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SPS Webinar, 20 December 2021: Infinite-Dimensional Expansion for Sound Field Estimation with Application to Spatial Audio

Sound field estimation using a microphone array is a fundamental problem in acoustic signal processing, which has a wide variety of applications, such as visualization/auralization of an acoustic field, spatial audio reproduction using a loudspeaker array or headphones, and active noise cancellation in a spatial region.

Faculty Position - NYU ECE Department, NYU Wireless

NYU ECE Department is looking to hire in all areas related to wireless systems including, but not limited to (in alphabetical order): antennas, circuits, communications theory, information theory, machine learning, networking, radio propagation, signal processing, sensing, security, and applications. The candidate will be a member of NYU WIRELESS, a world leading research institute on next generation networks; we seek individuals that can engage actively with the industrial affiliates of the center.

Industry Leaders in Signal Processing and Machine Learning: Luna Dong

Dr. Luna Dong is ACM Distinguished Member for her contributions on knowledge integration and knowledge fusion, and the recipient of the VLDB Early Career Research Contribution Award for "Advancing the state of the art of knowledge fusion". The Knowledge-based Trust project she led at Google was called the “Google Truth Machine” by Washington’s Post.

Industry Leaders in Signal Processing and Machine Learning: Kush R. Varshney

Kush R. Varshney was born in Syracuse, NY in 1982. He received the B.S. degree (magna cum laude) in electrical and computer engineering with honors from Cornell University, Ithaca, NY, in 2004. He received the S.M. degree in 2006 and the Ph.D. degree in 2010, both in electrical engineering and computer science from the Massachusetts Institute of Technology (MIT), Cambridge.

Series to Highlight Women in Signal Processing: Dr. Pamela Guevara

Pamela Guevara received her B.S. with honors in Electronics Engineering from Universidad de Concepción, Chile in 2001. She then received a Master’s degree in medical Imaging and a Ph.D. in Physics, both from the Université Paris-Sud, France, both with honors, in 2007 and 2011, respectively.

SPS Webinar: 10 December 2021: Image Fusion with Convolutional Sparse Representation

As a popular signal modeling technique, sparse representation (SR) has achieved great success in image fusion during the last decade. However, due to the patch-based manner adopted in standard SR models, most existing SR-based image fusion methods suffer from two drawbacks, namely, limited ability in detail preservation and high sensitivity to mis-registration, while these two issues are of great concern in image fusion.