Michael Dioha is a Postdoctoral Fellow in the Carnegie Institution for Science Department of Global Ecology, located at the Stanford University campus. His main research areas include energy system analysis & modelling and socioeconomic development for a sustainable energy transition. Michael develops integrated energy system models to examine the techno-economic implications of alternative energy strategies, and how they might be shaped for a coherent and sustainable energy future.
Kristen is an administrative professional with over 10 years of comprehensive experience in human resources and executive support. She holds a Master's degree in Psychology from Santa Clara University and is passionate about supporting people with their visions and goals. Kristen is thrilled and honored to be joining the Carnegie Institution for Science.
With the help of mathematical models and statistics I try to tackle ecological questions ranging from molecular up to global scales. During my PhD, I developed statistical techniques and software to improve the performance of ultrahigh-resolution mass spectrometry and derived new ways to link the composition of dissolved organic matter to biotic and abiotic factors.
I am a scientist studying low carbon energy transitions. How do we create a low carbon energy system? What could that system look like? What technological breakthroughs are necessary? These are some of the questions which motivate my research.
My current work focuses on studying the interannual variability of renewable energy resources and potential consequences for a highly-renewable grid. I also model the conversion of electric power to liquid fuels or hydrogen to study the benefits these technologies can bring to the grid including increased flexibility.
Wu Sun is a Postdoctoral Research Associate in the Michalak Lab at the Department of Global Ecology, Carnegie Institution for Science. His research aims to understand the variability of terrestrial carbon fluxes across scales by leveraging leaf-scale, atmospheric, and space-borne observations, terrestrial biosphere models, and atmospheric inverse modeling. His current research uses atmospheric observations and remotely sensed photosynthetic proxies to constrain space-time patterns of North American carbon fluxes from divergent model estimates.