BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN X-WR-CALNAME:36th Annual IEEE Workshop on Machine Learning for Signal Proce ssing (MLSP 2026) X-WR-TIMEZONE:Eastern Time (US & Canada) BEGIN:VEVENT DTSTAMP:20260911T230841Z UID:tag:localist.com\,2008:EventInstance_53013849602015 DTSTART;VALUE=DATE:20260928 DESCRIPTION:The 36th IEEE Workshop on Machine Learning for Signal Processin g (MLSP 2026) will bring together researchers\, engineers\, and industry p ractitioners from around the world for four days of technical exchange at the intersection of machine learning and signal processing. The workshop w ill take place in Atlanta\, Georgia\, from September 28 through October 1\ , 2026\, with Centennial Hall on the downtown campus of Georgia State Univ ersity serving as the conference venue.\n\nMLSP has long been one of the I EEE Signal Processing Society’s key forums for emerging methods and appl ications in learning-driven signal processing. MLSP 2026 will continue tha t tradition with a program designed to highlight both foundational advance s and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landsca pe of the field\, including: Foundation and Generative Models for Signals\ ; Temporal and Sequential Signal Learning\; Agentic and Multimodal Learnin g\; Machine Learning for Neuroimaging\, Neuroscience\, and Biomedical Sign als\; and Responsible\, Causal\, and Federated Signal Intelligence.\n\nThe se themes are complemented by a broad call for contributions spanning deep learning\, Bayesian and probabilistic inference\, graph representation le arning\, federated and distributed learning\, privacy and fairness\, multi modal machine learning\, large language models\, learning from biosignals\ , and applications in areas such as healthcare\, neuroscience\, wireless c ommunications\, disaster management\, and financial engineering. Together\ , the program reflects both the rapid methodological advances in the field and their increasing importance across real-world systems and industry ap plications.\n\nThe workshop will also include tutorials and special sessio ns intended to expose attendees to fast-moving topics and cross-disciplina ry opportunities. The tutorial program is designed to be valuable to both industry and academic participants\, with formats ranging from 1.5-hour sh ort tutorials to 3.5-hour in-depth sessions. Special sessions are being so licited on emerging topics expected to have substantial near-term impact\, providing a platform for focused discussion and community building.\n\nML SP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun\, sup ported by an international organizing committee overseeing the technical p rogram\, tutorials\, keynotes\, publications\, finance\, and publicity. Th e workshop will feature keynote talks from leaders in the field\, includin g confirmed keynote speaker Tülay Adali\, known for her contributions to statistical signal processing and machine learning. GEO:33.755867;-84.383556 LOCATION:Centennial Hall SUMMARY:36th Annual IEEE Workshop on Machine Learning for Signal Processing (MLSP 2026) URL;VALUE=URI:https://calendar.gsu.edu/event/36th-annual-ieee-workshop-on-m achine-learning-for-signal-processing-ieee-mlsp-2026 CATEGORIES:Conferences & Workshops END:VEVENT BEGIN:VEVENT DTSTAMP:20260911T230841Z UID:tag:localist.com\,2008:EventInstance_53013849603040 DTSTART;VALUE=DATE:20260929 DESCRIPTION:The 36th IEEE Workshop on Machine Learning for Signal Processin g (MLSP 2026) will bring together researchers\, engineers\, and industry p ractitioners from around the world for four days of technical exchange at the intersection of machine learning and signal processing. The workshop w ill take place in Atlanta\, Georgia\, from September 28 through October 1\ , 2026\, with Centennial Hall on the downtown campus of Georgia State Univ ersity serving as the conference venue.\n\nMLSP has long been one of the I EEE Signal Processing Society’s key forums for emerging methods and appl ications in learning-driven signal processing. MLSP 2026 will continue tha t tradition with a program designed to highlight both foundational advance s and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landsca pe of the field\, including: Foundation and Generative Models for Signals\ ; Temporal and Sequential Signal Learning\; Agentic and Multimodal Learnin g\; Machine Learning for Neuroimaging\, Neuroscience\, and Biomedical Sign als\; and Responsible\, Causal\, and Federated Signal Intelligence.\n\nThe se themes are complemented by a broad call for contributions spanning deep learning\, Bayesian and probabilistic inference\, graph representation le arning\, federated and distributed learning\, privacy and fairness\, multi modal machine learning\, large language models\, learning from biosignals\ , and applications in areas such as healthcare\, neuroscience\, wireless c ommunications\, disaster management\, and financial engineering. Together\ , the program reflects both the rapid methodological advances in the field and their increasing importance across real-world systems and industry ap plications.\n\nThe workshop will also include tutorials and special sessio ns intended to expose attendees to fast-moving topics and cross-disciplina ry opportunities. The tutorial program is designed to be valuable to both industry and academic participants\, with formats ranging from 1.5-hour sh ort tutorials to 3.5-hour in-depth sessions. Special sessions are being so licited on emerging topics expected to have substantial near-term impact\, providing a platform for focused discussion and community building.