The 2022 International Conference on Acoustics, Speech, & Signal Processing (ICASSP) invites proposals for its Signal Processing Grand Challenges (SPGC) program. ICASSP is the IEEE Signal Processing Society’s flagship conference targeting signal processing and its applications.

Adaptive (i.e., data-driven) methods have become very popular these last decades. Among the existing techniques, the empirical mode decomposition has proven to be very efficient in extracting accurate time-frequency information from non-stationary signals.

Dr. Henrique Malvar is a Fellow of the IEEE and a Member of the US National Academy of Engineering. He is a Distinguished Engineer at Microsoft Research, having previously served as Managing Director of the largest Microsoft Research Lab in Redmond, WA. Prior to joining Microsoft in 1997, he was Vice President of Research and Advanced Technology at PictureTel Corporation. Prior to that he was a professor at University of Brasilia. 

I received my Ph.D. degree from University of Southern California (USC), Los Angeles, CA. Currently I am an Associate Professor and Associate Head of Information Systems Technology and Design (ISTD), Singapore University of Technology and Design (SUTD). I have been an active researcher in the field of Image Processing and Computer Vision. My research has resulted in 14 U.S. patents granted with several pending. Two of my inventions have been licensed to companies. 

SP Arun, Associate Professor, IISc Bangalore, India, received his B.Tech from IIT Bombay, and MS & PhD from Johns Hopkins University, all in Electrical Engineering. He completed his postdoctoral research at Carnegie Mellon University and joined the Centre for Neuroscience at IISc where he is currently an Associate Professor and also an Associate Faculty of the Electrical Communication Engineering department.

The Signal Processing Society (SPS) has 12 Technical Committees that support a broad selection of signal processing-related activities defined by the scope of the Society.

The DSLW team is inviting you to submit regular papers to the 2022 IEEE Data Science & Learning Workshop (DSLW 2022), a workshop organized by the IEEE Signal Processing Society (supported by the SPS Data Science Initiative). The workshop aims to bring together researchers in academia and industry to share the most recent and exciting advances in data science, learning theory and applications.