Victoria is a postdoctoral investigator at the Woods Hole Oceanographic Institution and former graduate researcher in the Massachusetts Institute of Technology and Woods Hole Oceanographic Institution Joint Program (MIT-WHOI JP), sharing time between the departments of MIT AeroAstro and WHOI Applied Ocean Physics and Engineering. She is currently affiliated with the Robust Robotics Group led by Nicholas Roy (MIT CSAIL), with whom she also completed her doctoral studies, and the Chemical Sensors Laboratory led by Anna Michel (WHOI) on research at the intersection of artificial intelligence, machine learning, environmental science, and numerical modeling.

Her research goal is to enable intelligent mobile scientific observatories for robust and autonomous long-term monitoring of complex, dynamic environments. She is particularly motivated by geochemical contexts in which a robot may be tasked with mapping greenhouse gases or toxic chemicals in aquatic or atmospheric systems. Victoria's SM thesis presented a novel robotic decision-making framework for maximum-seeking in potentially transient environments, and her PhD thesis (defended Dec 2022) presented a full autonomy framework for detecting, predicting, and sampling deep ocean hydrothermal plumes with state-of-the-art autonomous underwater vehicles. Through this work, key challenges on data efficiency in learning, inference over high-dimensional states, and planning in spatiotemporal systems have been key themes. Currently, her work is focused on developing a data-efficient probabilistic model to learn spatiotemporal dynamics from sparse robotic measurements.