Academic Qualifications:

• O-Levels in 2017
• A-Levels in 2019
• Bachelor of Science in Computer Science, graduated in 2023

Research Interests:

• Data Science
• Machine Learning
• Computer Vision
• Simulation and Modeling 

Check updates in Google Scholar: https://scholar.google.com/citations?user=igQd0ScAAAAJ&hl

Journal Articles:

1. Islam, Md. F., Manab, M. A., Mondal, J. J., Zabeen, S., Rahman, F. B., Hasan, Md. Z., Sadeque, F., & Noor, J. (2024). Involution Fused ConvNet for Classifying Eye-Tracking Patterns of Children with Autism Spectrum Disorder. arXiv preprint (Submitted to Elsevier Engineering Applications with Artificial Intelligence). https://doi.org/10.48550/arXiv.2401.03575. [Minor Revision, Q1, IF: 7.5]

Conference or Workshop Papers:

1. Zabeen, S., Hasan A., Islam, Md. F, Sabbir Hossain, M., & Rasel, A. A. (2023). Robust Fake Review Detection Using Uncertainty-Aware LSTM and BERT, 2023 15th International Conference on Computational Intelligence and Communication Networks (CICN). 786-791, https://doi.org/10.1109/CICN59264.2023.10402342.
2. Islam, Md. F., Zabeen, S., Islam, Md. A., Rahman, F. B., Ahmed, A., Karim, D. Z., Rasel, A. A., & Manab, M. A. (2023). How certain are tansformers in image classification: uncertainty analysis with Monte Carlo dropout. In W. Osten, D. P. Nikolaev, & J. (Jessica) Zhou (Eds.), Fifteenth International Conference on Machine Vision (ICMV 2022) (Vol. 12701, p. 127010K). SPIE. https://doi.org/10.1117/12.2679442
3. Islam, Md. F., Zabeen, S., Rahman, F. B., Islam, Md. A., Kibria, F. B., Manab, M. A., Karim, D. Z., & Rasel, A. A. (2023). Exploring Node Classification Uncertainty in Graph Neural Networks. Proceedings of the 2023 ACM Southeast Conference, 186–190. https://doi.org/10.1145/3564746.3587019
4. Islam, Md. F., Zabeen, S., Rahman, F. B., Islam, Md. A., Kibria, F. B., Manab, M. A., Karim, D. Z., & Rasel, A. A. (2023). UnIC-Net: Uncertainty Aware Involution-Convolution Hybrid Network for Two-level Disease Identification. SoutheastCon 2023, 305–312. https://doi.org/10.1109/SoutheastCon51012.2023.10115109
5. Islam, Md. F., Bin Rahman, F., Zabeen, S., Islam, Md. A., Sabbir Hossain, M., Kabir Mehedi, M. H., Manab, M. A., & Rasel, A. A. (2022). RNN Variants vs Transformer Variants: Uncertainty in Text Classification with Monte Carlo Dropout. 2022 25th International Conference on Computer and Information Technology (ICCIT), 7–12. https://doi.org/10.1109/ICCIT57492.2022.10055922
6. Islam, Md. F., Zabeen, S., Rahman, M. M., Khan, M. H., Khan, F. N., Nahim, N. Z., Anwar, T., & Kaykobad, M. (2022). Identifying Hurricane Damage using Explainable Compact Transformer with Convolutional Embedding. 2022 25th International Conference on Computer and Information Technology (ICCIT), 833–838. https://doi.org/10.1109/ICCIT57492.2022.10054917
7. Mondal, J. J., Islam, Md. F., Zabeen, S., & Manab, M. A. (2022). InvoPotNet: Detecting Pothole from Images through Leveraging Lightweight Involutional Neural Network. 2022 25th International Conference on Computer and Information Technology (ICCIT), 599–604. https://doi.org/10.1109/ICCIT57492.2022.10055818
8. Islam, Md. F., Zabeen, S., Mehedi, Md. H. K., Iqbal, S., & Rasel, A. A. (2022). Monte Carlo Dropout for Uncertainty Analysis and ECG Trace Image Classification. In A. Krzyzak, C. Y. Suen, A. Torsello, & N. Nobile (Eds.), Structural, Syntactic, and Statistical Pattern Recognition (pp. 173–182). Springer International Publishing.
9. Mondal, J. J., Islam, Md. F., Zabeen, S., Islam, A. B. M. A. A., & Noor, J. (2022). Note: Plant Leaf Disease Network (PLeaD-Net): Identifying Plant Leaf Diseases through Leveraging Limited-Resource Deep Convolutional Neural Network. Proceedings of the 5th ACM SIGCAS/SIGCHI Conference on Computing and Sustainable Societies, 668–673. https://doi.org/10.1145/3530190.3534844 

Preprints:

1. Islam, Md. F., Reza, Md. T., Manab, M. A., Mahin, M. R. H., Zabeen, S., & Noor, J. (2024). Spatially Optimized Compact Deep Metric Learning Model for Similarity Search. arXiv preprint. https://doi.org/10.48550/arXiv.2404.06593. [Submitted to Elsevier Engineering Applications with Artificial Intelligence, Q1]

Undergraduate Thesis:

1. Islam, Md. F., Zabeen, S., Rahman, F. B., Islam, Md. A., Kibria, F. B. (2023). Analysis of Uncertainty in Different Neural Network Structures using Monte Carlo Dropout. BRAC University. https://dspace.bracu.ac.bd/xmlui/handle/10361/22153 . (Supervisor: Annajiat Alim Rasel, Co-supervisors: Dewan Ziaul Karim & Meem Arafat Manab.)

Research Posters:

1. Mondal, J. J., Islam, Md. F., Zabeen, S., Islam, A. B. M. A. A., & Noor, J. (2021). Identification of Plant Leaf Diseases using Deep Convolutional Neural Network with Less Computational Power. 8th International Conference on Networking, Systems and Security. https://doi.org/10.13140/RG.2.2.17702.04168. 

Graduate Teaching Assistant (Oct 2023 - Present)

Dept of Mathematics and Natural Sciences, School Data and Sciences, BRAC University

Course: MAT120 Lab

Responsibilities:
- Weekly four lectures on solving and plotting mathematical equations using python libraries (numpy, matplotlib, scipy, and seabron)
- Script grading
- Consultations and guidance
- Code Documentation
- Tutorial Content Creation

• 3rd Place: Project Showcasing at IEEE Project Tech Tussle 2021, sponsored by Global Brand
• Merit-Based and Previous Academic-Based Scholarships during undergraduate program at BRAC University for 7 semesters [up to 50% scholarship]