First International Workshop on Sustainable AI for Edge (SAI4E) 2023

With the rapid advancement of Artificial Intelligence (AI) technologies, the integration of AI into edge devices has gained significant attention. Edge computing, which enables data processing closer to the source of generation, has become essential for applications requiring real-time, low-latency, and privacy-sensitive computation. Moreover, the emerging field of neuromorphic computing, inspired by the architecture and functionality of the human brain, offers promising opportunities for efficient and intelligent edge computing systems. The First International Workshop on Sustainable AI for Edge (SAI4E 2023), as part of AIMLSys 2023, with a special focus on industry applications, aims to bring together researchers, practitioners, and enthusiasts from academia and industry to delve into the realm of sustainable AI for the edge, emphasizing the convergence of edge computing and neuromorphic computing. By combining the principles of edge computing’s decentralized approach with the brain-inspired computing paradigm of neuromorphic systems, we can explore innovative solutions that address the challenges of scalability, energy efficiency, and adaptability in AI deployments at the edge.


SAI4E 2023 invites submissions of original research papers, case studies, and review articles in the field of sustainable AI for edge computing. The workshop seeks to foster discussions on a wide range of topics, including but not limited to:

  • Energy-efficient AI algorithms for edge computing
  • Low power neuromorphic applications for intelligent edge
  • Low-power hardware and neuromorphic designs for edge devices
  • Green edge data centers and computing infrastructures
  • Resource-constrained AI at the edge
  • Energy harvesting and self-powering techniques for edge devices
  • Environmental impact assessment of edge AI deployments
  • Dynamic resource management and task scheduling in edge computing
  • Edge-based data compression and optimization techniques
  • Case studies and real-world implementations of sustainable AI for edge systems
  • AI-driven sustainability applications at the network edge
  • Lifecycle analysis and eco-design of edge devices
  • Security and privacy considerations for sustainable AI at the edge
  • Interdisciplinary approaches and collaborations in sustainable AI research.

General Workshop Chair:

Dr. Arpan Pal, Distinguished Chief Scientist, TCS Research

Workshop Advisor:

Dr. Pallab Dasgupta, Head of Research & Innovation, Synopsis Inc.

Program Co-Chairs:






TinyML Tutorial

 Swarnava Dey & Gitesh Kulkarni (TCS Research)


Keynote Talk: Importance of AI Explainability for Hight Frequency Data 

Shyam Prabhakar, Renesas


Invited Talk: Unlocking the Value of Vehicular Data: A Simple, Unsupervised Approach for On-board Driver Behavior Classification

Prof. Punit Rathore, IISc Bangalore

Tea/Coffee Break (1130-1200)


Multi-Task Learning for massive MIMO CSI Feedback 

Sharan Mourya Bathala

A Study on Tiny YOLO for Resource Constrained XRay Threat Detection

Raghav Venkata Ambati

GPU Implementation: Accelerating 3D-Bin Packing Problem

Krishna Vamsi, Ashwin Krishnan, Manoj Nambiar)

Binarized-Distance Computation for performing low-power Face Recognition with optimized storage

Vivek K Parmar, Manan Suri

Lunch Break (1330-1430)


 Keynote Talk: How can neuroscience aid in designing a mortal computer?

Prof. Ayon Borthakur, IIT Hyderabad


Invited Talk: Machine Learning for Resource-efficient Industrial and Infrastructural Inspections

Dr. Hrishikesh Sharma, TCS Research)

Tea/Coffee Break (1600-1630)


Panel discussion: Motivation, challenges, state of the art and future directions of Sustainable AI for Edge (Dr. Balamurali, TCS Research)

Panelists: Shyam Prabhakar, Ayon Borthakur, Punit Rathore, Hrishikesh Sharma



Click here to view the complete program for the workshop.

Submission Guidelines

We invite authors to submit original and unpublished research papers (upto 4 pages excluding references). All submissions will undergo a rigorous peer-review process by the program committee. The authors are requested to follow the ACM sigconf template (see All accepted papers will be published in the proceedings of AIMLSys 2023.

Submission link:

Important Dates

  • Paper Submission Deadline: 31st August 2023 21stSeptember 2023
  • Notification of Acceptance: 30th September 2023
  • Camera-Ready Deadline: 8th October 2023
  • Workshop Date: 28th October 2023

Workshop Organization

The workshop will feature keynote speeches, technical paper presentations, interactive poster sessions, and panel discussions. Additionally, it will foster networking opportunities for participants to connect with fellow researchers and industry experts.

Keynote Speakers

We are pleased to announce that leading experts in Sustainable AI and Edge Computing will deliver keynote speeches at SAI4E 2023. Stay tuned for updates on the AIMLSys workshop pages!

Workshop Venue

The Chancery Pavilion | Bengaluru, India

Contact Information

For any inquiries regarding the workshop, please feel free to contact the workshop organizers.

Join us at SAI-Edge 2023 to shape the future of Sustainable AI at the Edge!