Assistant Professor

The petitioner proposes to develop and implement advanced cryptographic techniques and innovative machine learning models. This work aims to ensure secure data transmission and analysis across healthcare systems, Internet-of-Things (IoT) networks, and critical digital infrastructure. The endeavor focuses on enhancing cybersecurity within the framework of artificial intelligence applications.

The petitioner proposes to continue his research in computer science by developing machine learning algorithms designed to improve the detection of anomalous and out-of-distribution data. This work focuses on creating better datasets and advancing artificial intelligence to enhance cybersecurity measures and combat cybercrime. The endeavor aims to improve safety and security in applications ranging from autonomous vehicle navigation to intelligent surveillance systems.

The petitioner proposes to develop advanced machine learning algorithms to improve cybersecurity, wireless sensor networks, and healthcare technologies. His work focuses on creating tools for Android malware detection, chatbot-driven health management, and anomaly detection in real-time data systems.

The petitioner proposes to employ machine learning techniques to build advanced security analysis tools that enhance the security and privacy of connected vehicles and software systems. These tools are designed to provide real-time threat detection, improved anomaly recognition, and greater protection of user data across complex digital ecosystems. The work specifically focuses on deep learning and encryption-based solutions to enable secure behavior analysis and identify code vulnerabilities.