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Dr. Faisal Ahmed is a dedicated educator and researcher with a strong background in university-level teaching and scholarly work. He earned his Ph.D. in Mathematics with a focus on Data Science from the University of Texas at Dallas, where his research centered on Topological Data Analysis, Machine Learning and Deep Learning.

Currently serving as an assistant professor of Mathematics, Dr. Ahmed is actively involved in teaching blended courses such as Mathematics (Calculus I, Calculus III), Data Science and Statistics. He is committed to fostering interdisciplinary learning and supporting student growth through both research mentorship and classroom instruction.

Dr. Ahmed is proficient in programming languages including Python, R and SQL. His academic interests span a wide range of machine learning methods, such as Machine Learning, Convolutional Neural Networks (CNN), Neural Networks, Natural Language Processing (NLP) and generative AI. His research includes the development of innovative models like ToFi-ML and Topo-CNN for medical image classification, presented at leading venues such as IEEE and ICCV.

1. Faisal Ahmed." Enhancing Brain Tumor Classification Using Vision Transformers with Colormap-Based Feature Representation on BRISC2025 Dataset".��Submitted paper in a journal.��https://arxiv.org/abs/2603.21234
2. Faisal Ahmed." Brain Tumor Classification from 3D MRI Using Persistent Homology and Betti Features: A Topological Data Analysis Approach on BraTS2020".��Submitted paper in a journal.��https://arxiv.org/abs/2603.13771
3. Faisal Ahmed."��Hybrid Topological and Deep Feature Fusion for Accurate MRI-Based Alzheimer's Disease Severity Classification". Submitted paper in a journal.����ٳٱ��://�����澱��.�ǰ���/������/2602.00956
4. Faisal Ahmed." MRI-Based Alzheimer’s Disease Severity Classification Across Four Stages Using Topological Descriptors and Ensemble Learning ".��Submitted paper in a journal.��arXiv preprint��:����ٳٱ��://�����澱��.�ǰ���/������/2601.00918
5. Faisal Ahmed." Colormap-Enhanced Vision Transformers for MRI-Based Multiclass (4-Class) Alzheimer’s Disease Classification".  Submitted paper in a journal.��arXiv preprint arXiv:2512.16964.����
6. Faisal Ahmed." PseudoColorViT-CXR: Colormap-Enhanced Vision Transformers for Tuberculosis and Pneumonia Detection from Grayscale Chest X-ray Images". 2026 International Conference on Artificial Intelligence, Computer, Data Sciences and Applications (ACDSA), Boracay Island, Philippines, 2026, pp. 1-7, doi: 10.1109/ACDSA67686.2026.11467813.��
7. Faisal Ahmed." RepViT-CXR: A Channel Replication Strategy for Vision Transformers in Chest X-ray Tuberculosis and Pneumonia Classification".��arXiv preprint arXiv:2509.08234 (2025).����Accepted for presentation at the AABIP 2026 Annual Conference and will also be published in the Journal of Bronchology and Interventional Pulmonology.��

8. Richa Rawat and Faisal Ahmed." Efficient Breast and Ovarian Cancer Classification via ViT-Based Preprocessing and Transfer Learning ".����arXiv preprint arXiv: 2509.18553 (2025). (Abstract accepted and paper selected for oral presentation at the NxT AI Conference 2025.) 

9. Faisal Ahmed.��" Addressing High Class Imbalance in Multi-Class Diabetic Retinopathy Severity Grading with Augmentation and Transfer Learning."�� arXiv preprint arXiv:2507.17121 (2025). [Review paper for publication in SN Computer Science]

10. Faisal Ahmed. “Transfer Learning with EfficientNet for Accurate Leukemia Cell Classification.”  arXiv preprint arXiv:2508.06535 (2025). (Abstract accepted and paper selected for oral presentation at the NxT AI Conference 2025.)

11. Faisal Ahmed. “Topological Signatures vs. Gradient Histograms: A Comparative Study for Medical Image Classification.” arXiv preprint arXiv:2507.03006 (2025). [Review paper for publication in Biomedical Signal Processing and Control] 

12. Faisal Ahmed. “HistoViT: Vision Transformer for Accurate and Scalable Histopathological Cancer Diagnosis.”  arXiv preprint arXiv:2508.11181 (2025). [Review paper for publication in SN Computer Science]

13. Faisal Ahmed . “HOG-CNN: Integrating Histogram of Oriented Gradients with Convolutional Neural Networks for Retinal Image Classification.” Published in Journal of Imaging Informatics in Medicine (2026).��https://doi.org/10.1007/s10278-026-01893-4 

14. Faisal Ahmed, Mohammad Alfrad Nobel Bhuiyan,  and Baris Coskunuzer. “Topo-CNN: Retinal Image Analysis with Topological Deep Learning.” Published in Journal of Imaging Informatics in Medicine. 2025 Jun 25:1-7. https://doi.org/10.1007/s10278-025-01575-7

15. Faisal Ahmed, MD Joshem Uddin.��"OcuViT: A  Vision Transformer-Based Approach for Automated Diabetic Retinopathy and AMD Classification."  Published in Journal of Imaging Informatics in Medicine (2025): 1-11. https://doi.org/10.1007/s10278-025-01676-3  

16. Emanuele Bossi and Faisal Ahmed. "Enhancing Sentiment Analysis with Feature Extraction and Dimensionality Reduction in Traditional Machine Learning Models".��In Intelligent Systems Conference, pp. 166-183. Cham: Springer Nature Switzerland, 2025.��

17. Faisal Ahmed, Taymaz Akan, Fatih Gelir, Mohammad Alfrad Nobel Bhuiyan. " Alzheimers 3D MRI diseases detection with Topological Machine Learning." (Accepted paper in AMIA 2025 Clinical Informatics  Conference by the Scientific Program Committee (SPC))

18. �󲹾������������󳾱�� and Baris Coskunuzer. "Topo-Net: Retinal Image Analysis with Topological Deep Learning." medRxiv (2024): 2024-02. [Pre-print paper accepted and published by medRxiv journal]

19. �󲹾������������󳾱��, Brighton Nuwagira, Furkan Torlak, and Baris Coskunuzer. "Topo-CXR: Chest X-ray TB and Pneumonia Screening with Topological Machine Learning." In Proceedings of the IEEE/CVF International Conference on Computer Vision, pp. 2326-2336. 2023.

20. Faisal Ahmed ,  Ankur Yadav, Ovidiu Daescu, Reyhan Gedik, and Baris Coskunuzer. "Histopathological Cancer Detection with Topological Signatures." In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp. 1610-1619. IEEE, 2023.

21. Faisal Ahmed and Baris Coskunuzer. "ToFi-ML: Retinal Image Screening with Topological Machine Learning." In Annual Conference on Medical Image Understanding and Analysis, pp. 281-297. Cham: Springer Nature Switzerland, 2023.