Abstract: Ice formation plays an important role in a wide range of contexts, from serving as nuclei for clouds in the upper atmosphere to forming on the surfaces of aircraft […]
Abstract: Global transition to clean energy relies on the development of efficient hydrogen storage materials and hydrogen evolution reaction (HER) catalysts—two primary chemistries investigated in this thesis. MXenes, a family […]
Abstract: Despite recent advances in catalytic conversion of plastic waste into high-value chemicals, the interactions between the polymers and catalysts, which are highly porous nanomaterials, are not well understood. Fundamental […]
With finite resources to complete tasks like monitoring, coverage, and search, the challenge lies in identifying and performing tasks that can change both in frequency and location. One potential solution […]
Abstract: Proteins perform many important biological functions while also avoiding fouling in an aqueous and crowded cellular environment. Their surfaces have evolved to be both chemically heterogeneous (containing nonpolar, polar, […]
Graph Neural Networks (GNNs) are the tool of choice for scalable and stable learning in graph-structured data applications involving geometric information. My research addresses the fundamental questions of how GNNs […]
AI agents, both in the physical and digital worlds, should generalize from their training data to three increasingly difficult levels of deployment: training tasks and environments, training tasks and environments […]
Neural compression, which pertains to compression schemes that are learned from data using neural networks, has emerged as a powerful approach for compressing real-world data. Neural compressors often outperform classical […]
The three-dimensional organization of chromatin within the cell nucleus plays a critical role in regulating gene expression, maintaining genome stability, and guiding cellular responses to environmental cues. Despite advances in […]
Directly training deep learning models for applications in large-scale cyber-physical systems can be intractable due to the large number of components and decision variables. Instead, we focus on exploiting spatial […]
