Faculty of Science and Engineering
Department of Computer Science and Engineering
MSc in Computer Science from American International University-Bangladesh (AIUB) (On going)
BSc in Computer Engineering from American International University-Bangladesh (AIUB)
HSC from Saidpur Cantonment Public School & College, Saidpur, Nilphamari
SSC from Ibrahim Memorial Shiksha Niketan, Birganj, Dinajpur
Tahmid Enam Shrestha is a Lecturer in the Department of Computer Science and Engineering at City University, Dhaka, and an Assistant Investigator at the Artificial Intelligence Research and Innovation Lab (AIRIL), Dhaka. He holds a Bachelor of Science degree in Computer Science and Engineering, majoring in Information Systems, from the American International University-Bangladesh (AIUB), and is currently pursuing a Master of Science in Computer Science at AIUB, specializing in Intelligent Systems. Mr. Shrestha's research interests are primarily focused on Deep-learning, Explainable Artificial Intelligence, Computer Vision, Biomedical Image Analysis, and Federated-learning for decision-support applications. His work aims to advance the development of AI systems that are not only technically robust but also transparent and interpretable, particularly in critical fields such as healthcare and security. A member of the Institute of Electrical and Electronics Engineers, Mr. Shrestha has been recognized for his contributions to AI research, receiving the Best Researcher Award from AIRIL in 2025. His work continues to have a significant impact on both academic and applied AI research, contributing to the development of scalable, ethical AI technologies.
Lecturer, Department of Computer Science and Engineering, City University.
September 2025 – Till date.
Computer Vision,
Deep Learning,
Biomedical Image Analysis,
Federated Learning,
Cyber-Security,
Explainable AI.
Journal Papers
1. Tanim, S. A., Shrestha, T. E., Emon, M. R. I., Mridha, M. F., & Miah, M. S. U. (2025). Explainable deep learning for diabetes diagnosis with DeepNetX2. Biomedical Signal Processing and Control, 99, 106902. Q1(Impact Factor 4.9).
2. Aurnob, A.R., Tanim, S. A., Shrestha, T. E., Mridha, M. F., FedFusionNet: Advancing Oral Cancer Recurrence Prediction through Federated Fusion Modeling. Information Fusion Q1(Impact Factor 15.8).
3. Al Huda, M. S., Shrestha, T. E., Hossain, A., Sharif, N. B., Ali, M. A., & Erdei, T. I. (2025). DeepMelaNet: Advancing Melanoma Stage Classification in Skin Cancer Diagnosis, Engineering Technology & Applied Science Research, 15(1), 19627-19635. Q2(Impact Factor 1.96).
4. Rahman, R. B., Tanim, S. A., Alfaz, N., Shrestha, T. E., Miah, M. S. U., & Mridha, M. F. (2024). A comprehensive dental dataset of six classes for deep learning based object detection study. Data in Brief, 57, 110970. Q3(Impact Factor 1.0).
Conference Papers
1. Shrestha, T. E., Tanim, S. A., Islam, M., & Nur, K. (2024, May). Revolutionizing cucumber agriculture: Ai for precision classification of leaf diseases. In 2024 6th International Conference on Electrical Engineering and Information & Communication Technology. IEEE (ICEEICT 2024).
2. Tanim, S. A., Arnob, A. R., Shrestha, T. E., Alam, T., & Nur, K. (2024, May). Enhancing blood cell classification by applying big transfer and (xai). In Doctoral Symposium on Computational Intelligence (pp. 181-192). Singapore: Springer Nature Singapore (DoSCI 2024).
3. Shrestha, T. E., Khan, M., Mishu, M. J., Huda, S. A., & Ali, A. (2025). DeepRoseNet: An Explainable Hybrid Deep Learning Approach for Precise Rose Leaf Disease Classification. Proceedings of the 2025 IEEE International Conference on Quantum Photonics, Artificial Intelligence, and Networking IEEE(QPAIN-2025).
4. Shrestha, T. E., Rahman, S. B., Bika, S. A., Khan, M. A., & Rahman, T (2025, December). Enhancing Potato Leaf Disease Classification Using a Modified CNN with XAI. 2nd IEEE Conference on Computing Applications and Systems (COMPAS 2025).
5. Shrestha, T. E., Islam, J., Rukaiya, A. R., Rizon, A.M. R., Dipto, S. K., & Ali, A. (2025, December), LungXResViT: A Robust Hybrid DL Framework for Accurate Lung Cancer Classification with XAI, 2nd IEEE Conference on Computing Applications and Systems (COMPAS 2025).
6. Shrestha, T.E., Habib, A., Sabbir, H., Annasha, F.R., Hossen, M.S., Rahman, S.M.A., (2025, December), Chronic Kidney Disease Diagnosis Using Interpretable Ensemble Machine Learning Models, 7th International Conference on Integrated Sciences (ICIS 2025).
