About
Aspiring AI/ML researcher passionate about developing secure, ethical, and human-centered solutions through explainable and trustworthy machine learning. Seeking to advance research in AI security, privacy-preserving methods, and generative AI, while emphasizing real-world impact and interdisciplinary collaboration.
Research Interests
Computer Vision
Generative AI
Privacy-Preserving AI
Machine Learning
Explainable AI (XAI)
Healthcare Informatics
Skills
Programming Languages
Python, SQL, C++.
Machine Learning & Data Science Tools
Pandas, NumPy, Matplotlib, Scikit-learn, TabNet, SHAP.
Software & Platforms
Azure, Google Colab, Jupyter Notebook, VS Code, Microsoft Office, Teams, Google Workspace, Slack.
Research Interests
Computer Vision, AI Security, Privacy-Preserving AI, Machine Learning, Generative AI, Transformers, Explainable AI (XAI), Healthcare Informatics.
Publications
Leveraging Hypertuned Hybrid TabNet Transformer for Enhanced Heart Disease Prediction with Improved SHAP Explanations
Published by
Scientific Reports (Nature Portfolio, Q1 Journal)
Summary
Authored a research paper detailing the development and application of a hypertuned hybrid TabNet Transformer model for advanced heart disease prediction, incorporating SHAP explanations for enhanced interpretability. Currently under revision after peer review.
Languages
Shina
Native
Urdu
Native
English
Fluent