Department of Computer Science and Engineering
Dr. Md Alamgir Kabir  Assistant Professor
Name :
Dr. Md Alamgir Kabir
Employee ID
710003552
Designation
Assistant Professor  
Department
Department of Computer Science and Engineering
Faculty
Faculty of Science and Information Technology
Personal Webpage
https://faculty.daffodilvarsity.edu.bd/profile/cse/alamgirkabir.html
E-mail
kabir.cse@diu.edu.bd
Phone
Cell-Phone
01723034458
  • MEng in Software Engineering, Wuhan University, Wuhan, China
  • BSc in Software Engineering, Daffodil International University, Dhaka, Bangladesh, Gold Medalist

More than 10 years of experience in teaching, development, and research at IT sector in Sweden, Hong Kong, China, and Bangladesh

Computer Science and Software Engineering

 Forthcoming:

  1. Shahina Begum and Mobyen Uddin Ahmed, Shaibal Barua and Md Alamgir Kabir (2024). Research Issues and Challenges in the Computational Development of Trustworthy AI (Accepted) 
  2. Kabir, M. A., Mobyen Uddin Ahmed, Shahina Begum, Shaibal Barua, Md Rakibul Islam (2024). Balancing Fairness : Unveiling the Potential of SMOTE-Driven Oversampling in AI Model Enhancement. International Conference on Machine Learning Technologies, (Accepted)
  3. M M Manjurul Islam, Kabir, M. A., Alamin Sheikh, Muhammad Saiduzzaman, Abdelakram Hafid, Saad Abdullah (2024). Enhancing Speech Emotion Recognition Using Deep Convolutional Neural Networks. International Conference on Machine Learning Technologies, (Accepted)

Selected Journals: 

  1. Racherla, S., Sripathi, P., Faruqui, N., Kabir, M. A., Whaiduzzaman, M., & Shah, S. A. (2024). Deep-IDS: A Real-Time Intrusion Detector for IoT Nodes Using Deep Learning. IEEE Access. (Impact Factor : 3.9)
  2. Kabir, M. A., Rehman, A. U., Islam, M. M., Ali, N., & Baptista, M. L. (2023). Cross-Version ´Software Defect Prediction Considering Concept Drift and Chronological Splitting. Symmetry, 15(10), 1934. (Impact Factor : 2.7)
  3. Elahe, M. F., Kabir, M. A., Mahmud, S. M. H., & Azim, R. (2023). Factors impacting short-term load forecasting of charging station to electric vehicle. Electronics, 12(1). (Impact Factor : 2.690)
  4. Faruqui, N., Kabir, M. A., Yousuf, M. A., Whaiduzzaman, M., Barros, A., & Mahmud, I. (2023). Trackez : An IoT-based 3D-Object Tracking from 2D Pixel Matrix using Mez and FSL Algorithm. IEEE Access. (Impact Factor : 3.9)
  5. Ur Rehman, A., Belhaouari, S. B., Kabir, M. A., & Khan, A. (2023). On the Use of Deep Learning for Video Classification. Applied Sciences, 13(3), 2007.(Impact Factor : 2.7)
  6. Kabir, M. A., Begum, S., Ahmed, M. U., & Rehman, A. U. (2022). CODE : A Moving-Window-Based Framework for Detecting Concept Drift in Software Defect Prediction. Symmetry, 14(12), 2508. (Impact Factor : 2.7)
  7. Mahmud, M. H., Nayan, M. T. H., Ashir, D. M. N. A., & Kabir, M. A. (2022). Software Risk Prediction : Systematic Literature Review on Machine Learning Techniques. Applied Sciences, 12(22), 11694. (Impact Factor : 2.838)
  8. Kabir, M. A., Keung, J., Turhan, B., & Bennin, K. E. (2021). Inter-release defect prediction with feature selection using temporal chunk-based learning : An empirical study. Applied Soft Computing, 113, 107870. (Impact Factor : 8.263)
  9. Yang, Z., Keung, J., Kabir, M. A., Yu, X., Tang, Y., Zhang, M., & Feng, S. (2021). AComNN : Attention enhanced Compound Neural Network for financial time-series forecasting with cross-regional features. Applied Soft Computing, 111, 107649. (Impact Factor : 8.263)
  10. Zhang, M., Keung, J. W., Xiao, Y., & Kabir, M. A. (2021). Evaluating the effects of similar-class combination on class integration test order generation. Information and Software Technology, 129, 106438. (Impact Factor : 3.862)
  11. Feng, S., Keung, J., Yu, X., Xiao, Y., Bennin, K. E., Kabir, M. A., & Zhang, M. (2021). COSTE : Complexity-based OverSampling TEchnique to alleviate the class imbalance problem in software defect prediction. Information and Software Technology, 129, 106432. (Impact Factor : 3.862)
  12. Kabir, M. A., & Han, B. (2016). An improved usability evaluation model for point-of-sale systems. International Journal of Smart Home, 10(7), 269-282.



