Van Savage is a professor in the UCLA Departments of Ecology and Evolutionary Biology as well as Computational Medicine. Additionally, he is chair of the UCLA Computational and Systems Biology undergraduate major, co-chair of the biomathematics training grant, and a core member of the Quantitative and Computational Biosciences (QCB) Institute. His research leverages mathematical and computational tools and combines this with scaling of metabolic processes to understand tumor growth, sleep, vascular pathologies, rates of evolution, and how ecosystem function, stability, and diversity respond to climate change, especially warming. A major goal of my research is to quantify and understand the possible functions, forms, and interactions of biological systems that result in the extraordinary diversity in nature. Complementary to this, he aims to understand how much variation around optima or averages is considered healthy or adaptive versus diseased or disturbed states, which are essentially deviations from normal or sustainable functioning. As he attempts to make progress on these questions, he joins together ecology, evolutionary theory, physiology, mathematical modeling, image-analysis software, informatics, and biomedical sciences. Many theories, including some of my work, focus on optimal or average properties, but more recently, he have been working to obtain the large amounts of data necessary to characterize variation in key properties. His new findings about the diversity and variation in form and function are revealing flaws in current models, and I am working to develop new theories that incorporate realistic amounts of natural variation.
Primary Institution: UCLA
Topics of Interest: Biology - Environment/Climate Change - Evolution - Health - Physics - Scaling - Time
How SFI changes your mind: Through all the brilliantly creative and encyclopedically knowledgeable characters I talk with at lunch and tea there and now through virtual zoom links.
When and how you first got involved with SFI:
Favorite Film: The Graduate