Embedded System Design Methodologies for Signal Processing and Machine Learning

Shuvra S. Bhattacharyya, Professeur à l'Université du Maryland et éditeur du Handbook of Signal Processing Systems, donnera les 18 et 19 mars 2020 à l'INSA Rennes, en introduction de sa Chaire Internationale de Recherche INSA/INRIA/IETR, un séminaire exceptionnel sur la conception des systèmes embarqués de traitement du signal et d'apprentissage machine. Les détails sont ci-dessous, venez nombreux!

Seminar on "Embedded System Design Methodologies for Signal Processing and Machine Learning"

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Shuvra S. Bhattacharyya

University of Maryland

Chaire Internationale de Recherche INSA/INRIA/IETR, Rennes, France

Email: sbhattacinsa-rennes [*] fr (sbhattac[at]insa-rennes[dot]fr)

March 18–19, 2020, Amphi Bonnin, INSA Rennes, France Free access, upon registration

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Advances in sensor technology, signal and information processing algorithms, and embedded computing architectures provide great potential for innovation in novel applications and services. Representative areas that are impacted by this potential are biomedical devices, environmental monitoring systems, industrial Internet of things, and smart homes. Critical to supporting advances in such areas are effective methodologies for developing complex signal processing and machine learning (SPML) implementations on embedded platforms. In this seminar, we will cover concepts and methods that are important to this class of methodologies.

The seminar will contain theoretical and practical components. The theoretical part will cover fundamentals of model-based design of signal processing systems, which provide an important foundation for developing efficient and reliable SPML implementations. In particular, we will cover concepts of high level dataflow models of computation with an emphasis on synchronous dataflow techniques. The practical component of the seminar will involve software exercises that provide experience applying signal-processing-oriented dataflow techniques.

Two YouTube videos that provide short introductions to material related to the seminar can be found at the following links: (1) https://www.youtube.com/watch?v=hjULlVF3Ozc, and (2) https://www.youtube.com/watch?v=P-AReEILMgY.

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Shuvra S. Bhattacharyya is a Professor in the Department of Electrical and Computer Engineering at the University of Maryland, College Park. He holds a joint appointment in the University of Maryland Institute for Advanced Computer Studies (UMIACS).  He also holds a part-time position as International Research Chair, joint with INSA/IETR, and INRIA in Rennes, France. His research interests include signal processing, embedded systems, electronic design automation, machine learning, wireless communication, and wireless sensor networks. He received the Ph.D. degree from the University of California at Berkeley.  He has held industrial positions as a Researcher at the Hitachi America Semiconductor Research Laboratory (San Jose, California), and Compiler Developer at Kuck & Associates (Champaign, Illinois). From 2015 through 2018, he was a part time visiting professor in the Department of Pervasive Computing at the Tampere University of Technology, Finland, as part of the Finland Distinguished Professor Programme (FiDiPro). He is a Fellow of the IEEE.

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In the afternoon of the first day (March 18), participants are invited to present summaries of their M.S. or Ph.D. research. Each student who is interested in presenting is requested to contact Prof. Bhattacharyya by email (sbhattacinsa-rennes [*] fr (sbhattac[at]insa-rennes[dot]fr)) with the title of the planned presentation. All M.S. and Ph.D. student participants are encouraged to take part in these presentations, and are requested to submit their presentation titles by March 15. This will help in organizing the schedule of presentations.

Lien pour l'inscription : https://framaforms.org/seminar-on-embedded-system-design-methodologies-forsignal-processing-and-machine-learning-1580807742

Informations utiles : https://hackmd.io/@Ol7nA4sDS2GxynhdgXhjpQ/B1N6YiUfI