Skip to main content

21 Nov

SPS BSI Webinar: Investigating the Brain Mechanisms Supporting Adolescent Neurocognitive Plasticity Supporting the Formation of Adult Trajectories

Date: 21-November-2025
Time: 1:00 PM ET (New York Time)
Presenter: Dr. Beatriz Luna

Meeting information:
Meeting number: 2533 908 5841
Password: 49PacsG5qJ3 (49722745 when dialing from a phone or video system)

Join by phone:
+1-415-655-0002 US Toll
Access code: 2533 908 5841

https://gsumeetings.webex.com/gsumeetings/j.php?MTID=m4f590f97b560d8a1fa5d6ff9aff74f62

Congratulations to the 2025 SPS Scholarship recipients!

The IEEE Signal Processing Society (SPS) is proud to announce the 2025 class of SPS Scholarship recipients!

The SPS Scholarship Program recognizes students who have expressed interest and commitment to pursuing signal processing education and real-world career experiences. This year, 43 outstanding students were selected from a large field of more than 260 qualified applicants worldwide. The Scholarship Program will return in 2026, with applications opening in March – stay tuned for more information!

Congratulations to the 2025 SPS Scholarship awardees!

IEEE Signal Processing Systems Workshop (SiPS 2025) Convenes in Hong Kong

1–4 November 2025 | Hong Kong Polytechnic University

The 38th IEEE Signal Processing Systems (SiPS) Workshop brought together researchers, engineers, and industry leaders from around the world at the Hong Kong Polytechnic University for four days of discussion and discovery on the design, implementation, and application of signal processing systems.

IEEE Signal Processing Society Industry Board's Event on Low-Altitude Economy

November 16, 2025 (Sunday), 1:30 PM – 6:00 PM | Shenzhen, China
Register here: https://conference.silassz.com/

The Low-Altitude Economy (LAE) — using airspace below 1,000m — integrates manned and unmanned aerial vehicles (UAVs/eVTOLs), air traffic management, and digital infrastructure, transforming mobility, logistics, agriculture, disaster response, and nearly every aspect of daily work and life.

Rethinking Image Learning: From Real Data to Synthetic Vision

Featuring Professor Antonio Torralba, MIT
Recorded live at the IEEE International Conference on Image Processing (ICIP 2025)

Modern computer vision relies on vast image datasets—but collecting and labeling those images comes at a high cost. What if AI systems could learn from synthetically generated images—even ones that look like abstract art with no recognizable objects?