Numerical computation is indispensable in power system analysis, operation and planning. Examples such as load flow analysis, optimal power flow, unit commitment and generation expansion planning are routinely performed by utilities worldwide. Changes in climate, industrial demand and social landscape call for greater reliability, resilience and efficiency in power systems while minimizing environmental impact. New technologies such as renewables, power electronics and automation are integrated into power systems to cope with the

Task oriented communications, which extracts only task-relevant information for transmission, is envisioned to be a key enabler to alleviate the communication burden in next-generation wireless networks. Thanks to the recent advances in AI, deep neural networks (DNNs) has been introduced for task-relevant information extraction. Nonetheless, most existing work either overly simplifies the wireless channel

Developing effective and computationally efficient statistical models to accommodate nonstationary/nonseparable processes containing both long-range and short-scale variations becomes a challenging task, especially for large-scale datasets with various corruption/missing structures. In this talk, we will introduce Bayesian Complementary Kernelized Learning (BCKL) to achieve scalable probabilistic modeling for multidimensional spatiotemporal data.

Additive manufacturing (AM) is a digital manufacturing process that can directly convert a computer-aided design model into a physical object in a layer-by-layer manner. Due to the additive and discrete nature of the digital manufacturing process, AM needs to find a trade-off between process resolution and production efficiency. Traditional AM processes balance the resolution and efficiency by tuning the processes either in the

With continuous advancements in cyber transportation technologies, connected and automated vehicle systems (CAVs) are poised to revolutionize the way human drivers navigate roads. Understanding the impact of CAVs on driver cognition and performance is paramount for addressing driver needs and enhancing transportation safety.

In metazoans, both transcription initiation and the escape of RNA polymerase (RNAP) from promoter-proximal pausing are key rate-limiting steps in gene expression.