Principal Machine Learning Scientist

The petitioner proposes to continue research on developing diagnostic and enhancement approaches to improve the robustness of artificial intelligence-enabled software systems. This work specifically targets safety-critical applications such as facial recognition and self-driving vehicles to strengthen cybersecurity and ensure safe deployment.

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 computational and theoretical models to explain the functioning of modern AI systems, aiming to unlock the 'black box' of artificial intelligence. This work focuses on creating interpretable and trustworthy intelligent systems to ensure safe deployment in national security, public health, and finance.

The petitioner proposes to develop advanced machine learning and deep learning frameworks to predict user intent during online interactions. This work aims to create secure and efficient customer experiences that help U.S. businesses safeguard sensitive systems and drive revenue through real-time recommendation optimization.