Security & Adversarial ML
Defending AI systems against adversarial attacks, malware, binary analysis, and behavioral authentication.
4 ProjectsBiomedical AI
Applying deep learning to medical imaging, disease detection, and multimodal clinical decision support.
3 Projects
Securing Interpretable Deep Learning Systems
The growing integration of deep learning (DL) models into high-stakes domains, such as healthcare, finance, and autonomous syst...
Comprehensive Evaluation of Adversarial Robustness in Deep Learning
Adversarial attacks pose a serious challenge to the reliability and security of deep learning (DL) models. These attacks, often...
Explainable Artificial Intelligence for Trustworthy and Transparent Decision-Making in Medical Applications
TThe project seeks to address the growing need for transparency, accountability, and interpretability in artificial intelligenc...
Behavioral Biometrics for Continuous and Adversarially Robust User Authentication on Smartphones
Traditional authentication methods—such as passwords, PINs, and even biometric systems (fingerprint, facial recognition)—typica...
Multimodal, Explainable, and Adversarially-Robust Deep Learning for Alzheimer’s Disease Progression Detection
Traditional authentication methods—such as passwords, PINs, and even biometric systems (fingerprint, facial recognition)—typica...
Explainable Dynamic Ensemble Learning with Late Fusion of Multimodal Data for Intelligent Decision Support
Traditional authentication methods—such as passwords, PINs, and even biometric systems (fingerprint, facial recognition)—typica...
Explainable and Dynamic Ensemble Models for ICU Mortality and Length-of-Stay Prediction
Traditional authentication methods—such as passwords, PINs, and even biometric systems (fingerprint, facial recognition)—typica...
Funding & Support
