María Snæbjörnsdóttir

María Snæbjörnsdóttir completed her doctorate at the Faculty of Physical Sciences of the University of Iceland, where her dissertation developed Hamilton-Jacobi-Bellman methods for optimal climate policy under stochastic climate dynamics. The work formulated the carbon emissions reduction problem as a stochastic optimal control problem in which the planner chooses a trajectory of abatement effort facing uncertainty in both the climate sensitivity parameter and in the economic damages from temperature increase, deriving the associated HJB equation and establishing the regularity and monotonicity properties of its value function under natural conditions on the damage and cost functionals. The dissertation extended the framework to a multi-sector model incorporating both a carbon budget constraint and a stochastic renewable energy cost process, characterising the optimal switching boundary between fossil fuel and renewable capacity investment as a free boundary problem whose solution determines the optimal energy transition pathway.

Following her doctorate, Snæbjörnsdóttir worked on stochastic optimal control models for geothermal resource management — a domain of particular relevance in Iceland, where geothermal energy constitutes a dominant share of the primary energy supply and the economic value of the resource is sensitive to uncertain geological and market conditions. Her work developed HJB frameworks for optimal geothermal extraction under price uncertainty and capacity degradation, establishing optimal depletion policies and characterising the conditions under which conservation dominates immediate extraction as a function of the drift and diffusion parameters of the price process. She also examined the integration of renewable investment decisions under uncertain carbon prices into a unified stochastic control framework for sovereign energy policy design.

At IADU, Snæbjörnsdóttir contributes optimal control methods to the Institute's work on environmental and energy policy. Her research focuses on the mathematical foundations of stochastic climate policy optimisation — carbon pricing under model uncertainty, optimal renewable energy transition under stochastic technology costs, and the design of national energy portfolios that balance geothermal, hydro, and import capacity under uncertain demand and price dynamics. She supports the Institute's engagement with sovereign clients whose policy mandates include both fiscal and environmental objectives.