I am a Computer Science and Engineering graduate with a strong interest in Artificial Intelligence, Machine Learning, Natural Language Processing, and Intelligent Systems.
My interests focus on developing practical AI solutions and conducting research-oriented projects that address real-world problems.
- 🎓 B.Sc. in Computer Science & Engineering
- 🤖 Interested in AI, Machine Learning & NLP
- 🔬 Research-oriented and passionate about intelligent systems
- 📚 Interested in graduate research and advanced study
- 💡 Enjoy building practical, data-driven solutions
- 🌱 Continuously learning and exploring emerging AI technologies
- Artificial Intelligence
- Machine Learning
- Natural Language Processing
- Large Language Models
- Generative AI
- Explainable AI
- Intelligent Recruitment Systems
- AI for Healthcare
- Data-Driven Decision Making
An AI-powered resume screening and candidate ranking system using NLP, TF-IDF, semantic embeddings, and machine learning techniques.
Key areas:
- Resume information extraction
- Skill and job-category matching
- TF-IDF & cosine similarity
- Semantic embeddings
- Candidate ranking
- Explainable scoring
- LLM-based analysis
A machine learning research project using the PHQ-9 questionnaire and additional lifestyle and demographic factors to analyze depression severity.
Key areas:
- PHQ-9 based data
- Feature engineering
- Classification
- Logistic Regression
- Random Forest
- Model evaluation
- Confusion matrix & performance analysis
A machine learning-based heart disease detection system using clinical, demographic, behavioral, and lifestyle-related health features.
Key areas:
- Health data preprocessing
- Feature selection
- Multiple machine learning models
- XGBoost, Random Forest & Decision Tree
- SVM, Naive Bayes & MLP
- Model performance comparison
- SHAP-based interpretability
- ROC-AUC & precision-recall analysis
- Ensemble learning
- Probability calibration
A hybrid recommendation engine integrating Natural Language Processing and machine learning to suggest books based on users' emotional resonance and preferred genres.
Key areas:
- Natural Language Processing
- Emotion & sentiment classification
- Imbalanced data handling (ADASYN)
- Classical ML (SVM, Random Forest)
- Transformer evaluation (BERTweet, XLM-R)
- Emotion detection
- Recommendation systems
Bachelor of Science in Computer Science & Engineering
Daffodil International University
- Large Language Models
- Generative AI
- Advanced NLP
- Explainable AI
- Research Methodology
- AI-driven Intelligent Systems
I am interested in connecting with researchers, academics, developers, and professionals working in Artificial Intelligence and related fields.
Building intelligent solutions through research, learning, and experimentation.