CS PhD @ Texas State

Research Interests

Eye Tracking · Computer Vision · Machine Learning · Biometrics · Generative AI · Vision-Language Models · Scientific Reproducibility

Projects

Project A: MMF-Gait: A Multi-Model Fusion-Enhanced Gait Recognition Framework Integrating Convolutional and Attention Networks

This work integrates multiple deep learning models to improve the accuracy and robustness of gait-based identification.

Python PyTorch Biometrics

Related publication

Project B: A vision-language approach for detecting and classifying floating debris on aquatic surfaces

Detects floating debris and objects with VLMs; supports real-time decision making.

VLM YOLO Real-time

Related publication

Publications

  1. Hasan, Kamrul, Md Zasim Uddin, Ausrukona Ray, Mahmudul Hasan, Fady Alnajjar, and Md Atiqur Rahman Ahad. "Improving gait recognition through occlusion detection and silhouette sequence reconstruction." IEEE Access (2024). PDF
  2. Ray, Ausrukona, Md Zasim Uddin, Kamrul Hasan, Zinat Rahman Melody, Prodip Kumar Sarker, and Md Atiqur Rahman Ahad. "Multi-Biometric Feature Extraction from Multiple Pose Estimation Algorithms for Cross-View Gait Recognition." Sensors 24, no. 23 (2024): 7669. PDF
  3. Uddin, Md Zasim, Kamrul Hasan, Md Atiqur Rahman Ahad, and Fady Alnajjar. "Horizontal and Vertical Part-wise Feature Extraction for Coss-view Gait Recognition." IEEE Access (2024). PDF
  4. Doula, Md Shafi Ud, Kamrul Hasan, Chutiporn Anutariya, and Md Ashraful Alam. "A vision-language approach for detecting and classifying floating debris on aquatic surfaces." In Eighth International Conference on Machine Vision and Applications (ICMVA 2025), vol. 13734, pp. 119-127. SPIE, 2025. PDF
  5. Hasan, Kamrul, Khandokar Alisha Tuhin, Md Rasul Islam Bapary, Md Shafi Ud Doula, Md Ashraful Alam, Md Atiqur Rahman Ahad, and Md Zasim Uddin. "MMF-Gait: A Multi-Model Fusion-Enhanced Gait Recognition Framework Integrating Convolutional and Attention Networks." Symmetry 17, no. 7 (2025): 1155. PDF
  6. Hasan, Kamrul, et al. "Quantitative and Qualitative Comparison of Generative Models for Subject-Specific Gaze Synthesis: Diffusion vs GAN." arXiv preprint arXiv:2511.09867 (2025). PDF
  7. Mahamood, M. N., Hasan, M. I., Rasheduzzaman, M., Ray, A., Doula, M. S. U., and Hasan, Kamrul. "Mam-App: A Novel Parameter-Efficient Mamba Model for Apple Leaf Disease Classification." arXiv preprint arXiv:2601.21307 (2026). PDF
  8. Hasan, Kamrul, and Oleg V. Komogortsev. "Eye Feel You: A DenseNet-driven User State Prediction Approach." arXiv preprint arXiv:2601.21045 (2026). PDF
  9. Hasan, Kamrul, and Oleg V. Komogortsev. "Privatization of Synthetic Gaze: Attenuating State Signatures in Diffusion-Generated Eye Movements." arXiv preprint arXiv:2601.21057 (2026). PDF
  10. Qian, C. S., Aziz, S., Hasan, K., and Komogortsev, O. V. "Why do we need high-fidelity synthetic eye movement data and how should they look like?" bioRxiv (2025). PDF

Professional Experience

Organization Role Period Notes
Next Solution Lab Artificial Intelligence Engineer Aug 2023 - Aug 2025 Worked on DeepICR Project.

Seminar and Workshop

Open Source