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SPS Conferences and Events

The IEEE Signal Processing Society sponsors technical conferences, symposia and workshops dedicated to fostering networking opportunities with peers from around the world, and to exchange leading-edge, peer-reviewed scientific and technological knowledge. The Society hosts a number of worldwide events throughout the year, enabling members to exchange knowledge and network with leading scientists among many signal processing disciplines while exploring countries around the world. If you’re interested in attending an event or getting involved in the research or planning process, explore the calendar of events to learn more. Visit the Call for Papers page for conference call for paper submission deadlines.

If you’re a student, you may be interested in attending one of the Society’s Seasonal Schools in Signal Processing (S3P) Program, designed to offer opportunities for students to engage with industry professionals and academics, in hands-on tutorial sessions for experimentation with concepts and methods.

The Society's Distinguished Lecturer Program provides means for chapters to have access to individuals who are well known educators and authors in the fields of signal processing, to lecture at Chapter meetings. While many IEEE Societies have similar programs, the SPS provides financial support for the Chapters to take advantage of the service.


Choose from a List of our Events:

Michael Picheny (IBM Research)

Lecture Date: July 3, 2018
Chapter: Turkey
Chapter Chair: Murat Saraclar
Topic: Speech Recognition: What’s Left?

Rick Blum (Lehigh University, USA)

Lecture Date: July 5, 2018
Chapter: Kerala
Chapter Chair: Suresh Kumarasamy
Topic: Cyber Attacks on Internet of Things Systems

Rick Blum (Lehigh University, USA)

Lecture Date: July 7, 2018
Chapter: Madras
Chapter Chair: S. Salivahanan
Topic: Cyber Attacks on Sensor Systems for Estimation and Detection

Rama Chellappa (University of Maryland, USA)

Lecture Date: July 9, 2018
Chapter: Singapore
Chapter Chair: Hong Cao
Topic: (1) Unconstrained Face Analytics
(2) Domain Adaptation using Manifolds, Dictionaries and Deep Features


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