Briefings in Bioinformatics, 25(5), bbae355. (doi: 10.1093/bib/bbae355) (PMID:39082653) (PMCID:PMC11289738)

Long, Z. , Zhuang, L., Killick, G., Aragon-Camarasa, G. , Meng, Z. and Mccreadie, R. (2024) CLCE: An Approach to Refining Cross-Entropy and Contrastive Learning for Optimized Learning Fusion. In: 27th European Conference on Artificial Intelligence (ECAI-2024), Santiago de Compostela, Spain, 19-24 Oct 2024, (Accepted for Publication)

Zhang, X., Meng, Z. , Lever, J. and Ho, E. S.L. (2024) Gla-AI4BioMed at RRG24: Visual Instruction-tuned Adaptation for Radiology Report Generation. In: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), 23rd BioNLP Workshop, Bangkok, Thailand, 16 August 2024, (Accepted for Publication)

Meng, Z., Meng, Z. and Ounis, I. (2024) FusionDTI: Fine-grained Binding Discovery with Token-level Fusion for Drug-Target Interaction. 5th AI for Science workshop: Scaling in AI for SCientific Discovery at The 41st International Conference on Machine Learning, Vienna, Austria, 26-27 July 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, 56(6), pp. 1-42. (doi: 10.1145/3643806)

Fang, J., Meng, Z. and Macdonald, C. (2024) REANO: Optimising Retrieval-Augmented Reader Models through Knowledge Graph Generation. In: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand, 11-16 Aug 2024, (Accepted for Publication)

Frisoni, G., Cocchieri, A., Presepi, A., Moro, G. and Meng, Z. (2024) To Generate or to Retrieve? On the Effectiveness of Artificial Contexts for Medical Open-Domain Question Answering. In: 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024), Bangkok, Thailand, 11-16 August 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, pp. 5275-5279. ISBN 9798350344851 (doi: 10.1109/ICASSP48485.2024.10447982)

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)

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)

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, pp. 3880-3885. ISBN 9798400701245 (doi: 10.1145/3583780.3615252)

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 Wed Nov 20 20:33:13 2024 GMT.

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