Lily Xu

Research Abstract:

Planetary health recognizes the inextricable link between human health and the health of our planet. Our planet’s growing crises include biodiversity loss, with animal population sizes declining by an average of 70% since 1970, and maternal mortality, with 1 in 49 girls in low-income countries dying from complications in pregnancy or birth. Overcoming these crises will require effectively allocating and managing our limited resources. My research develops data-driven AI decision-making methods to do so, overcoming the messy data ubiquitous in these settings. I’ll present technical advances in multi-armed bandits, robust reinforcement learning, and causal inference, addressing research questions that emerged from on-the-ground challenges across conservation and maternal health. I’ll also discuss bridging the gap from research and practice, with anti-poaching field tests in Cambodia, field visits in Belize and Uganda, and large-scale deployment with SMART conservation software.

Bio:

Lily Xu is a computer science PhD student at Harvard developing AI techniques to address planetary health challenges, with a focus on biodiversity conservation and public health. Her research enables effective decision-making in these high-stakes settings using methods across machine learning, sequential planning, and causal inference. Her work building the PAWS system to predict poaching hotspots has been deployed in multiple countries and is being scaled globally through integration with SMART conservation software. Lily co-organizes the Mechanism Design for Social Good (MD4SG) research initiative and serves as AI Lead for the SMART Partnership. Her research has been recognized with best paper runner-up at AAAI, the INFORMS Doing Good with Good OR award, a Google PhD Fellowship, and a Siebel Scholarship.