Research

My work spans explainable AI, pattern mining, human-centered systems, and applied machine learning. I am especially interested in building computational methods that produce interpretable insights from complex real-world data.

Causal Pattern Mining in Large-Scale Health Insurance Survey Data

Goal: Explainable AI for Understanding Switching Behavior in Statutory Health Insurance

  • Designed and implemented a multi-stage analysis pipeline combining causal inference and pattern mining techniques.
  • Applied Minimum Description Length (MDL) based pattern extraction to identify behavioral drivers for switching.
  • Conducted advanced data preprocessing, statistical validation, and robustness checks on large-scale survey datasets.
  • Produced visual summaries and interpretable insights supporting research conclusions and potential publication.
  • Implemented pattern mining techniques and conducted the literature review for algorithmic approaches.

GitHub Repository: https://github.com/Farhanmq/DS_Project

Paper: Available on request

Human Learning System Prototype – Universität des Saarlandes

  • Conducted survey studies and structured observation sessions to derive design principles for educational technology.
  • Evaluated prototype performance through user studies and structured field observations.
  • Documented experimental findings and proposed improvements based on behavioral analysis.

Report: Available on request

Bachelor’s Thesis (Peer-reviewed Publication) – National University of Computer and Emerging Sciences

Title: Brain Hemorrhage Detection and Segmentation using Deep Learning

  • Developed deep learning models for detecting and localizing intracranial hemorrhages in CT scans.
  • Implemented CNN-based architectures, including Faster R-CNN and U-Net.
  • Performed medical imaging preprocessing, model training, and evaluation using clinically relevant metrics.
  • Contributed to dataset preparation and experimental evaluation pipelines.
  • Resulted in a peer-reviewed publication.

Publication: Hassan, N. et al., International Journal of Computer Science and Engineering, “Brain Hemorrhage Detection using ML/DL” View publication

Full Thesis PDF: Available on request