The practical implementation of photoelectrochemical devices for hydrogen generation is limited by their short lifetimes. Understanding the factors affecting the stability of the heterogeneous photoelectrodes is required to formulate degradation mitigation ...
Many robotics problems are formulated as optimization problems. However, most optimization solvers in robotics are locally optimal and the performance depends a lot on the initial guess. For challenging problems, the solver will often get stuck at poor loc ...
Many transportation markets are characterized by oligopolistic competition. In these markets customers, suppliers and regulators make decisions that are influenced by the preferences and the decisions of all other agents. In particular, capturing and under ...
We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...
Traffic congestion constitutes one of the most frequent, yet challenging, problems to address in the urban space. Caused by the concentration of population, whose mobility needs surpass the serving capacity of urban networks, congestion cannot be resolved ...
The invention relates to a material removing tool, such as an ice cream scoop, and method for designing the same. The material removing tool has a shape optimized to minimize the amount of work the user has to provide in order to form and remove a piece of ...
Future low-carbon societies will need to store vast amounts of electricity to stabilize electricity grids and to power electric vehicles. Vehicle-to-grid allows vehicle owners and grid operators to share the costs of electricity storage by making the batte ...
In this thesis, we advocate that Computer-Aided Engineering could benefit from a Geometric Deep Learning revolution,
similarly to the way that Deep Learning revolutionized Computer Vision.
To do so, we consider a variety of Computer-Aided Engineering pr ...
We generalize the hidden-fermion family of neural network quantum states to encompass both continuous and discrete degrees of freedom and solve the nuclear many-body Schrodinger equation in a systematically improvable fashion. We demonstrate that adding hi ...
The research community has been making significant progress in hardware implementation, numerical computing and algorithm development for optimization-based control. However, there are two key challenges that still have to be overcome for optimization-base ...
Automated switch-block exploration gains in importance as technology scaling brings more emphasis on the physical constraints, making it insufficient to rely on abstract measures of routability alone. In this work, we take an approach that significantly di ...
Simulation-based optimization models are widely applied to find optimal operating conditions of processes. Often, computational challenges arise from model complexity, making the generation of reliable design solutions difficult. We propose an algorithm fo ...
