Advancing AI, Software & Data Science

Focus Areas

Research

I specialize in AI and machine learning, with a strong focus on data stream learning, concept drift adaptation, imbalanced data classification, data mining, and knowledge engineering.

Software Development

With expertise in web and database development, I design scalable software solutions using PHP, ASP.NET, and MySQL. I have led teams to build robust applications for diverse industries.

Trainings

I conduct hands-on training sessions to help researchers and professionals integrate AI and data science into their work. My workshops emphasize practical learning, ensuring participants can apply AI techniques effectively.

Experience

I have over a decade of experience spanning software engineering, web development, and data science, progressing from building and maintaining software solutions to designing and developing complex web applications, and eventually advancing into data-driven research and analysis. My expertise combines strong programming skills with the ability to design, implement, and optimize systems, alongside applying advanced analytical methods to extract insights, solve problems, and support decision-making. This blend of technical development and analytical proficiency allows me to deliver solutions that are both innovative and impactful.

Education

Ph.D. (Computer Science)

University of Science and Technology of China, Hefei, China.

Masters of Computer Science (MSCS)

SZABIST, Islamabad.

Masters of Computer Science (MCS)

International Islamic University, Islamabad.

Recent Research Pubications

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

Hina Farooq, Muhammad Usman and Huanhuan Chen(2025). MinoRare: Handling Rare Minority Instances in Imbalanced and Drifting Data Streams through Adaptive Instance Weighting Scheme, IEEE Transactions on Big Data, Accepted, In Press.
Muhammad Usman and Huanhuan Chen(2024). EMRIL: Ensemble method based on ReInforcement Learning for Imbalanced and Drifting Data streams, Neurocomputing, Accepted, In Press.
Muhammad Usman and Huanhuan Chen(2024). Bin.INI: An Ensemble Approach for Dynamic Data Streams, Expert Systems with Applications, Accepted, In Press.
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, Accepted, In Press.
Muhammad Usman and Huanhuan Chen(2024). Intensive Class Imbalance Learning in Drifting Data Streams, IEEE Transactions on Emerging Topics on Computational Intelligence, Accepted, In Press.
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, Accepted, In Press.
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, Accepted, In Press.
Buliao Huang, Yunhui Zhu, Muhammad Usman, Huanhuan Chen(2023). Semi-supervised Learning with Missing Values Imputation. Knowledge-Based Systems, Accepted, In Press.

Google Scholar Profile

Dr. Muhammad Usman

Training Workshops

SPSS Tutorial

LaTeX Tutorial

Training News / Funding Opportunities

I’m a professional specializing in the design, development, and optimization of AI-driven systems, software solutions, and data-driven applications, ensuring both functionality and user experience.