This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …

Advancements in digital automation for smart grids have led to the installation of
measurement devices like phasor measurement units (PMUs), micro-PMUs (-PMUs), and …

Due to their high energy intensity, buildings play a major role in the current worldwide
energy transition. Building models are ubiquitous since they are needed at each stage of the …

Integrating physics models within machine learning models holds considerable promise
toward learning robust models with improved interpretability and abilities to extrapolate. In …

Recent developments in data science and machine learning have inspired a new wave of
research into data-driven modeling for mathematical optimization of process applications …

In this paper, we work towards a neural surrogate to model wireless electro-magnetic
propagation effects in indoor environments. Such neural surrogates provide a fast …

Abstract Heating Ventilation and Air Conditioning (HVAC) are energy-intensive systems that
greatly contribute to peak demand, which can cause stability and reliability issues in the grid …

Accurate models of robot dynamics are critical for safe and stable control and generalization
to novel operational conditions. Hand-designed models, however, may be insufficiently …

Data-driven approaches are promising to address the modeling issues of modern power
electronics-based power systems, due to the black-box feature. Frequency-domain analysis …

Deep learning models, though having achieved great success in many different fields over
the past years, are usually data-hungry, fail to perform well on unseen samples, and lack …