Lecturer in Computer Science • Machine Learning & Cyber Security Researcher
Specialized in federated learning, intrusion detection, explainable AI, and video anomaly detection.

• Federated Learning
  Privacy-preserving distributed training, FL aggregation pipelines, decentralized IDS
• Intrusion Detection Systems (IDS)
  CNN, LSTM, Attention, hybrid deep learning models, temporal feature selection
• Cyber Security & Network Threat Modeling
  Ransomware detection, adversarial robustness, phishing detection
• Explainable AI (XAI)
  SHAP, LIME, explanation stability under adversarial conditions
• Anomaly Detection
  Video anomalies, two-stage CNN + Vision Transformer pipelines

• Cross-Domain Adversarial Robustness and Explainability Stability in Phishing Detection Systems
  Md. Rifat Hassan, J. A. Nabin, Toyeer-E-Ferdoush.
  IEEE International Conference on Power, Electronics, Communications, Computing, and Intelligent Infrastructure (PECCII) · DOI

• Unraveling the Factors of Procrastination: An Insightful Assessment of Procrastination Levels Through ML and XAI
  Mariam Sarker, Anwar Hossain Efat, Maria Afrin Khan, Minhaz Zibran, J. A. Nabin.
  IEEE 5th International Conference on Computing and Machine Intelligence (ICMI) · DOI

• A Novel File Entropy Dataset for Crypto-Ransomware Detection Using Machine Learning
  J. A. Nabin, M. M. Haque. [First Author]
  2nd International Conference on Machine Intelligence and Emerging Technologies (Springer LNNS) · DOI

• Federated Deep Learning for Cybersecurity and Intrusion Detection in Decentralized Networks
  N. Mia, J. A. Nabin, S. Mohammad, M. Hasan, F. S. Tamim, D. M. Das.
  IEEE 3rd International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA) · DOI

• A Novel Temporal-Aware Adaptive Feature Selection Strategy for Network Intrusion Detection Systems
  N. Mia, M. M. H. Gazi, J. A. Nabin, F. S. Tamim, S. Mohammad, M. R. U. Islam.
  IEEE Global Conference in Emerging Technology (GINOTECH) · DOI

• Two-Stage Vision Transformer-Based Framework for Anomaly Detection and Classification in Surveillance Videos
  M. Hasan, J. A. Nabin, N. Mia, F. S. Tamim, S. Mohammad, D. M. Das.
  IEEE International Conference on Electrical, Computer and Communication Engineering (ECCE) · DOI

• From Prediction to Causation: An Interpretable Diagnosis of Procrastination Using XAI with ML
  Maria Afrin Khan, Anwar Hossain Efat, Mariam Sarker, J. A. Nabin.
  28th International Conference on Computer and Information Technology (ICCIT) · DOI

• Federated Machine Learning for Cardiovascular Risk Assessment: A Decentralized XGBoost Approach
  M. S. Alom, S. S. Akhi, S. N. Borsha, N. Mia, F. S. Tamim, J. A. Nabin.
  IEEE International Conference on Quantum Photonics, Artificial Intelligence, and Networking (QPAIN) · DOI

ML / AI:
Python • PyTorch • TensorFlow • Scikit-Learn • Keras • OpenCV • SHAP • LIME
Federated Learning:
FL aggregation pipelines • privacy-preserving distributed training
Core Tools:
Git • Bash • SQL
Research Tools:
Jupyter • LaTeX • Pandas • NumPy

• Website: https://nabin47.github.io
• LinkedIn: https://www.linkedin.com/in/ahmednabin/
• Email: janabin.research@gmail.com