光子学结构设计是微纳光学器件和系统研究的核心. 许多人工设计的光子学结构, 比如超材料,
光子晶体, 等离激元纳米结构等, 已经在高速可视通信, 高灵敏度传感和高效能源收集及转换中 …

The structure design is the core of micro-nanophotonic devices and optical systems. Many
artificially designed photonic structures, such as metamaterials, photonic crystals, and …

With its tremendous success in many machine learning and pattern recognition tasks, deep
learning, as one type of data-driven models, has also led to many breakthroughs in other …

The design of plasmonic stack metamaterials (PSMs) is critical due to their promising
potentials in the fields of optical absorbers, sensors, and thermal irradiation. Compared with …

A new deep-learning approach based on dimensionality reduction techniques for the design
and knowledge discovery in nanophotonic structures will be presented. It is shown that …

Deep learning has become a vital approach to solving a big-data-driven problem. It has
found tremendous applications in computer vision and natural language processing. More …

In this talk, I will discuss how to accelerate the design of novel metamaterials by deep
learning, a subset of artificial intelligence (AI) that learns multilevel abstraction of data using …

Advances in plasmonic materials and devices have given rise to a variety of applications in
photocatalysis, microscopy, nanophotonics, and metastructures. With the advent of …

Innovative techniques play important roles in photonic structure design and complex optical
data analysis. As a branch of machine learning, deep learning can automatically reveal the …

The past decade has witnessed the advent of nanophotonics, where light–matter interaction
is shaped, almost at will, with human-made designed nanostructures. However, the design …