I am a Computer Science researcher with a multidisciplinary focus spanning Computer Science, Psychology, and Public Health. My work integrates Explainable AI (XAI), Deep Learning, Computer Vision, and Natural Language Processing to solve real-world problems in healthcare, cybersecurity, and cultural heritage.

• 🔭 I’m currently working on AI/ML projects – from image classification to LLM-powered applications.
• 🌱 I’m currently learning Quantum Computing, MLOps, Bioinformatics, and Reinforcement Learning.
• 👯 I’m looking to collaborate on open-source AI/ML and research projects.
• 📫 How to reach me: connect on LinkedIn.

Computer Science · Psychology · Public Health

Focus: Multidisciplinary research integrating AI/ML with healthcare, cybersecurity, LLM, NLP, Computer vision, public health, and cognitive sciences.

1. Assessing Large Language Models on Zero-Shot Poetry Summarization Using ROUGE, BERT, and LLM-as-a-Judge Metrics
   Md. Ismiel Hossen Abir, Nayeema Ferdous, Afsara Tasnim, Nabiha Mustaqeem
   2026 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE)
   Year: 2026 | Conference Paper | Publisher: IEEE
   🔗 DOI: 10.1109/ICECTE69292.2026.11429378

2. BERT-Based Malicious URL Detection with Explainable AI: A Comparative Analysis of Traditional and Transformer Models
   Md. Ismiel Hossen Abir, Sanjana Islam Kasfia, Abir Mahmud Shahariar
   2026 5th International Conference on Electrical, Computer & Telecommunication Engineering (ICECTE)
   Year: 2026 | Conference Paper | Publisher: IEEE
   🔗 DOI: 10.1109/ICECTE69292.2026.11429459

3. Egyptian Hieroglyphics Handwriting Character Classification Using CNN with Explainable AI: SHAP and LIME
   Md. Ismiel Hossen Abir, M D. Shaek Ahmed, Nurul Bashar, Hasibul Islam Peyal
   2025 International Conference on Electrical, Computer and Communication Engineering (ECCE)
   Year: 2025 | Conference Paper | Publisher: IEEE
   🔗 DOI: 10.1109/ECCE64574.2025.11013519

4. XGBClassifier and Explainable AI for Disease Classification from Patient Symptom and Demographic Data with Late Fusion
   Md. Ismiel Hossen Abir, Nurul Bashar, Md. Shaek Ahmed, Hasibul Islam Peyal
   2025 International Conference on Electrical, Computer and Communication Engineering (ECCE)
   Year: 2025 | Conference Paper | Publisher: IEEE
   Cited by: 1 paper
   🔗 DOI: 10.1109/ECCE64574.2025.11013373

5. Explainable Multiclass Blood Cell Classification: Combining Custom CNNs with SHAP
   Md. Ismiel Hossen Abir, Shantanu Dey Anik, Hasibul Islam Peyal
   2025 International Conference on Electrical, Computer and Communication Engineering (ECCE)
   Year: 2025 | Conference Paper | Publisher: IEEE
   Cited by: 2 papers
   🔗 DOI: 10.1109/ECCE64574.2025.11012986

6. Integrating SHAP, LIME and Grad-CAM with CNNs for Transparent Kidney Condition Classification
   Md. Ismiel Hossen Abir, Hasibul Islam Peyal, Sumya Rashid, Md Jahid, Syed Mustafizur Rahman Chowdhury, Md. Nazrul Islam Mondal
   2024 27th International Conference on Computer and Information Technology (ICCIT)
   Year: 2024 | Conference Paper | Publisher: IEEE
   Cited by: 2 papers
   🔗 DOI: 10.1109/ICCIT64611.2024.11021878

📚 Full list available on ResearchGate and ORCID.

Python

JavaScript

Codeforces

HTML5

CSS3

Bootstrap

JavaScript

React.js

Next.js

FastAPI

Python

PostgreSQL

MySQL

Oracle

TensorFlow	PyTorch	Hugging Face	Scikit-learn	OpenCV	Pandas	NumPy
Jupyter	Kaggle	Streamlit	Anaconda	Flask	Django	Keras

Advanced AI/ML/LLM Frameworks & Libraries (No Repetition):

Core AI/ML Research Areas:

• Image Classification
• Object Detection
• Image Segmentation
• Natural Language Processing (NLP)
• Large Language Models (LLM)
• Retrieval-Augmented Generation (RAG)
• Explainable AI (XAI) – SHAP, LIME, Grad-CAM
• Quantum Machine Learning (QML)

VS Code

Git

GitHub

Figma

• 🥇 Notebooks Master – Kaggle Profile
• 📊 Datasets Master – Kaggle Datasets