Call for Participation:


Virtual Conference, October 8 – 15, 2021


  • ESWEEK 2021 attendee registration is only USD 10 for IEEE/ACM members and USD 20 for others, and a limited number of free registrations are available (via a fee waiver) for attendees with demonstrated need:
  • ESWEEK 2021 features a new Education Track, which comprises of classes aimed at background knowledge of various topics in “embedded learning”:
  • Technical program:

About Embedded Systems Week (ESWEEK)
Embedded Systems Week (ESWEEK) is the premier event covering all aspects of hardware and software design for smart, intelligent and
connected computing systems. By bringing together three leading conferences (CASES, CODES+ISSS, EMSOFT), one symposium (NOCS), and several workshops and tutorials, ESWEEK allows attendees to benefit from a wide range of topics covering the state of the art in embedded systems research and development.

The registration covers all events at ESWEEK including CASES, CODES+ISSS, EMSOFT, NOCS, keynote, panel, workshops, tutorials, and educational classes. There will be pre-recorded 2-3min lightning talks and papers available through Whova before the conference for participants to comment and post questions. During the conference, will be used as main platform to access all live and interactive content throughout the conference week. You will be able to interact with other attendees, network, attend all talks or join poster sessions in the ESWEEK 2021 Gather space.

More details:


  • September 24, 2021: Papers and pre-recorded lightning videos will be online. Questions about papers can be asked through the Whova platform.
  • October 8–15, 2021: ESWEEK Virtual Conference with live sessions and interactive posters through


  • Monday Keynote: “Advances in Neuromorphic Computing for Fast, Efficient, and Intelligent Processing”, by Mike Davies, Intel Labs
  • Tuesday Keynote: “Safe Learning in Robotics”, by Claire Tomlin, University of California at Berkeley
  • Wednesday Keynote: “Why is Machine Learning on Embedded Systems so Important?”, by Pete Warden, Google

Special Interest Days

Tuesday, October 12: “Special Industry Day” (

  • Two special sessions on collaborative industry-academia European research projects
  • An industry pitch and poster session

Wednesday, October 13: “Special Edge AI Day” (

  • Keynote “Why is Machine Learning on Embedded Systems so Important?”
  • Topic-related journal-track papers
  • Two special sessions on “Automated Edge AI Design” and “New Applications, Systems, and Challenges toward Designing New ‘Things’ at the Edge”
  • A panel about “Machine Learning on the Edge: How deep can we ’embed’ it into the Cloud-Edge continuum?”


  • CASES: International Conference on Compilers, Architecture, and Synthesis for Embedded Systems (
    Program Chairs: Umit Ogras, University of Wisconsin-Madison, US
    Preeti Panda, IIT Delhi, IN
  • CODES+ISSS: International Conference on Hardware/Software Codesign and System Synthesis (
    Program Chairs: Jason Xue, City University of Hong Kong, HK
    Chengmo Yang, University of Delaware, US
  • EMSOFT: International Conference on Embedded Software (
    Program Chairs: Linh Thi Xuan Phan, University of Pennsylvania, US
    David Broman, KTH Royal Institute of Technology, SE


Tutorials (T) and Industrial Tutorials (IT) (

  • T1. QuantumFlow: A Co-Design Framework of Neural Network and Quantum Circuit towards Quantum Advantage
  • T2. Fog Computing for Industrial IoT
  • T3. Deterministic Reactive Programming for Cyber-Physical Systems Using Lingua Franca
  •  IT1. Scalable SoC Architecture for Edge AI Products, Intel
  • IT2. Integrating Compute Acceleration Into Embedded System Design Using Vitis, Xilinx
  • IT3. GPU Code Generation from MATLAB and Simulink, Mathworks Inc.

Workshops (

  • International Workshop on Memory and Storage Computing (MSC)
  • International Workshop on Rapid System Prototyping (RSP)
  • Trustworthy and Reliable AI accelerator desigN (TRAIN)

Education Track (

  • “Edge AI Systems”, Lin Wang, VU Amsterdam
  • “Memory-Centric Computing”, Onur Mutlu, ETH Zurich and CMU
  • “Learn to Drive (and Race!) Autonomous Vehicles”, Rahul Mangharam and Johannes Betz, University of Pennsylvania
  • “TinyML on Edge”, Vijay Janapa Reddi, Harvard University
  • “Binarized Neural Network Inference”, Nicolas J Fraser, Xilinx
  • “Research Reproducibility in Embedded Learning”, Romain Jacob, ETH Zurich
  • “Spiking Neural Networks”, Priyadarshini Panda, Yale
  • “Neural Network Accelerator Design”, Yu Wang, Tsinghua University
  • “Introduction to Neuromorphic Computing”, Helen Li, Duke University
  • “DNNs on FPGAs”, Jaesun Seo, Arizona State University
  • “Machine Learning-Driven Manycore Systems”, Biresh Kumar, Duke University, Jana Doppa, Washington State University

Organization (

Andreas Gerstlauer, University of Texas at Austin, US (General Chair)
Aviral Shrivastava, Arizona State University, US (Vice General Chair)
Tulika Mitra, National University of Singapore, SG (Past Chair)

Virtual Conference Chairs:
Sudeep Pasricha, Colorado Statue University, US (Chair)
Hoeseok Yang, Ajou University, KR (Co-Chair)