My complete curriculum vitae is available at this link. For more information about my research, you can also visit my ResearchGate and Google scholar profiles.
I am focused on designing security frameworks that enhance the privacy and trustworthiness of AI-driven systems. This includes:
- AI Model Robustness
- Data Privacy in AI Applications
- Trustworthy Machine Learning
- Adversarial Machine Learning
- Federated Learning Security
These areas play a crucial role in ensuring the safe deployment of AI systems across various domains, addressing risks in data leakage, manipulation, and misuse.
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▶️ New Book: Check out my latest book, "Trustworthy AI: From Theory to Practice", where I explore the theoretical foundations and practical implementations of trustworthiness in AI systems. -
▶️ More details are available at my personal website.
I am interested in Data Privacy and Cyber Security for machine learning and deep learning, covering the theoretical, applicative, and computational aspects. My primary research interests lie broadly in deep learning.
- Cyber Security
- Malware Analysis
- Artificial Intelligence
- Machine/Deep Learning Methods for Cyber-Security,
- Distributed machine learning
- Homomorphic encryption based Privacy-preserving machine learning.