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ways in which such physical learning is realized, and design new types of learning machines capable of solving complex engineering problems on their own. Some examples include neuromorphic computers
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structures for application in high-precision semiconductor metrology, guided by design principles from the field of optical metasurfaces. The tremendous success of the semiconductor industry is enabled by
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hand to perfom metrology on structures in wafers that themselves emit at very short wavelengths when illuminated by infrared light. How do you design optical metasurfaces that efficiently radiate UV
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the following questions: Suppose optical signals are encoded in space like an image, in wavelength and polarization. How do you then design metasurfaces to perform common image processing steps, nowadays done
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focused on the fundamental aspects of understanding and characterizing how chiral amplification effects can occur during crystallization, or on the design and development of systems that can undergo these
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that are relevant for semiconductor manufacturing and uses tomographic techniques in combination with inverse design and machine learning tools. The aim is to determine the possibilities and limitations of the use