SOLID Lab focuses on the design and implementation of large-scale local and global optimization algorithms to solve problems that arise in diverse decision-making paradigms such as machine learning, data analysis, stochastic optimization,and optimal control. Our algorithms combine mathematical techniques and emerging high-performance computing hardware (e.g., multi-core CPUs, GPUs, and computing clusters) to achieve computational scalability. The goal is to make these developments accessible to academic and industrial users by implementing algorithms on easy-to-use and extensible software libraries.

Furthermore, We have applied the algorithms and tools to help collaborators address engineering and scientific questions that arise in diverse application domainsincluding conflict resolution in energy system design, robust control of crystallization systems, predictive control of wind turbines, power management in large networks, estimation of microbial growth models, and image classification for contaminant detection.