Apoorva develops synthetic benchmarks to help validate Terra AI’s generative geological models and Bayesian inference methods end-to-end. She is currently pursuing her Bachelor’s in mathematics and Master’s in Computer Science at Stanford University, with minors in biology and political science. Previously, she has conducted research in privacy law and legal uncertainty benchmarks at the Stanford Regulation, Evaluation, and Governance Lab (RegLab), human memory and decision-making at the Stanford Graduate School of Business, Bayesian models for persuasion, coral reef ecology, and analytic number theory. She is particularly interested in modeling complex dynamic systems that are difficult to observe directly, but in which careful design and rigorous validation enable reasoning from incomplete and noisy information. Outside of work, she loves to paint, swim and scuba dive, cook, and explore the great outdoors. Why I joined Terra AI I was inspired by Terra AI’s quantitative and rigorous approach to subsurface modeling, the company’s values of safety and sustainability, and its mission to tackle some of the most consequential challenges in energy and resource development with an awareness of the environment and social impact of the industry. The people here are amazing and brilliant, and I feel very lucky to be able to learn from them.