{"693809":{"#nid":"693809","#data":{"type":"event","title":"PhD Defense | Adaptive Subspace Tracking and Inverse Design for High-Dimensional Electromagnetics","body":[{"value":"\u003Cdiv\u003ETitle: Adaptive Subspace Tracking and Inverse Design for High-Dimensional Electromagnetics\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EDate: Thursday, November 19, 2026\u003C\/div\u003E\u003Cdiv\u003ETime: 2:00 PM EST\u003C\/div\u003E\u003Cdiv\u003ELocation:\u003C\/div\u003E\u003Cdiv\u003EIn person: CODA C1015 (Vinings)\u003C\/div\u003E\u003Cdiv\u003EVirtual: \u003Ca href=\u0022https:\/\/teams.microsoft.com\/meet\/2420063874953443?p=zH2mKpDkLDTZuzvr7Q\u0022 title=\u0022https:\/\/teams.microsoft.com\/meet\/2420063874953443?p=zH2mKpDkLDTZuzvr7Q\u0022\u003Ehttps:\/\/teams.microsoft.com\/meet\/2420063874953443?p=zH2mKpDkLDTZuzvr7Q\u003C\/a\u003E\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EAlex Saad-Falcon\u003C\/div\u003E\u003Cdiv\u003EMachine Learning PhD Student\u003C\/div\u003E\u003Cdiv\u003ESchool of Electrical and Computer Engineering\u003C\/div\u003E\u003Cdiv\u003EGeorgia Institute of Technology\u003C\/div\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003ECommittee\u003C\/div\u003E\u003Col\u003E\u003Cli data-list-item-id=\u0022ea96a93cf8e38bab85bf4d859af2e5405\u0022\u003E\u003Cdiv\u003EDr. Justin Romberg (Advisor), School of Electrical and Computer Engineering, Georgia Institute of Technology\u003C\/div\u003E\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e76d54b6cc2650ef565e5c2e781af6ce4\u0022\u003E\u003Cdiv\u003EDr. Mark Davenport, School of Electrical and Computer Engineering, Georgia Institute of Technology\u003C\/div\u003E\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e3580dd60c2c7a8e9ded8aca7430cb0c0\u0022\u003E\u003Cdiv\u003EDr. Saibal Mukhopadhyay, School of Electrical and Computer Engineering, Georgia Institute of Technology\u003C\/div\u003E\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e69ecfc04d1fce0af769ae55f0f61a18c\u0022\u003E\u003Cdiv\u003EDr. Nima Ghalichechian, School of Electrical and Computer Engineering, Georgia Institute of Technology\u003C\/div\u003E\u003C\/li\u003E\u003Cli data-list-item-id=\u0022e977b81935816e109383d0effd9eb335b\u0022\u003E\u003Cdiv\u003EDr. Ryan Westafer, Georgia Tech Research Institute\u003C\/div\u003E\u003C\/li\u003E\u003C\/ol\u003E\u003Cdiv\u003E\u0026nbsp;\u003C\/div\u003E\u003Cdiv\u003EAbstract\u003C\/div\u003E\u003Cdiv\u003EThis dissertation develops theory, algorithms, and systems for high-dimensional optimization problems in electromagnetics. The first part studies subspace tracking and principal component analysis under hardware constraints such as limited computation, scarce memory, or acquisition restricted to a few linear measurements per sample. For Gaussian data in dimension d, it shows that an Oja-type algorithm using 2k adaptive linear measurements per sample estimates the top-k principal subspace at the minimax error rate of a two-level spiked model, up to a constant factor, when the sample size is known in advance, while measurement designs fixed in advance have a lower bound larger by a factor of order d\/k at large sample sizes when the (k+1)-th eigenvalue is comparable to the k-th. It also develops regularized least squares algorithms on the Grassmann manifold for tracking time-varying subspaces. On the systems side, it describes AdaAFE-CIM, which uses subspace tracking for adaptive data compression in array processing hardware and reduces baseband power by 95.4% relative to full digitization in power-model simulations, together with an open-source end-to-end simulator for array processing under realistic hardware and channel effects. Finally, it presents inverse design methods for electromagnetic structures: a periodic level set function for gradient-free topology optimization, validated by fabrication and measurement for metasurfaces, and a neural adjoint method for reconfigurable antennas with exponentially large switch configuration spaces.\u003C\/div\u003E","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003EAdaptive Subspace Tracking and Inverse Design for High-Dimensional Electromagnetics\u003C\/p\u003E","format":"limited_html"}],"field_summary_sentence":[{"value":"Alex Saad-Falcon - Machine Learning PhD Student - School of Electrical and Computer Engineering Georgia Institute of Technology"}],"uid":"36518","created_gmt":"2026-11-05 19:13:35","changed_gmt":"2026-11-05 19:14:18","author":"shatcher8","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2026-11-19T14:00:00-05:00","event_time_end":"2026-11-19T16:00:00-05:00","event_time_end_last":"2026-11-19T16:00:00-05:00","gmt_time_start":"2026-11-19 19:00:00","gmt_time_end":"2026-11-19 21:00:00","gmt_time_end_last":"2026-11-19 21:00:00","rrule":null,"timezone":"America\/New_York"},"location":"CODA C1015 (Vinings)","extras":[],"related_links":[{"url":"https:\/\/teams.microsoft.com\/meet\/2420063874953443?p=zH2mKpDkLDTZuzvr7Q","title":""}],"groups":[{"id":"576481","name":"ML@GT"}],"categories":[],"keywords":[],"core_research_areas":[],"news_room_topics":[],"event_categories":[],"invited_audience":[],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}