\n\nML SP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun\, sup ported by an international organizing committee overseeing the technical p rogram\, tutorials\, keynotes\, publications\, finance\, and publicity. Th e workshop will feature keynote talks from leaders in the field\, includin g confirmed keynote speaker Tülay Adali\, known for her contributions to statistical signal processing and machine learning. GEO:33.755867;-84.383556 LOCATION:Centennial Hall SUMMARY:36th Annual IEEE Workshop on Machine Learning for Signal Processing (MLSP 2026) URL;VALUE=URI:https://calendar.gsu.edu/event/36th-annual-ieee-workshop-on-m achine-learning-for-signal-processing-ieee-mlsp-2026 CATEGORIES:Conferences & Workshops END:VEVENT BEGIN:VEVENT DTSTAMP:20260911T230841Z UID:tag:localist.com\,2008:EventInstance_53013849605089 DTSTART;VALUE=DATE:20260930 DESCRIPTION:The 36th IEEE Workshop on Machine Learning for Signal Processin g (MLSP 2026) will bring together researchers\, engineers\, and industry p ractitioners from around the world for four days of technical exchange at the intersection of machine learning and signal processing. The workshop w ill take place in Atlanta\, Georgia\, from September 28 through October 1\ , 2026\, with Centennial Hall on the downtown campus of Georgia State Univ ersity serving as the conference venue.\n\nMLSP has long been one of the I EEE Signal Processing Society’s key forums for emerging methods and appl ications in learning-driven signal processing. MLSP 2026 will continue tha t tradition with a program designed to highlight both foundational advance s and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landsca pe of the field\, including: Foundation and Generative Models for Signals\ ; Temporal and Sequential Signal Learning\; Agentic and Multimodal Learnin g\; Machine Learning for Neuroimaging\, Neuroscience\, and Biomedical Sign als\; and Responsible\, Causal\, and Federated Signal Intelligence.\n\nThe se themes are complemented by a broad call for contributions spanning deep learning\, Bayesian and probabilistic inference\, graph representation le arning\, federated and distributed learning\, privacy and fairness\, multi modal machine learning\, large language models\, learning from biosignals\ , and applications in areas such as healthcare\, neuroscience\, wireless c ommunications\, disaster management\, and financial engineering. Together\ , the program reflects both the rapid methodological advances in the field and their increasing importance across real-world systems and industry ap plications.\n\nThe workshop will also include tutorials and special sessio ns intended to expose attendees to fast-moving topics and cross-disciplina ry opportunities. The tutorial program is designed to be valuable to both industry and academic participants\, with formats ranging from 1.5-hour sh ort tutorials to 3.5-hour in-depth sessions. Special sessions are being so licited on emerging topics expected to have substantial near-term impact\, providing a platform for focused discussion and community building.\n\nML SP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun\, sup ported by an international organizing committee overseeing the technical p rogram\, tutorials\, keynotes\, publications\, finance\, and publicity. Th e workshop will feature keynote talks from leaders in the field\, includin g confirmed keynote speaker Tülay Adali\, known for her contributions to statistical signal processing and machine learning. GEO:33.755867;-84.383556 LOCATION:Centennial Hall SUMMARY:36th Annual IEEE Workshop on Machine Learning for Signal Processing (MLSP 2026) URL;VALUE=URI:https://calendar.gsu.edu/event/36th-annual-ieee-workshop-on-m achine-learning-for-signal-processing-ieee-mlsp-2026 CATEGORIES:Conferences & Workshops END:VEVENT BEGIN:VEVENT DTSTAMP:20260911T230841Z UID:tag:localist.com\,2008:EventInstance_53013849606114 DTSTART;VALUE=DATE:20261001 DESCRIPTION:The 36th IEEE Workshop on Machine Learning for Signal Processin g (MLSP 2026) will bring together researchers\, engineers\, and industry p ractitioners from around the world for four days of technical exchange at the intersection of machine learning and signal processing. The workshop w ill take place in Atlanta\, Georgia\, from September 28 through October 1\ , 2026\, with Centennial Hall on the downtown campus of Georgia State Univ ersity serving as the conference venue.\n\nMLSP has long been one of the I EEE Signal Processing Society’s key forums for emerging methods and appl ications in learning-driven signal processing. MLSP 2026 will continue tha t tradition with a program designed to highlight both foundational advance s and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landsca pe of the field\, including: Foundation and Generative Models for Signals\ ; Temporal and Sequential Signal Learning\; Agentic and Multimodal Learnin g\; Machine Learning for Neuroimaging\, Neuroscience\, and Biomedical Sign als\; and Responsible\, Causal\, and Federated Signal Intelligence.\n\nThe se themes are complemented by a broad call for contributions spanning deep learning\, Bayesian and probabilistic inference\, graph representation le arning\, federated and distributed learning\, privacy and fairness\, multi modal machine learning\, large language models\, learning from biosignals\ , and applications in areas such as healthcare\, neuroscience\, wireless c ommunications\, disaster management\, and financial engineering. Together\ , the program reflects both the rapid methodological advances in the field and their increasing importance across real-world systems and industry ap plications.\n\nThe workshop will also include tutorials and special sessio ns intended to expose attendees to fast-moving topics and cross-disciplina ry opportunities. The tutorial program is designed to be valuable to both industry and academic participants\, with formats ranging from 1.5-hour sh ort tutorials to 3.5-hour in-depth sessions. Special sessions are being so licited on emerging topics expected to have substantial near-term impact\, providing a platform for focused discussion and community building.\n\nML SP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun\, sup ported by an international organizing committee overseeing the technical p rogram\, tutorials\, keynotes\, publications\, finance\, and publicity. Th e workshop will feature keynote talks from leaders in the field\, includin g confirmed keynote speaker Tülay Adali\, known for her contributions to statistical signal processing and machine learning. GEO:33.755867;-84.383556 LOCATION:Centennial Hall SUMMARY:36th Annual IEEE Workshop on Machine Learning for Signal Processing (MLSP 2026) URL;VALUE=URI:https://calendar.gsu.edu/event/36th-annual-ieee-workshop-on-m achine-learning-for-signal-processing-ieee-mlsp-2026 CATEGORIES:Conferences & Workshops END:VEVENT END:VCALENDAR