Calendar of Events

Speaker: Viviana Acquaviva, CUNY

Abstract:  Recent developments in machine learning and AI have given us a new set of tools to answer science questions, while creating new challenges in terms of trust and interpretability. My research focuses on the process of learning from simulations using these tools. I will show a few examples from my Astrophysics work, on validating cosmological simulations and formulating hypotheses for the physical model that drives galaxy evolution processes. I will then move on to current research in climate science, where we are developing custom metrics to assess similarity in climate models outputs, and using representation learning to reconstruct full spatiotemporal fields from sparse and biased ocean data. I will conclude with some lessons learned in applying AI across disciplines, and some considerations and open questions on how AI is changing the way we do science.