Dr. Engr. Muhammad Bux Alvi
Predictive Modeling and Data-Driven Decision Support; Text Analytics and Natural Language Processing; Sentiment Analysis and Opinion Mining; Machine Learning and Deep Learning Architectures; Large Language Models (LLMs) and Transformer-Based Systems.
Dr. Muhammad Bux Alvi is an Associate Professor in the Department of Computer Science at the Benazir Bhutto Shaheed University of Technology and Skill Development (BBSUTSD), Khairpur Mirs, Sindh, Pakistan. He holds a Ph.D. in Computer Systems Engineering and a Master of Engineering in Information Technology, both from Mehran University of Engineering and Technology (MUET), Jamshoro. He began his academic journey with a Bachelor of Engineering (B.E.) in Computer Systems Engineering from Quaid-e-Awam University of Engineering, Science and Technology (QUEST), Nawabshah, graduating with First Class and First Position and earning a Silver Medal. With over 24 years of diverse experience spanning academia, academic administration, and field engineering, Dr. Alvi brings a rare breadth of perspective to his teaching and research. He began his career as a Lecturer in Computer Systems Engineering at QUEST, Nawabshah, before joining the Pakistan Telecommunication Company Limited (PTCL), where he served as Assistant Divisional Engineer and later as Divisional Engineer (OPS). He subsequently returned to academia as an Assistant Professor in Computer Systems Engineering at The Islamia University of Bahawalpur, where he also served as the Officiating Head of Department for more than five years. Dr. Alvi has authored more than 20 research publications in internationally reputable journals and presented 10 papers at international conferences. He actively contributes to the academic community as a peer reviewer for leading publishers, including IEEE, Elsvier, Springer Nature, and TechScience Press. His mentorship record includes supervising 25 Masters students to completion, and he is currently supervising a PhD candidate.
1. Keerio, T., Memon, M. S., Shafique, M., Alvi, M. B., Chan, A., Hussain, A., & Fauadi, M. H. F. B.
M. (2026). MAC protocol for multi-hop wireless sensor networks utilizing integrated reinforcement
learning with joint frame and slot optimization. Frontiers in Computer Science, 8, 1862641.
2. Asif Ali Laghari, Awais Khan Jumani, Shoulin Yin, Muhammad Bux Alvi, Kamlesh Kumar, Hang
Li, & Khan, A. A. (2026). Blockchain Security and Privacy: Threats, Solutions, and Future
Directions. Web Intelligence. doi:10.1177/24056456261438151 (Available Online)
3. Majdah Alvi, Qureshi M. A., & Alvi M. B. (2026). Harnessing Encoder-based Transformer Models
for Multilingual Student Feedback Sentiment Analysis. Journal of Computers and Intelligent
Systems, 4(1).
4. Alvi M. B., Majdah Alvi, & et al. (2025). Life Expectancy Prediction using Recursive Partitioning
and Bagging Algorithms. EAI Endorsed Transactions on Scalable Information Systems, 12(5).
5. Karim, S., Hussain, K., Alvi M. B., Rahu, M. A., Kaloi, M. A., & Haleem, H. (2025). Artificial
Intelligence in Sustainable Smart Agriculture: Concepts, Applications, and Challenges. VAWKUM
Transactions on Computer Sciences, 13(1), 307–342.
6. Alvi, M., Akhter, A., Alvi M. B., & Fatima, N. (2025). Emotion Detection and Analysis using
Textual Data through Trainable and Pre-trained Word Embedding Methods. VFAST Transactions on
Software Engineering, 13(2), 28–43. (Corresponding Author)
7. Alvi, M., Alvi M. B., & Fatima, N. (2025). A Framework for Sarcasm Detection Incorporating
Roman Sindhi and Roman Urdu Scripts in Multilingual Dataset Analysis. Journal of Computing &
Biomedical Informatics, 8(02). (Corresponding Author)
8. Fatima, N., Alvi, M., & Alvi M. B. (2024). Empowering Sentiment Analysis with Deep Learning
Model: Evaluating Social Media’s Benefits and Drawbacks. VAWKUM Transactions on Computer
Sciences, 12(2), 241–253. (Corresponding Author)
9. Jawad, K., Ahmad, M., Alvi, M., & Alvi M. B. (2024). RUSAS: Roman Urdu Sentiment Analysis
System. Computers, Materials & Continua, 79(1). (Corresponding Author)
10. Shah, R., Riaz, S., Kumar, D., Alvi M. B., Bibi, S. R., & Zardari, Z. (2023). Efficient Machine
Learning Techniques to Classifying Cardiovascular Disease and Improve Prediction Analysis.
Sukkur IBA Journal of Emerging Technologies, 6(2), 28–42.
11. Alvi M. B., Mahoto, N. A., Reshan, M. S. A., Unar, M., Elmagzoub, M. A., & Shaikh, A. (2023).
Count me too: Sentiment analysis of roman sindhi script. SAGE Open, 13(3), 21582440231197452.
12. Ahmad, M., Jawad, K., Alvi M. B., & Alvi, M. (2023). Google maps data analysis of clothing
brands in south punjab, Pakistan. EAI Endorsed Transactions on Scalable Information Systems,
10(3). (Corresponding Author)
13. Alvi M. B., Alvi, M., Shah, R. A., Munir, M., & Akhtar, A. (2022). Machine learning-based Fake
reviews detection with amalgamated features extraction method. Sukkur IBA Journal of Emerging
Technologies, 5(2), 10–17.
14. Akhter, A., Alvi M. B., & Alvi, M. (2021). Forecasting Multan estate prices using optimized
regression techniques. Univ. Sindh J. Inf. Commun. Technol, 5(4), 166–173. (Corresponding
Author)
15. Alvi M. B., Mahoto, N. A., Unar, M. A., & Shaikh, M. A. (2019). An effective framework for
tweet level sentiment classification using recursive text pre-processing approach. International
Journal of Advanced Computer Science and Applications, 10(6).
16. Memon, K. H., Memon, S., Qureshi, M. A., Alvi M. B., Kumar, D., & Shah, R. A. (2019). Kernel
possibilistic fuzzy c-means clustering with local information for image segmentation. International
Journal of Fuzzy Systems, 21, 321–332.
17. Shah, R. A., Qian, Y., Kumar, D., Ali, M., & Alvi M. B. (2017). Network intrusion detection
through discriminative feature selection by using sparse logistic regression. Future Internet, 9(4),
81.
18. Khahro, S. F., Tabbassum, K., Talpur, S., Alvi M. B., Liao, X., & Dong, L. (2015). Evaluation of
solar energy resources by establishing empirical models for diffuse solar radiation on tilted surface
and analysis for optimum tilt angle for a prospective location in southern region of Sindh, Pakistan.
International Journal of Electrical Power & Energy Systems, 64, 1073–1080.
19. Khahro, S. F., Tabbassum, K., Soomro, A. M., Liao, X., Alvi M. B., Dong, L., & Manzoor, M. F.
(2014). Techno-economical evaluation of wind energy potential and analysis of power generation
from wind at Gharo, Sindh Pakistan. Renewable and Sustainable Energy Reviews, 35, 460–474.
