HCI Researcher

The petitioner proposes to continue research in developing trustworthy and human-centered artificial intelligence systems, specifically focusing on Large Language Model (LLM) safety. The work involves creating advanced LLM-based systems that enhance productivity while implementing safeguards against bias and unfair outcomes. The intended impact is to ensure AI-driven applications operate responsibly and equitably within the United States.

The petitioner proposes to continue her research in the field of artificial intelligence, specifically focusing on developing algorithms for effective collaboration between humans and AI. Her work aims to improve the safety, interpretability, and usability of autonomous systems through innovations in explainable planning and secure AI action synthesis. The endeavor seeks to bridge technical innovation with practical, socially responsible deployment of AI systems.

The petitioner proposes to design accessible, ethical, and human-centered AI systems that bridge the gap between algorithmic efficiency and human-computer interaction. Her work focuses on creating adaptive user interfaces and secure digital infrastructures that ensure machine learning tools are usable by diverse populations. The intended impact includes improving outcomes and equity in healthcare, education, and cybersecurity through intuitive AI design.

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.