I-DeepLearn aims to increase diversity in computer science and related field by inviting students from grades 10-12 to experience machine learning (Artificial Intelligence) and deep learning (AI processing) and their applications, specifically in the healthcare domain. In this one-week online workshop, students will learn about essential concepts in machine learning and deep learning through a dynamic mix of hands-on programming projects and interactive discussions.

Prof. Mihaela van der Schaar is the John Humphrey Plummer Professor of Machine Learning, Artificial Intelligence and Medicine at the University of Cambridge, a Fellow at The Alan Turing Institute in London, and a Chancellor’s Professor at UCLA.

Mónica F. Bugallo received her Ph.D. in computer science and engineering from University of A Coruña, Spain. She is a Professor of Electrical and Computer Engineering and the Vice Provost for Faculty Affairs, and Diversity, Equity and Inclusion at Stony Brook University, NY, USA. Bugallo is the current Chair of the IEEE SPS Signal Processing Theory and Methods Technical Committee, Senior Associate Editor of the IEEE Signal Processing Letters and Associate Editor of the IEEE Transactions on Signal Processing. 

Xuedong Huang is a Microsoft Technical Fellow and Azure AI Chief Technology Officer. He is responsible for Microsoft’s Azure AI engineering and research to bring the dream of making machines see, hear and understand human beings a reality.

Dr. Supavadee Aramvith received her B.S. (first class honors) degree in Computer Science from Mahidol University, Bangkok, Thailand, in 1993. She received her M.S. and Ph.D. degrees in Electrical Engineering from the University of Washington, Seattle, USA, in 1996 and 2001, respectively. 

Facial expressions are configurations of different muscle movements in the face. The local characters of muscle movements play an important role in distinguishing facial expressions by machines. In this webinar, the presenter will explore the local characters local characters of muscle movements by introducing the attention mechanism into two frameworks.

Global navigation satellite systems (GNSS) have been the main technology used in aerial and ground vehicle navigation systems. As vehicles approach full autonomy, the requirements on the accuracy, reliability, and availability of their navigation systems become very stringent. Due to the limitations of GNSS, namely severe attenuation in deep urban canyons and susceptibility to interference, jamming, and spoofing, alternative sensors and signals are sought. 

The IEEE Signal Processing Society (SPS) is honored to announce the elevation of 108 of its members to the grade of IEEE Senior Member. These members have demonstrated outstanding professional performance, exhibited professional maturity through long-term experience, and established themselves as leaders in their respective IEEE-designated fields of interest. 

Every person spends around 1/3 of their life in bed. For an infant or a young toddler this percentage can be much higher, and for bed-bound patients it can go up to 100% of their time. In-bed pose estimation is a critical step in many human behavioral monitoring systems, which are focused on prevention, prediction, and management of at-rest or sleep-related conditions in both adults and children.

The Society offers funding under the Member Driven Initiatives program for events that encourage involvement by SPS membership, including local chapters, universities, industry members as well as individual members. Programs under the Member Driven Initiatives include the launched Forums and Regional Meetings, in addition to the existing Chapter Driven Initiatives.