What Motivates Us
The world is an uncertain place. To understand complex behaviors in the real world, such as the behavior of human drivers, manufacturing processes, or complex physical reactions, we need to explicity model and account for these degrees of uncertainty.
We are developing new methods in probabilistic modeling that address these challenges. Specifically, we are building statistical models that combine data-driven learning with prior engineering knowledge. Our approach allows us to accurately model prediction uncertainties originated in real-world scenarios, such as the behavior and interaction of vehicles in the real world.
The AI techniques developed as part of this work are of substantial value to Bosch business units that need to accurately and correctly model, quantify and verify the performance of systems operating in the real-world.