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20212025
most citedGeneral Inverse Design of Thin-Film Metamaterials With Convolutional Neural Networks

67 citations · 157 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

PATCH: a deep learning method to assess heterogeneity of artistic practice in historical paintings

Andrew Van Horn, Lauryn Smith, Mahamad Mahmoud +10

The history of art has seen significant shifts in the manner in which artworks are created, making understanding of creative processes a central question in technical art history.…

physics.optics2022★ 60 cited

Fano Resonant Optical coatings platform for Full Gamut and High Purity Structural Colors

Mohamed ElKabbash, Nathaniel Hoffman, Andrew R Lininger +5

Structural coloring is a photostable and environmentally friendly coloring approach that harnesses optical interference and nanophotonic resonances to obtain colors with a range of…

physics.optics2022

Manipulating Random Lasing Correlations in Doped Liquid Crystals

Yiyang Zhi, Andrew Lininger, Giuseppe Strangi

Random lasers are highly configurable light sources that are promising for imaging and photonic integration. In this study, random lasing action was generated by optically pumping…

physics.optics2022★ 30 cited

All-Optical tunability of metalenses infiltrated with liquid crystals

Giovanna Palermo, Andrew Lininger, Alexa Guglielmelli +8

Metasurfaces have been extensively engineered to produce a wide range of optical phenomena, allowing unprecedented control over the propagation of light. However, they are generall…

physics.comp-ph2021★ 67 cited

General Inverse Design of Thin-Film Metamaterials With Convolutional Neural Networks

Andrew Lininger, Michael Hinczewski, Giuseppe Strangi

The design of metamaterials which support unique optical responses is the basis for most thin-film nanophotonics applications. In practice this inverse design problem can be diffic…