Research Diaries

My Research Journey  |  Behind the Papers  |  Publications

My Research Journey

A personal journey through my research - highlighting motivations, challenges, methods, and reflections behind each of my published works.

How I Started Research Without a Roadmap

A story from 2007/08

I discuss how research got to me..

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What Made Me Choose Data Mining

A fresh Ph.D. goes hard at students.

Know about my struggling days at SZABIST..

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My First Paper: The Struggles and Lessons

Writing a conference paper

The charm behind writing a conference paper..

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How Freelancing Helped Me Become a Better Researcher

Whats good in being technically strong

Read out how I just dived into data mining..

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How Freelancing Helped Me Become a Better Researcher

Whats good in being technically strong

Read out how I just dived into data mining..

Read more →

Publications

  • Research contributions across years.

Research Interest:

  • Data stream learning, e.g., Concept drift detection, Incremental learning, Imbalanced data classification, Streaming anomaly detection, Online feature selection, Ensemble methods for data streams, Scalable classification algorithms, Time series classification, Class-incremental learning, missing-values analysis, etc.
  • Knowledge Mining, e.g. Information retrieval and search, Information extraction from unstructured data, Knowledge graph construction and analysis, Event detection and tracking in news and social media, pattern extraction,Topic modeling and document clustering etc.

