IEEE International Workshop on Electronic Design Automation and Machine Learning (EDAML), 2022

Jun 3, 2022 (10AM ET – 3PM ET)
Co-located with 36th IEEE International Parallel and Distributed Processing Symposium (IPDPS)
May 30 – June 3, 2022, Ecole Normale Supérieure de Lyon Lyon, France

Please register here by May 23 for the early bird rates. Registration includes access to EDAML and the entire IPDPS 2022 conference


Machine Learning (ML) has evolved substantially over the past decade and is now an integral component of many applications such as classification and object detection in images and video, speech recognition and language translation, data mining and pattern recognition, and cybersecurity. However, the design of server, edge, and embedded/IoT computing platforms to support these ML and other emerging applications remains a significant challenge. This workshop aims to explore the intersection of ML and electronic design automation (EDA) and define a roadmap to realize the next generation of parallel and distributed computing systems. Topics of interest to this workshop include but are not limited to:

  • ML for EDA physical design (layout, placement, routing, etc.)
  • ML for EDA with emerging technologies (photonics, ReRAM, quantum, etc.)
  • ML for test, verification, and validation
  • ML for resource, power, and thermal management in manycore computing
  • Hardware/software co-design with ML
  • ML for electronic chip security and reliability
  • ML for analog and mixed-signal design
  • ML accelerator design for next generation parallel and distributed systems
  • EDA for ML and AI Systems (also covering tinyML and EdgeAI)

This year’s program will feature a keynote talk by Prof. David Pan from The University of Texas at Austin and ten invited talks from experts in the field of EDA and ML. We thank the keynote and invited speakers for contributing to a high-quality technical program for this inaugural edition of the EDAML workshop.

Workshop General Chairs:

Sudeep Pasricha, Colorado State University (
Muhammad Shafique, New York University, Abu Dhabi (

Keynote Speaker

David Pan, The University of Texas at Austin

Invited Speakers

Ankush Sood, Cadence Design Systems
Deming Chen, University of Illinois at Urbana-Champaign
Krishnendu Chakrabarty, Duke University
Laleh Behjat, University of Calgary, Alberta, Canada
Muhammad Shafique, New York University, Abu Dhabi, UAE
Partha Pande, Washington State University
R. Iris Bahar, Colorado School of Mines
Sachin S. Sapatnekar, University of Minnesota
Sheldon Tan, University of California at Riverside
Sudeep Pasricha, Colorado State University