Rigorous ideas. Open conversations.

Lina Song is a decision scientist, scholar, and founder working to put rigorous analysis within reach of more people. Her research focuses on healthcare. She holds a PhD in Health Policy / Decision Science from Harvard University and is the founder of Doogooda.

Lina Song is a decision scientist, scholar, and founder working to put rigorous analysis within reach of more people. Her research examines how institutions, incentives, and resources shape healthcare, using empirical studies, economic models, and disease modelling. She holds a PhD in Health Policy / Decision Science from Harvard University and was formerly a tenure-track Assistant Professor at UCL School of Management. At Doogooda, she is working to translate research-grounded methods into software for healthcare operating decisions.

Lina Song is a decision scientist, scholar, and founder whose work asks how more people can use rigorous analysis when making consequential choices. Her research examines physician integration, hospital closures, patient choice, and the long-term consequences of prevention and treatment. Across these questions, she works with empirical research, economic models, disease modelling, and causal methods.

She holds a PhD in Health Policy / Decision Science from Harvard University and was formerly a tenure-track Assistant Professor at UCL School of Management. Her earlier training was in mathematics at Caltech and statistics at Yale. A research-led project at Moorfields helped shape her interest in who has access to the resources behind rigorous analysis.

She is the founder of Doogooda, where she is working to translate research-grounded methods into software for healthcare operating decisions. Through writing and public conversation, she also explores access to analytical capability, the assumptions behind an answer, and whose outcomes count.