Participate in the SCD conference to:

• Share your work with the university community.

• Get feedback from experts in different disciplines.

• Build new connections.

• Learn new methods and techniques you can apply in your research.

Lunch will be provided. View the conference agenda here.

View on site | Email this event

Participate in the SCD conference to:

• Share your work with the university community.

• Get feedback from experts in different disciplines.

• Build new connections.

• Learn new methods and techniques you can apply in your research.

Lunch will be provided. View the conference agenda here.

View on site | Email this event

MLSP has long been one of the IEEE Signal Processing Society’s key forums for emerging methods and applications in learning-driven signal processing. MLSP 2026 will continue that tradition with a program designed to highlight both foundational advances and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landscape of the field, including: Foundation and Generative Models for Signals; Temporal and Sequential Signal Learning; Agentic and Multimodal Learning; Machine Learning for Neuroimaging, Neuroscience, and Biomedical Signals; and Responsible, Causal, and Federated Signal Intelligence.

These themes are complemented by a broad call for contributions spanning deep learning, Bayesian and probabilistic inference, graph representation learning, federated and distributed learning, privacy and fairness, multimodal machine learning, large language models, learning from biosignals, and applications in areas such as healthcare, neuroscience, wireless communications, 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 applications.

The workshop will also include tutorials and special sessions intended to expose attendees to fast-moving topics and cross-disciplinary opportunities. The tutorial program is designed to be valuable to both industry and academic participants, with formats ranging from 1.5-hour short tutorials to 3.5-hour in-depth sessions. Special sessions are being solicited on emerging topics expected to have substantial near-term impact, providing a platform for focused discussion and community building.

MLSP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun, supported by an international organizing committee overseeing the technical program, tutorials, keynotes, publications, finance, and publicity. The workshop will feature keynote talks from leaders in the field, including confirmed keynote speaker Tülay Adali, known for her contributions to statistical signal processing and machine learning.

View on site | Email this event

MLSP has long been one of the IEEE Signal Processing Society’s key forums for emerging methods and applications in learning-driven signal processing. MLSP 2026 will continue that tradition with a program designed to highlight both foundational advances and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landscape of the field, including: Foundation and Generative Models for Signals; Temporal and Sequential Signal Learning; Agentic and Multimodal Learning; Machine Learning for Neuroimaging, Neuroscience, and Biomedical Signals; and Responsible, Causal, and Federated Signal Intelligence.

These themes are complemented by a broad call for contributions spanning deep learning, Bayesian and probabilistic inference, graph representation learning, federated and distributed learning, privacy and fairness, multimodal machine learning, large language models, learning from biosignals, and applications in areas such as healthcare, neuroscience, wireless communications, 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 applications.

The workshop will also include tutorials and special sessions intended to expose attendees to fast-moving topics and cross-disciplinary opportunities. The tutorial program is designed to be valuable to both industry and academic participants, with formats ranging from 1.5-hour short tutorials to 3.5-hour in-depth sessions. Special sessions are being solicited on emerging topics expected to have substantial near-term impact, providing a platform for focused discussion and community building.

MLSP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun, supported by an international organizing committee overseeing the technical program, tutorials, keynotes, publications, finance, and publicity. The workshop will feature keynote talks from leaders in the field, including confirmed keynote speaker Tülay Adali, known for her contributions to statistical signal processing and machine learning.

View on site | Email this event

MLSP has long been one of the IEEE Signal Processing Society’s key forums for emerging methods and applications in learning-driven signal processing. MLSP 2026 will continue that tradition with a program designed to highlight both foundational advances and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landscape of the field, including: Foundation and Generative Models for Signals; Temporal and Sequential Signal Learning; Agentic and Multimodal Learning; Machine Learning for Neuroimaging, Neuroscience, and Biomedical Signals; and Responsible, Causal, and Federated Signal Intelligence.

These themes are complemented by a broad call for contributions spanning deep learning, Bayesian and probabilistic inference, graph representation learning, federated and distributed learning, privacy and fairness, multimodal machine learning, large language models, learning from biosignals, and applications in areas such as healthcare, neuroscience, wireless communications, 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 applications.

The workshop will also include tutorials and special sessions intended to expose attendees to fast-moving topics and cross-disciplinary opportunities. The tutorial program is designed to be valuable to both industry and academic participants, with formats ranging from 1.5-hour short tutorials to 3.5-hour in-depth sessions. Special sessions are being solicited on emerging topics expected to have substantial near-term impact, providing a platform for focused discussion and community building.

MLSP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun, supported by an international organizing committee overseeing the technical program, tutorials, keynotes, publications, finance, and publicity. The workshop will feature keynote talks from leaders in the field, including confirmed keynote speaker Tülay Adali, known for her contributions to statistical signal processing and machine learning.

View on site | Email this event

MLSP has long been one of the IEEE Signal Processing Society’s key forums for emerging methods and applications in learning-driven signal processing. MLSP 2026 will continue that tradition with a program designed to highlight both foundational advances and practical impact across academia and industry. The technical program is organized around several core themes that reflect the evolving landscape of the field, including: Foundation and Generative Models for Signals; Temporal and Sequential Signal Learning; Agentic and Multimodal Learning; Machine Learning for Neuroimaging, Neuroscience, and Biomedical Signals; and Responsible, Causal, and Federated Signal Intelligence.

These themes are complemented by a broad call for contributions spanning deep learning, Bayesian and probabilistic inference, graph representation learning, federated and distributed learning, privacy and fairness, multimodal machine learning, large language models, learning from biosignals, and applications in areas such as healthcare, neuroscience, wireless communications, 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 applications.

The workshop will also include tutorials and special sessions intended to expose attendees to fast-moving topics and cross-disciplinary opportunities. The tutorial program is designed to be valuable to both industry and academic participants, with formats ranging from 1.5-hour short tutorials to 3.5-hour in-depth sessions. Special sessions are being solicited on emerging topics expected to have substantial near-term impact, providing a platform for focused discussion and community building.

MLSP 2026 is led by Conference Co-Chairs Sergey Plis and Vince Calhoun, supported by an international organizing committee overseeing the technical program, tutorials, keynotes, publications, finance, and publicity. The workshop will feature keynote talks from leaders in the field, including confirmed keynote speaker Tülay Adali, known for her contributions to statistical signal processing and machine learning.

View on site | Email this event

View on site | Email this event

View on site | Email this event

View on site | Email this event