7. Shrestha, T. E., Sayem, A., Rahman, M. F., Khan, M. A., & Ali, A. (2025, December), Securing TLS in the Quantum Era: A Robust Hybrid Protocol with Kyber, X25519, and Dilithium. 28th International Conference on Computer and Information Technology. (ICCIT 2025).
8. Shrestha, T. E., Khan, M., & Karim, R. (2025, December), TM-DeepNet: A Hybrid Deep Learning Model with Explainable AI for Acute Lymphoblastic Leukemia Stage Classification. 28th International Conference on Computer and Information Technology. (ICCIT 2025).
9. S. A. Tanim, T. E. Shrestha, K. Tanvir, M. S. Kabir, M. F. Mridha and M. K. Haq, "Single-Level Fusion for Enhancing Meat Quality Classification with Explainable AI," 2024 IEEE International Conference on Computing, Applications and Systems (COMPAS), Cox's Bazar, Bangladesh, 2024, pp. 1-6, doi: 10.1109/COMPAS60761.2024.10796775. (COMPAS 2024).
10. Sadi, A. H., Shrestha, T. E., Tanvir, K., Ali, A., Towhid, B., (2024). ViTBiT-PoxNet: An Explainable Hybrid Deep Learning Framework for Enhanced Early Stage Monkeypox Classification. International Conference on Computing and Communication Networks. Springer (ICCCNet-2025).
11. Rukaia, A. R., Shrestha, T. E., Kakingwe, A., Chen, S., (2025). AGNet: An Alternate Guidance Network for Colorectal Polyp Segmentation and Detection. 2nd International Conference on Next-Generation Computing, IoT and Machine Learning. IEEE (NCIM-2025).
12. Shatil, S. M., Habib, A., Shrestha, T. E., Hossain, S., Huda, M. S. A., & Tania, N. A. J. (2024, October). Improving Big Data Visualization and Association Rule Mining through Splunk Database Gap Analysis. In Proceedings of the 3rd International Conference on Computing Advancements (pp. 713-718), ACM (ICCA 2024).
13. Sahrin Jisha, S., Ayon, S., Tanim, S. A., Md. Raeid, F. A., Shrestha, T. E., Huda, M. S. A., & Ali, M. A. (2024, October). Mental Health Analysis: ML And Explainable AI Predict Depression Among Bangladeshi University Students. In Proceedings of the 3rd International Conference on Computing Advancements (pp. 491-497), ACM (ICCA 2024).
14. Alam, G. M. I., Tanim, S. A., Shrestha, T. E., Raihan, M., & Nur, K. (2024, June). Deep Learning Approach with eXplainable Artificial Intelligence Interpretation for Early-Stage Diabetes Detection. In the International Conference on Data Analytics & Management (pp. 289-302). Singapore: Springer Nature (ICDAM 2024).
15. Tanim, S. A., Alam, G. M. I., Shrestha, T. E., Islam, M., Jahan, F., & Nur, K. (2024, November). Breast Cancer Diagnosis with XAI-Integrated Deep Learning Approach. In 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies (pp. 659-665). IEEE (3ICT 2024).
16. Al Huda, M. S., Arman, R. A., Shrestha, T. E., Tamim, S. A., & Ali, M. A. (2024, October). DeepResVit: A Hybrid Deep Learning Approach for Ovarian Cancer Classification with XAI. In 2024 2nd International Conference on Information and Communication Technology (pp. 229-233). IEEE (ICICT 2024).
17. Chowdhury, M. T., Tanim, S. A., Shrestha, T. E., Hossain, M. F., & Bhuyan, M. H. (2024, June). Enhancing Electoral Integrity: A Multi-layered Approach to Electronic Voting Security Using Arduino and Biometric Authentication. In the International Conference on Data Analytics & Management (pp. 643-654). Singapore: Springer Nature Singapore (ICDAM 2024).
18. Hossain, M. H., Shrestha, T. E., Abdullah, M., Iqbal, M. A., Ahmhed, T., Rahman, S. (2025, December), DeepBNet: A Modified DL Model for More Accurate Classification of Bengali Compound Handwritten Characters. 2nd IEEE Conference on Computing Applications and Systems (COMPAS 2025).
19. M. Hossain, S. A. Promi, S. H. Arman, A.A. Rabeya, M. S. A. Huda, and T. E. Shrestha, “Exploring deep 3D U-Net architectures for automated brain tumor segmentation: A study on the BraTS benchmark dataset,” in International Conference on Intelligent Data Analysis and Applications Springer (IDAA 2025).
20. Sohag, Nuhash, A.A. Rabeya, Ahmhed, M. S. A. Huda, and T. E. Shrestha, “Bridging AI and Ethnobotany: A Deep Learning Approach for Medicinal Plant Identification and Real-World Deployment,” in International Conference on Intelligent Data Analysis and Applications Springer (IDAA 2025).