1. Azhar, T., Sumi, T. A., Reza, A. W., & Arefin, M. S. (2023). CTFCP: A Cloud-based Deep Transfer Learning Framework for Analyzing Chest X-Ray Images to Detect Pneumonia. In Proceedings of the 2nd International Conference on Big Data, IoT, and Machine Learning (BIM 2023), Accepted for Publication.

2. S. A. Ome, T. Azhar and Asaduzzaman, "A Transformer-Based Model for Image Caption Generation with Memory Enhancement," 2024 IEEE International Women in Engineering (WIE) Conference on Electrical and Computer Engineering (WIECON-ECE), Chennai, India, 2024, pp. 059-064, doi: 10.1109/WIECON-ECE64149.2024.10915030.

3. M. I. Alam, T. Azhar and M. N. Uddin, "Distilling Knowledge for Efficient Multiclass Skin Cancer Classification using Lightweight CNN Model," 2024 27th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 2024, pp. 1317-1322, doi: 10.1109/ICCIT64611.2024.11022327. 

4.  G. M. Fahim Faiyaz, M. Abbas Uddin Tasin, T. Azhar and M. N. Uddin, "A Hybrid Deep Learning Approach For Brain Tumor Detection Using XAI with GradCAM," 2024 27th International Conference on Computer and Information Technology (ICCIT), Cox's Bazar, Bangladesh, 2024, pp. 1235-1240, doi: 10.1109/ICCIT64611.2024.11021963.

5.  T. K. Nowrin, S. Akter, T. Azhar and M. N. Uddin, "Enhancing Object Detection for Autonomous Vehicles Using YOLO-NAS on Bangladeshi Dataset," 2024 International Conference on Innovations in Science, Engineering and Technology (ICISET), Chittagong, Bangladesh, 2024, pp. 1-6, doi: 10.1109/ICISET62123.2024.11003917. 

6. S. Nawar and T. Azhar, "Enhancing Space Debris Detection and Classification Using Optimized YOLO Variants," 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE), Chittagong, Bangladesh, 2025, pp. 1-6, doi: 10.1109/ECCE64574.2025.11013138.

7. M. S. Kabir and T. Azhar, "Semi-Supervised Learning Approach Using Hybrid Bidirectional LSTM Networks for Diabetes Prediction with Explainable AI," 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE), Chittagong, Bangladesh, 2025, pp. 1-6, doi: 10.1109/ECCE64574.2025.11014053.

8. M. Bin Habib, A. T. Jannat and T. Azhar, "Transformer-Based Multi-Label Classification for Code Smell Detection in Software Engineering," 2025 6th International Conference for Emerging Technology (INCET), BELGAUM, India, 2025, pp. 1-6, doi: 10.1109/INCET64471.2025.11140264. 

9. T. Islam, N. S. Riya, M. Irfan Abrar and T. Azhar, "Advancing Coconut Tree Disease Detection Using Integrated CNN And Hybrid Vision Transformer," 2025 International Conference on Electrical, Computer and Communication Engineering (ECCE), Chittagong, Bangladesh, 2025, pp. 1-5, doi: 10.1109/ECCE64574.2025.11013140.

10. M. I. Alam, T. Azhar, and M. N. Uddin, “Ensemble-Based Knowledge Distillation with Channel Attention for Resource-Efficient Skin Cancer Classification,” in Proc. 2025 IEEE Int. Conf. Quantum Photon., Artif. Intell., Netw. (QPAIN), 2025, Accepted for Publication

11. M. S. Kabir, T. Azhar, and U. G. Joy, “Attention-Driven Ensemble Learning: Enhancing Diabetes Prediction in Data-Scarce Environments,” in Proc. Int. Conf. Data Sci., Artif. Intell. Appl. (ICDSAIA), 2025, Accepted for Publication

Industry Research Project Collaboration/Work Experiences –

• Colon Cancer Research Project @ The Royal Melbourne Hospitals, Australia. (Our Solution is currently being used by RMH)

• VicRoads Driver’s Attention Detection @ VicRoads, Australia. (Placed in the Top 3 solution provided to the ICT industry and also implemented in the road surveillance camera.) - M.Sc. Research Project Placement by RMIT University.

• Deep Learning Engineer @ JP Morgan Chase & Co. (1 year)

• ToS (Tan-OS) – Developer of open-source Bosch Kernel for Operating System.

(Currently under the supervision of University of Melbourne, Australia)