Designing Photodetectors with Machine Learning

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dc.contributor.authorSimsek, Ergun
dc.contributor.authorAnjum, Ishraq Md
dc.contributor.authorCarruthers, Thomas F.
dc.contributor.authorMenyuk, Curtis
dc.date.accessioned2024-03-05T22:00:30Z
dc.date.available2024-03-05T22:00:30Z
dc.date.issued2022-07
dc.descriptionNovel Optical Materials and Applications 2022, Maastricht, Limburg Netherlands, 24–28 July 2022
dc.description.abstractModern optimization techniques are used to design high-performance photodetectors. All the designs created during these optimization studies are then used to train a physics-inspired, two-stage neural network to obtain even better-performing devices.
dc.description.urihttps://opg.optica.org/abstract.cfm?uri=NOMA-2022-NoW5C.2
dc.format.extent2 pages
dc.genreconference papers and proceedings
dc.identifierdoi:10.13016/m2bnut-nkvx
dc.identifier.citationE. Simsek, I. M. Anjum, T. F. Carruthers, and C. R. Menyuk, "Designing Photodetectors with Machine Learning," in Optica Advanced Photonics Congress 2022, Technical Digest Series (Optica Publishing Group, 2022), paper NoW5C.2. https://doi.org/10.1364/NOMA.2022.NoW5C.2
dc.identifier.urihttps://doi.org/10.1364/NOMA.2022.NoW5C.2
dc.identifier.urihttp://hdl.handle.net/11603/31810
dc.publisherOptica
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Computer Science and Electrical Engineering Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Student Collection
dc.relation.ispartofUMBC Data Science
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.titleDesigning Photodetectors with Machine Learning
dc.typeText
dcterms.creatorhttps://orcid.org/0000-0001-9075-7071
dcterms.creatorhttps://orcid.org/0009-0000-3447-6099
dcterms.creatorhttps://orcid.org/0000-0002-5002-1657
dcterms.creatorhttps://orcid.org/0000-0003-0269-8433

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