About Me
PhD student in Computer Science with research interests in machine learning, computer vision, natural language processing, multimodal learning, and medical imaging. Experienced in designing deep learning systems for healthcare applications and developing AI-driven solutions for clinical decision support.
Research Interests
- Machine Learning
- Deep Learning
- Computer Vision
- Medical Imaging
- Natural Language Processing
- Multimodal Learning
- Medical Foundation Models
Education
- University of Kentucky — PhD in Computer Science (2025–Present)
- BRAC University — MSc in CSE, CGPA 4.00/4.00
- BRAC University — BSc in CSE, CGPA 3.91/4.00
Professional Experience
Graduate Teaching Assistant
University of Kentucky | Aug 2025 – Present
- Grader for Data Structures and Algorithms.
- Secondary Instructor for Multimedia Systems and Computer Graphics.
Lecturer
BRAC University | May 2022 – Jun 2025
- Object-Oriented Programming
- Programming Languages (Java, Python)
- Discrete Mathematics
- Database Systems
- Compiler Design
- Computer Networks
- Digital Logic Design
Instructor
Codingal | May 2022 – Sep 2022
- Taught programming and computational thinking to school students.
Student Tutor
BRAC University | Jan 2020 – Jan 2022
- Taught Statistics and Probability.
- Mentored students in Compiler Design.
Publications
An Analysis of Clinical and Sociodemographic Data on Congenital Syphilis Using Gaussian Naive Bayes and XAI Modeling
N. Nayla and M. Haque
2024 International Conference on Emerging Techniques in Computational Intelligence (ICETCI)
An Effective Method for Detecting Tomato Leaf Disease Using Distributed Neural Networks
T. Afroz, T. M. Shoumik, S. Hossain Emon, S. Hossain and N. Nayla
ICCIT 2023
Product Market Demand Analysis Using NLP in Banglish Text with Sentiment Analysis and Named Entity Recognition
M. S. Hossain, N. Nayla and A. A. Rassel
CISS 2022
Technical Skills
- Programming Languages: Python, Java, JavaScript, C, C++
- Machine Learning & AI: Deep Learning, Computer Vision, Medical Image Analysis, Multimodal Learning, Natural Language Processing
- Frameworks & Libraries: PyTorch, TensorFlow, Keras, HuggingFace Transformers, OpenCV, Scikit-learn, NLTK, SpaCy, NumPy, Pandas
- Deep Learning Architectures: Vision Transformers (ViT), Swin Transformer, CLIP, CNNs, Transformer-based Models
- Tools: Git, Docker, LaTeX, Google Cloud, MySQL, Jupyter Notebook
- Platforms: Linux, Windows, Web
Featured Research Projects
FiLM-BCR: AI-Driven Multimodal Platform for Longitudinal Breast Cancer Risk Prediction
Developed a multimodal deep learning framework integrating mammography images and clinical data for long-term breast cancer risk prediction using transformer-based architectures and multimodal attention fusion.
Multimodal Continual Learning for Breast Cancer Segmentation and Classification
Designed a continual learning framework for multimodal breast cancer analysis while mitigating catastrophic forgetting across sequential tasks.
Alzheimer Disease Classification
Developed machine learning models for multiclass Alzheimer's disease classification using MRI images for early-stage diagnosis support.
Multi-Domain Multimodal Cross-Disease Detection
Investigated multimodal learning by combining heterogeneous data from Alzheimer's disease and congenital syphilis datasets for generalized healthcare analytics.
Honors & Awards
- Academic Excellence Award, Master's Program, BRAC University
- Graduate Merit Scholarship (100% Tuition Waiver), BRAC University
- Academic Highest Distinction, Undergraduate, BRAC University
- Vice Chancellor's Award (6 Semesters)
- Dean's Award (2 Semesters)
- Merit-Based Scholarship (50% Tuition Waiver)