Computing and Math: Oral Sessions

My research opens the possibility of routing-based AI that can solve the problem of one-size-fits-all modeling by directing attention to the most relevant patterns in complex data, improving accuracy, trustworthiness, and decision-making in real-world settings.

Here is What’s Possible: My research demonstrates how AI-driven analysis of 3D face masks and face-swapping technologies can help identify and mitigate emerging threats to biometric security systems.

Through our research, we explore the possibility of whether the presence of generative AI tools changes the kinds of programming errors students make in a data structures and algorithms undergraduate course. 

Here is What’s Possible: My research enables the effective integration of machine learning into biological systems with sparse and costly data, improving the robustness of modeling and understanding of retinal damage.

My research focuses on building machine-learning surrogate models for diffusion models.