Recent Papers

  • Farooq, H., Usman, M., Chen, H. (2025). MinoRare: Handling Rare Minority Instances in Imbalanced and Drifting Data Streams through Adaptive Instance Weighting Scheme, IEEE Transactions on Big Data, IF: 5.7, doi: https://doi.org/10.1109/TBDATA.2025.3594302
  • Muhammad Usman and Huanhuan Chen(2024). EMRIL: Ensemble method based on ReInforcement Learning for Imbalanced and Drifting Data streams, Neurocomputing, IF: 6.0, https://doi.org/10.1016/j.neucom.2024.128259.
  • Muhammad Usman and Huanhuan Chen(2024). Bin.INI: An Ensemble Approach for Dynamic Data Streams, Expert Systems with Applications, IF: 7.5, https://doi.org/10.1016/j.eswa.2024.124853.
  • Y. Zhu, B. Huang, Y. Fan, M. Usman, and H. Chen(2024). Iterative Polygon Deformation for Building Extraction, IEEE Transactions on Geoscience and Remote Sensing, IF: 7.5, http://dx.doi.org/10.1109/TGRS.2024.3396813.
  • Muhammad Usman and Huanhuan Chen(2024). Intensive Class Imbalance Learning in Drifting Data Streams, IEEE Transactions on Emerging Topics on Computational Intelligence, IF: 5.3, http://dx.doi.org/10.1109/TETCI.2024.3399657.
  • Zaka-Ud-Din Muhammad, Usman Muhammad, Zhangjin Huang, Naijie Gua(2023). MMFIL-Net: Multi-Level and Multi-source Feature Interactive Lightweight Network for Polyp Segmentation. Displays, IF: 3.7, http://dx.doi.org/10.1016/j.displa.2023.102600.
  • Xiangyu Wang, Taiyu Ban, Lyuzhou Chen, Muhammad Usman, Yifeng Guan, Derui Lyu, Jian Cheng, Huanhuan Chen, Cyril Leung, Chunyan Miao (2023). Decentralised Knowledge Graph Evolution via Blockchain. IEEE Transactions on Services Computing, IF: 5.5, http://dx.doi.org/10.1109/TSC.2023.3337873.
  • Buliao Huang, Yunhui Zhu, Muhammad Usman, Huanhuan Chen(2023). Semi-supervised Learning with Missing Values Imputation. Knowledge-Based Systems, IF: 7.2, http://dx.doi.org/10.1016/j.knosys.2023.111171.
  • Usman, M., & Chen, H. (2023). Pro-IDD: Pareto-based ensemble for imbalanced and drifting data streams. Knowledge-Based Systems, 111103, IF: 7.2, http://dx.doi.org/10.1016/j.knosys.2023.111103.
  • Wang, X., Ban, T., Chen, L., Usman, M., Wu, T., Chen, Q., & Chen, H. (2023). A distribution-based representation of Knowledge Quality. Knowledge-Based Systems, 111054, IF: 7.2, https://doi.org/10.1016/j.knosys.2023.111054.
  • Zhou, X., Chen, A., Usman, M., Chen, Q., Xiong, F., Wu, J., & Chen, H. (2023). "Underground Pipeline Mapping from Multi-positional Data: Data Acquisition Platform and Pipeline Mapping Model". IEEE Transactions on Geoscience and Remote Sensing, IF: 7.5, http://dx.doi.org/10.1109/TGRS.2023.3294518.
  • Wang, Xiangyu, Yuan Li, Taiyu Ban, Jiarun Zhu, Lyuzhou Chen, Muhammad Usman, Xin Wang et al. "Dynamic Link Prediction for Discovery of New Impactful COVID-19 Research Approaches." IEEE Journal of Biomedical and Health Informatics 26, no. 12 (2022): 5883-5894, IF: 6.7, http://dx.doi.org/10.1109/JBHI.2022.3212863.
  • Huang, Buliao, Yunhui Zhu, Muhammad Usman, Xiren Zhou, and Huanhuan Chen. "Graph Neural Networks for Missing Value Classification in a Task-driven Metric Space." IEEE Transactions on Knowledge and Data Engineering (2022), IF: 8.9, http://dx.doi.org/10.1109/TKDE.2022.3198689.
  • Chen, Lyuzhou, Xiangyu Wang, Taiyu Ban, Muhammad Usman, Shikang Liu, Derui Lyu, and Huanhuan Chen. "Research Ideas Discovery via Hierarchical Negative Correlation." IEEE Transactions on Neural Networks and Learning Systems (2022), IF: 10.2, http://dx.doi.org/10.1109/TNNLS.2022.3184498.
  • Zhu, Jiarun, Xingyu Wu, Muhammad Usman, Xiangyu Wang, and Huanhuan Chen. "Link Prediction in Continuous-Time Dynamic Heterogeneous Graphs with Causality of Event Types." International Journal of Crowd Science 6, no.2 (2022): 80-91, http://dx.doi.org/10.26599/IJCS.2022.9100013.
  • Wang, Xiangyu, Lyuzhou Chen, Taiyu Ban, Muhammad Usman, Yifeng Guan, Shikang Liu, Tianhao Wu, and Huanhuan Chen."Knowledge graph quality control: a survey." Fundamental Research (2021), IF: 5.7, http://dx.doi.org/10.1016/j.fmre.2021.08.018.
  • Li, Ziqiang, Muhammad Usman, Rentuo Tao, Pengfei Xia, Chaoyue Wang, Huanhuan Chen, and Bin Li. "A systematic survey of regularization and normalization in GANs." ACM Computing Surveys (2020), IF: 16.6, http://dx.doi.org/10.1145/3569928.
  • Ali, S.M.; Anjum, N.; Naureen, F.; Rashid, A.; Tahir, A.; Ishaq, M.; Usman, M. Satisfaction Level of Tuberculosis Patients Regarding Their Access to TB Care and Prevention Services, Delivered Through a Public-Private Mix Model in Pakistan. Healthcare 2019, 7, 119, IF: 2.5, http://dx.doi.org/10.3390/healthcare7040119.
  • Usman, Muhammad, & Akram Sheikh, M. (2018). Mining the Twitter Data Stream: A Review. Pakistan Journal of Computer and Information Sciences 3,(1): 27-40, [Full Text]
  • M. Usman. "Measuring Diversity of Associations Rules Extracted from a Data Warehouse". International Journal of Knowledge Engineering, Vol. 4, No. 1, June 2018, http://dx.doi.org/10.18178/ijke.2018.4.1.101.
  • Usman, Muhammad, & SHAIKH, M. A. (2018). Real Time Events Detection from the Twitter Data Stream: A Review. Pakistan Journal of Computer and Information Systems, 3(2), 47-60, [Full Text]
  • Usman, M., Usman, M. (2017). Multi-level mining of association rules from warehouse schema. Kuwait Journal of Science, 44(1), IF: 0.948, [Full Text].
  • Usman, M., Usman, M., & Asghar, S. (2016). A fuzzy-based methodology for accurate classification and prediction in large datasets. Journal of Intelligent & Fuzzy Systems, 31(3), 1759-1768, IF: 1.7, http://dx.doi.org/10.3233/JIFS-152176 .
  • Usman, M., & Usman, M. (2016). Multi-Level Mining and Visualization of Informative Association Rules. Journal of Information Science & Engineering, 32(4), IF: 3.5, [Full Text].

Muhammad Usman and M. Usman, "Predictive Analysis on Large Data for Actionable Knowledge: Emerging Research and Opportunities." IGI Global, USA. 2018. 1-125, doi: 10.4018/978-1-5225-5029-7.
https://www.igi-global.com/book/predictive-analysis-large-data-actionable/185884



Recall Comparison in EMRIL



Recall Comparison in BININI