Dr Mohammed Jameel
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Email
shoaib.jameel@essex.ac.uk -
Location
5A.529, Colchester Campus
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Academic support hours
Tuesday: 12:00 PM until 1:00 PM (Zoom ID: 97561813599)
Profile
Biography
My work revolves around proposing novel computational methods for machine learning with applications to text mining. Specifically, my work has centred around learning low-dimensional representations of natural language text on a large-scale. Among others, I have developed a variety of probabilistic topic models, which have seen applications in text mining and information retrieval, as well as vector space embeddings, which have shown promising results in tasks such as knowledge base completion and commonsense reasoning. You can find more about me here: https://bashthebuilder.github.io/
Qualifications
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PhD The Chinese University of Hong Kong, (2014)
Research and professional activities
Research interests
Information Retrieval (IR)
The goal is to propose novel computational methods for ad-hoc IR using one of these machine learning methods.
Natural Language Processing (NLP)
The goal is to propose novel methods in NLP.
Teaching and supervision
Previous supervision
Degree subject: Computer Science
Degree type: Doctor of Philosophy
Awarded date: 24/4/2023
Publications
Journal articles (14)
Zogan, H., Razzak, I., Jameel, S. and Xu, G., (2024). Hierarchical Convolutional Attention Network for Depression Detection on Social Media and Its Impact During Pandemic. IEEE Journal of Biomedical and Health Informatics. 28 (4), 1815-1823
Kia, MA., Garifullina, A., Kern, M., Chamberlain, J. and Jameel, S., (2024). Question-Driven Text Summarization Using an Extractive-Abstractive Framework. Computational Intelligence. 40 (3)
He, L., Xu, G., Jameel, S., Wang, X. and Chen, H., (2023). Graph-Aware Deep Fusion Networks for Online Spam Review Detection. IEEE Transactions on Computational Social Systems. 10 (5), 2557-2565
Roy, S., Gaur, V., Raza, H. and Jameel, S., (2023). CLEFT: Contextualised Unified Learning of User Engagement in Video Lectures with Feedback. IEEE Access. 11, 17707-17720
Correia, A., Grover, A., Jameel, S., Schneider, D., Antunes, P. and Fonseca, B., (2023). A hybrid human–AI tool for scientometric analysis. Artificial Intelligence Review. 56 (S1), 983-1010
Correia, A., Guimarães, D., Paredes, H., Fonseca, B., Paulino, D., Trigo, L., Brazdil, P., Schneider, D., Grover, A. and Jameel, S., (2023). NLP-Crowdsourcing Hybrid Framework for Inter-Researcher Similarity Detection. IEEE Transactions on Human-Machine Systems. 53 (6), 1017-1026
Zogan, H., Razzak, I., Wang, X., Jameel, S. and Xu, G., (2022). Explainable depression detection with multi-aspect features using a hybrid deep learning model on social media. World Wide Web. 25 (1), 281-304
Kia, MA., Garifullina, A., Kern, M., Chamberlain, J. and Jameel, S., (2022). Adaptable Closed-Domain Question Answering Using Contextualized CNN-Attention Models and Question Expansion. IEEE Access. 10, 45080-45092
Zhou, J., Zogan, H., Yang, S., Jameel, S., Xu, G. and Chen, F., (2021). Detecting Community Depression Dynamics Due to COVID-19 Pandemic in Australia. IEEE Transactions on Computational Social Systems. 8 (4), 982-991
Zhang, JJ., Wang, F-Y., Yuan, Y., Xu, G., Liu, H., Gao, W., Jameel, S., Razzak, I., Eklund, P., Ahmed, S., Qin, R., Li, J., Wang, X., Yang, D-N., Turgut, D., Benslimane, A., Prasad, N. and Chen, K-C., (2021). Guest Editorial Computational Social Systems for COVID-19 Emergency Management and Beyond. IEEE Transactions on Computational Social Systems. 8 (4), 928-929
