I am a Ph.D. candidate at the Concordia Institute for Information Systems Engineering (CIISE), Concordia University, Montreal, Canada, under the supervision of Prof. Nizar Bouguila, with co-supervision from Dr. Wentao Fan and Dr. Manar Amayri.

My research focuses on machine learning, generative models, clustering, multimodal learning, and representation learning. I am interested in probabilistic and latent-geometry learning for complex data, with recent work on hyperspherical and axial representation learning, deep clustering and neural topic modeling. My work has been published or accepted at venues including KDD, SIGIR, WWW, ICME, ICASSP, BIBM, IJCNN, DSAA, ACM Transactions on Knowledge Discovery from Data, Neural Networks, Expert Systems with Applications, Neurocomputing, and Applied Intelligence.

🔥 News

• 2026.04: 🎉 A paper is accepted by SIGIR 2026
• 2026.03: 🎉 A paper is accepted by IJCNN 2026
• 2026.03: 🎉 Two papers are accepted by ICME 2026
• 2026.01: 🎉 A paper is accepted by ICASSP 2026

📝 Publications

* denotes equal contribution & co-first authorship

2026

• WWW 2026 Multimodal Topic Discovery in Web Media via von Mises–Fisher Mixture Neural Topic Models, D. Guo*, Zhiwen Luo*, N. Bouguila, W. Fan. Proceedings of The Web Conference 2026. (Acceptance rate: 23%)
• ACM TKDD Hyperspherical Representation Learning of Axial Data via Axial VAEs with Watson Distribution, Zhiwen Luo, W. Fan, M. Amayri, N. Bouguila. ACM Transactions on Knowledge Discovery from Data (TKDD).
• Neurocomputing Adaptive Deep Clustering via Disentangled Hyperspherical VAEs With Contrastive Geometry Optimization, Zhiwen Luo, W. Fan, M. Amayri, N. Bouguila. Neurocomputing.
• NN Neural Topic Modeling on Hyperspheres: Spherical Representation Learning with von Mises-Fisher Mixtures, D. Guo*, Zhiwen Luo*, N. Bouguila, W. Fan. Neural Networks.
• JDSA Flexible Priors for Cross-Collection Topic Modeling: An Approach with Generalized Dirichlet and Beta-Liouville Distributions, Zhiwen Luo, W. Fan, M. Amayri, N. Bouguila. International Journal of Data Science and Analytics (JDSA).

2025

• BIBM 2025 BiovMNVTM: A Geometry-Aware Neural Topic Model for Biomedical Text Analysis via von Mises–Fisher Mixtures, D. Guo*, Zhiwen Luo*, N. Bouguila, W. Fan. IEEE International Conference on Bioinformatics and Biomedicine (BIBM 2025). (Acceptance rate: 19.8%)
• KDD 2025 Dynamic Deep Clustering of High-Dimensional Directional Data via Hyperspherical Embeddings with Bayesian Nonparametric Mixtures, Zhiwen Luo, W. Fan, M. Amayri, N. Bouguila. Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2025). (Acceptance rate: 19%).
• NN Disentangled Representation Learning for Multi-View Clustering via von Mises-Fisher Hyperspherical Embedding, Z. Li*, Zhiwen Luo*, N. Bouguila, W. Su, W. Fan. Neural Networks.
• DSAA 2025 High-Dimensional Axial Data Clustering via Watson Mixture Variational Autoencoder, Zhiwen Luo, W. Fan, M. Amayri, N. Bouguila. IEEE DSAA 2025 Machine Learning Journal Track.

2024 and Earlier

• ESWA Parallel Inference for Cross-Collection Latent Generalized Dirichlet Allocation Model and Applications, Zhiwen Luo, M. Amayri, W. Fan, K. E. Ihou, N. Bouguila. Expert Systems with Applications.
• IEA/AIE 2023 A Selective Supervised Latent Beta-Liouville Allocation for Document Classification, Zhiwen Luo, M. Amayri, W. Fan, N. Bouguila. Proceedings of the 36th International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE 2023).
• Applied Intelligence Cross-Collection Latent Beta-Liouville Allocation Model Training with Privacy Protection and Applications, Zhiwen Luo, M. Amayri, W. Fan, N. Bouguila. Applied Intelligence.

🎖 Honors and Awards

• 2024-2028 Fonds de recherche du Québec – Nature et technologies (FRQNT) Doctoral Scholarship
• 2022-2026 Concordia International Tuition Award of Excellence
• 2020 Concordia Merit Scholarship

🧑‍🎨 Academic Service

Regular Reviewer: IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), Pattern Recognition, Engineering Applications of Artificial Intelligence (EAAI), Transactions on SMC: Systems, Neurocomputing, IJCAI, AAAI, SIGIR, ICDM, ECML-PKDD, IJCNN, and other venues.

📖 Educations

• Sep. 2022 – Aug. 2026, Ph.D. in Information and Systems Engineering, Concordia University, Montreal, QC, Canada.
• Sep. 2020 – Aug. 2022, M.A.Sc. in Information Systems Security, Concordia University, Montreal, QC, Canada.
• Aug. 2015 – May 2019, B.Sc. in Computer Science, George Mason University, Fairfax, VA, USA.

💻 Internships

• Sep. 2023 – May 2025, Artificial Intelligence Developer Intern, Mitacs & Nectari, Montreal, Canada.
• Sep. 2021 – Sep. 2022, Artificial Intelligence Developer Intern, Mitacs & Reelcruit, Montreal, Canada.
• Oct. 2018 – May 2019, Web Developer Intern, ZTEICE Technology Co. Ltd., Shenzhen, China.