Atiye Sadat Hashemi

Atiye Sadat Hashemi is a Research Fellow at the Academy of Information Technology, Halmstad University. Her work bridges machine learning and healthcare innovation, with a focus on developing secure and interpretable AI models for medical applications. She maintains an active research profile through publications and collaborative projects in data-driven healthcare solutions.

Research Focus: Her expertise spans machine learning applications in disease surveillance, precision medicine, and adversarial robustness. Key areas include:

• Optimizing ML for real-time disease outbreak detection using anomaly detection
• Advancing personalized treatment strategies through data-driven models
• Enhancing model security against adversarial attacks in critical domains
• Developing privacy-preserving synthetic health data generation techniques

Publication Trends (2022-2024): Her recent works demonstrate a consistent focus on healthcare-AI integration, with emphasis on:

• Anomaly detection systems for epidemiological monitoring
• Privacy-enhancing technologies for medical data
• Explainable AI methods for clinical decision support
• Robustness improvements for safety-critical ML applications

Methodologies frequently involve generative adversarial networks, graph neural networks, and time-series analysis.