Benayas, A., Hashempour, R., Rumble, D., Jameel, S. and De Amorim, RC., (2021). Unified Transformer Multi-Task Learning for Intent Classification With Entity Recognition. IEEE Access. 9, 147306-147314
Jameel, S., Lam, W. and Bing, L., (2015). Supervised topic models with word order structure for document classification and retrieval learning. Information Retrieval Journal. 18 (4), 283-330
Bing, L., Jiang, S., Lam, W., Zhang, Y. and Jameel, S., (2015). Adaptive Concept Resolution for document representation and its applications in text mining. Knowledge-Based Systems. 74, 1-13
Bing, L., Lam, W., Wong, T-L. and Jameel, S., (2015). Web Query Reformulation via Joint Modeling of Latent Topic Dependency and Term Context. ACM Transactions on Information Systems. 33 (2), 1-38
Conferences (46)
Alsuhaibani, A., Zogan, H., Razzak, I., Jameel, S. and Xu, G., (2024). IDoFew: Intermediate Training Using Dual-Clustering in Language Models for Few Labels Text Classification
Talebpour, M., Garcia Seco De Herrera, A. and Jameel, S., (2023). Topics in Contextualised Attention Embeddings
Barry, E., Jameel, S. and Raza, H., (2022). Emojional: Emoji Embeddings
Yan, K., Zhang, C., Hou, J., Wang, P., Bouraoui, Z., Jameel, S. and Schockaert, S., (2022). Inferring Prototypes for Multi-Label Few-Shot Image Classification with Word Vector Guided Attention
Yan, K., Bouraoui, Z., Wang, P., Jameel, S. and Schockaert, S., (2021). Few-shot image classification with multi-facet prototypes
Antonio, C., Diogo, G., Dennis, P., Jameel, MS., Daniel, S., Benjamin, F. and Hugo, P., (2021). AuthCrowd: Author Name Disambiguation and Entity Matching using Crowdsourcing
Correia, A., Paulino, D., Paredes, H., Fonseca, B., Jameel, S., Schneider, D. and de Souza, JM., (2021). Scientometric Research Assessment of IEEE CSCWD Conference Proceedings: An Exploratory Analysis from 2001 to 2019
Hamad, Z., Imran, R., Jameel, MS. and Guandong, X., (2021). DepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media
Kun, Y., Zied, B., Ping, W., Jameel, MS. and Steven, S., (2021). Aligning Visual Prototypes with BERT Embeddings for Few-Shot Learning
He, L., Chen, H., Wang, D., Jameel, MS., Yu, P. and Xu, G., (2021). Click-Through Rate Prediction with Multi-Modal Hypergraphs
Correia, A., Fonseca, B., Paredes, H., Chaves, R., Schneider, D. and Jameel, S., (2021). Determinants and Predictors of Intentionality and Perceived Reliability in Human-AI Interaction as a Means for Innovative Scientific Discovery
Jameel, S. and Schockaert, S., (2020). Word and document embedding with VMF-mixture priors on context word vectors
Zihao, F., Bing, L., Wai, L. and Jameel, MS., (2020). Dynamic Topic Tracker for KB-to-Text Generation
Correia, A., Jameel, MS., Schneider, D., Paredes, H. and Fonseca, B., (2020). A Workflow-Based Methodological Framework for Hybrid Human-AI Enabled Scientometrics
Correia, A., Jameel, S., Schneider, D., Fonseca, B. and Paredes, H., (2020). Theoretical underpinnings and practical challenges of crowdsourcing as a mechanism for academic study
Correia, A., Fonseca, B., Paredes, H., Schneider, D. and Jameel, S., (2019). Development of a Crowd-Powered System Architecture for Knowledge Discovery in Scientific Domains
Correia, A., Paredes, H., Schneider, D., Jameel, S. and Fonseca, B., (2019). Towards Hybrid Crowd-AI Centered Systems: Developing an Integrated Framework from an Empirical Perspective
Camacho-Collados, J., Espinosa-Anke, L., Jameel, S. and Schockaert, S., (2019). A Latent Variable Model for Learning Distributional Relation Vectors