Selected Conference Proceedings:

  1. ur Rehman, A., Kabir, M. A., Ijaz, M., Al-Mohsin, H. M., & Bermak, A. (2023, May). Salp Swarm Algorithm for Drift Compensation in E-nose. In 2023 15th International Conference on Advanced Computational Intelligence (ICACI) (pp. 1-6). IEEE.
  2. Shakhawat, H., Hossain, S., Kabir, A., Mahmud, S. H., Islam, M. M., & Tariq, F. (2023). Review of Artifact Detection Methods for Automated Analysis and Diagnosis in Digital Pathology. In Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare (pp. 177-202). CRC Press.
  3. Kabir, M. A., Islam, M. M., Mahmud, S. H., & Elahe, M. F. (2022, March). Spectrum Impact Analysis of Fault Proneness Statement for Improved Fault Localization. In Proceedings of the 2nd International Conference on Computing Advancements (pp. 59- 66).
  4. Kabir, M. A., Keung, J. W., Bennin, K. E., & Zhang, M. (2020, July). A drift propensity detection technique to improve the performance for cross-version software defect prediction. In 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC) (pp. 882-891). IEEE.
  5. Kabir, M. A., Keung, J. W., Bennin, K. E., & Zhang, M. (2019, July). Assessing the significant impact of concept drift in software defect prediction. In 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) (Vol. 1, pp. 53-58). IEEE
  6. Sohan, M. F., Kabir, M. A., Rahman, M., Hasan Mahmud, S. M., & Bhuiyan, T. (2020). Training Data Selection Using Ensemble Dataset Approach for Software Defect Prediction. In Cyber Security and Computer Science : Second EAI International Conference, ICONCS 2020, Dhaka, Bangladesh, February 15-16, 2020, Proceedings 2 (pp. 243-256). Springer International Publishing.
  7. Sohan, M. F., Kabir, M. A., Rahman, M., Bhuiyan, T., Jabiullah, M. I., & Felix, E. A. (2020). Prevalence of machine learning techniques in software defect prediction. In Cyber Security and Computer Science : Second EAI International Conference, ICONCS 2020, Dhaka, Bangladesh, February 15-16, 2020, Proceedings 2 (pp. 257-269). Springer International Publishing.
  8. Zhang, M., Keung, J., Xiao, Y., Kabir, M. A., & Feng, S. (2019, July). A heuristic approach to break cycles for the class integration test order generation. In 2019 IEEE 43rd Annual Computer Software and Applications Conference (COMPSAC) (Vol. 1, pp. 47-52). IEEE.
  9. Sohan, M. F., Kabir, M. A., Jabiullah, M. I., & Rahman, S. S. M. M. (2019, February). Revisiting the class imbalance issue in software defect prediction. In 2019 International Conference on Electrical, Computer and Communication Engineering (ECCE) (pp. 1-6). IEEE.
  10. Kabir, M. A., Hossin, M. A., Mahmud, S. H., Noori, S. R. H., & Bhuiyan, T. (2018, December). Usability evaluation of mobile applications : An empirical analysis of supply chain management systems. In 2018 IEEE 4th International Conference on Computer and Communications (ICCC) (pp. 2525-2531). IEEE.
  11. Kabir, M. A., Salem, O. A., & Rehman, M. U. (2017, November). Discovering knowledge from mobile application users for usability improvement : A fuzzy association rule mining approach. In 2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) (pp. 126-129). IEEE



  • His research conceives on developing intelligent systems based on machine learning in different domains. Recently, he adapted algorithms and techniques to develop safe, secure, and robust AI systems for enhancing trustworthiness of AI systems including AI fairness, XAI, and generative AI. 
  • He previously crafted innovative methods and remedies for (1) Concept drift issues in software defects for the development of reliable models, (2) Class imbalance issues in software defect prediction, and (3) Oversampling techniques to alleviate class imbalance issues. He also enhances the state-of-the-art ML methods. 
  • Additionally, Dr. Kabir became involved with various research communities at home and abroad by serving as a member in the organizing committee, technical committee, technical co-chair, and reviewer in high-impact peer-reviewed journals. 
  • His mission is to help the community towards engineering high-quality and secure software systems for social good. If you share the same value, please reach out for collaborations.
  • Performance Award in Teaching Students : First Steps (SG8001) course in Semester B, 2018-19 at City University of Hong Kong
  • Hong Kong Government PhD Scholarship at City University of Hong Kong
  • Best paper award in the IEEE conference ICCSNT 2016.
  • Chinese Government Scholarship for master’s degree Study at Wuhan University, China (Sep 2015 – Aug 2017)
  • Received Vice Chancellor Gold Medal for highest CGPA among students of all departments at Daffodil International University, Bangladesh (2014)
  • Merit Scholarship in bachelor’s degree Study at Daffodil International University, Bangladesh (Jan 2010 – Dec 2013
  • IEEE
  • [Sep’2022-June’2024] Postdoctoral Research Fellow - Machine Learning, Department of Innovation, Design and Engineering, Mälardalen University, Sweden.
  • [Sep’2021-Aug’2022] Assistant Professor, Department of Computer Science, American International University-Bangladesh.
  • [Sep’2018-Aug’2021] Researcher, Department of Computer Science, City University of Hong Kong, Hong Kong.
  • [Sep’2017-Aug’2018] Senior Lecturer, Department of Software Engineering, Daffodil International University, Bangladesh.
  • [Sep’2015-Aug’2017] Research Assistant, International School of Software, Wuhan University, China.
  • [Apr’2014-Aug’2015] Lecturer, Department of Software Engineering, Daffodil International University, Bangladesh