ESWEEK (Embedded Systems Week) is piloting a new education track, where in, top researchers in the world will teach 2-hour topical class on emerging/newer, but well established embedded systems concepts, tools and methods that are not readily available in textbooks in an exciting, engaging and hands-on way to students across the globe, especially the ones that do not have access to high quality educational content.

The theme for ESWEEK Education this year is “Embedded Learning”. Please register for the ESWEEK Education classes through the main ESWEEK registration link. Please note that a limited number of attendee registration fee waivers are available for attendees with demonstrated need. More information about the ESWEEK attendee registration fee waiver program is on the registration page. In case of any questions/clarifications, please contact: Akash Kumar.

Saturday Classes

DATE/Time Class 1 Class 2 Class 3
9-11 am, Sat, Oct 09, 2021 EDT  A1. Edge AI Systems, by Prof. Lin Wang, VU Amsterdam A2. Memory-Centric Computing, by Prof. Onur Mutlu, ETH Zurich and CMU A3. Learn to Drive (and Race!) Autonomous Vehicles, by Prof. Rahul Mangharam, University of Pennsylvania and Dr. Johannes Betz, University of Pennsylvania
11 am – 1 pm, Sat, Oct 09, 2021 EDT B1. TinyML, by Prof. Vijay Janapa Reddi, Harvard University B2. Neural Networks and Accelerator Co-design, by Dr. Nicolas J Fraser, Xilinx B3: Face verification using few-shot deep learning by Prof. Amit Sethi, and Abhijeet Patil, IIT Bombay

Sunday Classes

Date/Time Class 1 Class 2 Class 3
9-11 am, Sun, Oct 10, 2021 EDT C1. Spiking Neural Networks, by Prof. Priyadarshini Panda, Yale C2. Neural Network Accelerator Design, by Prof. Yu Wang, Tsinghua University C3. Research Reproducibility in Embedded Learning, by Dr. Romain Jacob, ETH Zurich
11 am – 1 pm, Sun, Oct 10, 2021 EDT D1. Introduction to Neuromorphic Computing, by Prof. Helen Li, Duke University D2. DNNs on FPGAs, by Prof. Jaesun Seo, Arizona State University D3. Machine Learning for  Manycore System Design and Optimization, by Prof. Jana Doppa, Washington State University and Dr. Biresh Kumar, Duke University.