Correia, A., Jameel, S., Schneider, D., Fonseca, B. and Paredes, H., (2019). The Effect of Scientific Collaboration on CSCW Research: A Scientometric Study
Jameel, S., Fu, Z., Shi, B., Lam, W. and Schockaert, S., (2019). Word embedding as maximum a posteriori estimation
Jameel, S., Bouraoui, Z. and Schockaert, S., (2018). Unsupervised Learning of Distributional Relation Vectors
Bouraoui, Z., Jameel, S. and Schockaert, S., (2018). Relation induction in word embeddings revisited
JAMEEL, S. and SCHOCKAERT, S., (2017). Modeling Context Words as Regions: An Ordinal Regression Approach to Word Embedding
Shi, B., Lam, W., Jameel, S., Schockaert, S. and Lai, KP., (2017). Jointly Learning Word Embeddings and Latent Topics
Jameel, S., Bouraoui, Z. and Schockaert, S., (2017). MEmbER: Max-Margin Based Embeddings for Entity Retrieval
Jameel, S. and Schockaert, S., (2016). D-GloVe: A feasible least squares model for estimating word embedding densities
Jameel, S. and Schockaert, S., (2016). Entity embeddings with conceptual subspaces as a basis for plausible reasoning
Schockaert, S. and Jameel, S., (2016). Plausible reasoning based on qualitative entity embeddings
Liao, Y., Lam, W., Jameel, S., Schockaert, S. and Xie, X., (2016). Who Wants to Join Me?
Jameel, S., Liao, Y., Lam, W., Schockaert, S. and Xie, X., (2016). Exploring Urban Lifestyles Using a Nonparametric Temporal Graphical Model
Liu, P., Jameel, S., Wu, KK. and Meng, H., (2016). Learning Track Representation and Trends for Conference Analytics
Jameel, S., Lam, W., Schockaert, S. and Bing, L., (2015). A Unified Posterior Regularized Topic Model with Maximum Margin for Learning-to-Rank
Liao, Y., Jameel, S., Lam, W. and Xie, X., (2015). Abstract Venue Concept Detection from Location-Based Social Networks
Jameel, S., Lam, W. and Bing, L., (2015). Nonparametric Topic Modeling Using Chinese Restaurant Franchise with Buddy Customers
Liu, P., Jameel, S., Lam, W., Ma, B. and Meng, H., (2015). Topic modeling for conference analytics
Bing, L., Lam, W., Jameel, S. and Lu, C., (2014). Website Community Mining from Query Logs with Two-Phase Clustering
Jameel, S. and Lam, W., (2013). A Nonparametric N-Gram Topic Model with Interpretable Latent Topics
Jameel, S. and Lam, W., (2013). An unsupervised topic segmentation model incorporating word order
Jameel, S. and Lam, W., (2013). An N-Gram Topic Model for Time-Stamped Documents
Jameel, S., Lam, W. and Qian, X., (2012). Ranking Text Documents Based on Conceptual Difficulty Using Term Embedding and Sequential Discourse Cohesion
Jameel, S., Qian, X. and Lam, W., (2012). N-gram fragment sequence based unsupervised domain-specific document readability
Jameel, S. and Qian, X., (2012). An Unsupervised Technical Readability Ranking Model by Building a Conceptual Terrain in LSI
Jameel, S., Lam, W., Qian, X. and Au Yeung, C-M., (2012). An unsupervised technical difficulty ranking model based on conceptual terrain in the latent space
Jameel, S., Lam, W., Au Yeung, C-M. and Chyan, S., (2011). An unsupervised ranking method based on a technical difficulty terrain
Jameel, MS., Akshat, A. and Singh, CT., (2008). Enhancements in query evaluation and page summarization of The Thinking Algorithm
(2006). Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop on - COLING ACL '06
Thesis dissertation (1)
Abazari Kia, M., (2024). Question‐driven text summarization using an extractive‐abstractive framework
Grants and funding
2021
Multi-Modal Image Style Transfer: Automatically Geo-Localising Reading Material Digital Artwork for Increased Reader Engagement
University of Essex (GCRF)
2020
RoleCatcher AI
Fintex
Contact
Academic support hours:
Tuesday: 12:00 PM until 1:00 PM (Zoom ID: 97561813599)