Systems for the Future of AI/ML (SysAI)

Call for Papers

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Camera Ready Guidelines

https://www.comsnets.org/camera_ready.html

Accepted Papers

BloBS-FL: A Robust Architecture of Blockchain Based Decentralized Split Federated Learning
Shruti Mishra (Indian Institute of Technology Ropar, India), Yashasav Prajapati (Indian Institute of Technology Ropar, India), Keshav Aggarwal (Indian Institute of Technology Ropar, India), Sujata Pal (Indian Institute of Technology Ropar, India)
Post-Quantum Secure IoT-Enabled Crop Recommender System Using Machine Learning
Snehal Jain (International Institute of Information Technology, Hyderabad, India), Abhishek Pandey (International Institute of Information Technology Hyderabad, India), Ashok Kumar Das (International Institute of Information Technology, Hyderabad, India), Shantanu Pal (Deakin University, Australia)
Adaptive Model Selection using Meta Models and Drift Adaptation
Karthikeya Maruvada (Indian Institute of Technology Roorkee, India), Houssam Hajj Hassan (Télécom SudParis, France), Ajay Kattepur (Ericsson Research, India), Georgios Bouloukakis (University of Patras, Greece & Télécom SudParis, IP Paris, France)
A Hybrid Geostatistical and Deep Learning Framework for Urban Pollutant Concentration Prediction from Sparse Data
Chinmay Gupta (IIT Kharagpur, India), Arhat Amitabh (Indian Institute of Technology Kharagpur, India), Kapil Kumar Meena (Indian Institute of Technology Kharagpur, India), Arkopal Kishore Goswami (Indian Institute of Technology Kharagpur, India)
TinyFlame: Context-Aware Cooking Activity Detection Using Flame Sensing on Edge Devices
Ruma Ghosh (National Institude of Technology, Durgapur & B. C. Roy Engineering College, India), Rima Gorai (Dr B C Roy Engineering College, Durgapur, India), Gokul Pal (Dr B C Roy Engineering College, Durgapur, India), Sneha Chand (Dr B C Engineering College, Durgapur, India), Arindam Ghosh (Dr B C Roy Engineering College, Durgapur, India), Sujoy Saha (National Institute of Technology, Durgapur, India)
DIRECT: Enabling Scalable Processing-In-Memory via DPU-to-DPU Communication
Prateek P Kulkarni (PES University, Bangalore, India)
FusionPhishGuard: An Attention-Enhanced Multi-Branch Framework for Intelligent Phishing Detection on Mobile and Web Platforms
Yashwanth Yallavula (CBIT, Osmania University & Chaitanya Bharathi Institute of Technology, India), Srikanth Panigrahi (Chaitanya Bharathi Institute of Technology & VIT Bhopal University, India), Manoj Kumar Sunkara (Cbit, Osmania University & Chaitanya Bharathi Institute of Technology, India), Vishwanath Tangella (CBIT, Osmania University & Chaitanya Bharathi Institute of Technology, India)
Survival Classification of High-Grade Gliomas using an Interpretable 3D Multi-modal System
Sandeep Verma (Thapar Institute of Engineering & Technology, India), Neeraj Kumar (Thapar Institute of Engineering and Technology, India)
PDFInspect: A Unified Feature Extraction Framework for Malicious Document Detection
Sharmila SP (Indian Institute of Technology Indore & Siddaganga Institute of Technology, Tumakuru, India)
iAirGuard: A Modular IoT Architecture with Dynamic Sampling and TinyML-Based Fault Detection for Air Quality Monitoring
Molay Mondal (National Institute of Technology Durgapur, India), Arko Datta (Indian Institute of Technology Madras, India), Prashanth Durgam (National Institute of Technology Durgapur, India), Astom Mondal (B. C. Roy Engineering College, India), Khushi Shyam (B. C. Roy Engineering College, India), Pabitra Majhi (National Institute of Technology Durgapur, India), Subrata Nandi (National Institute of Technology, Durgapur, India), Sanghita Bhattacharjee (National Institute of Technology, Durgapur, India), Sujoy Saha (National Institute of Technology, Durgapur, India)
Energy-Efficient Coverage Path Planning for Multi-UAVs in Dynamic Threat Environments
Pranita Mahajan (IIIT Guwahati, India), Abdul Kayum Ali (IIIT Uwahati, India), Navya Dhawde (IIIT Guwahati, India), Nilotpal Chakraborty (Indian Institute of Information Technology, Guwahati, India), Mirza Ghalib Anwarul Husain Baig (IIT Mandi, India)
DPNet: A Lightweight TinyML Model for Real-Time Bathroom Sound Classification
Debolina Chowdhury (National Institute of Technology Durgapur, India), Chawan Vinod (National Institute of Technology Durgapur, India), Suman Samui (National Institute of Technology Durgapur, India), Mousumi Saha (NIT Durgapur, India), Sujoy Saha (National Institute of Technology, India)
Learning-Based Optimization of EV Routing with V2G Integration & On-the-Go Energy Harvesting
Risshab Srinivas Ramesh (Ramaiah Institute of Technology, India), Prasant Misra (Indian Institute of Science, Bengaluru, India), Pandara Swamy Arjunan (Indian Institute of Science, Bangalore, India)
TinyMLAir: Indoor Air Quality of Domestic Activities through TinyML
Pritisha Sarkar (NSHM Knowledge Campus, Durgapur, India), Kushalava Reddy Jala (TCS, India), Mousumi Saha (NIT Durgapur, India)
Leveraging Conditional Distribution Similarity for Task-Aware Personalization in Federated Learning
Fatema Huseni Vadnagarwala (VNIT, Nagpur, India), Prashanth Pvn (Visvesvaraya National Institute of Technology, Nagpur, India)
ML-Based Refrigerator Scheduling for Energy Efficiency in Renewable-Integrated Smart Homes
Sanjiban Roy (Indian Institute of Information Technology Guwahati, India), Yamini Sisodia (Indian Institute of Information Technology, Guwahati, India), Nilotpal Chakraborty (Indian Institute of Information Technology, Guwahati, India), Preveen Kumar Devarajan (NCMRWF, India)

Important Dates

Paper Submission deadline: ~~15^th October 2025 (AoE)~~ 30^th October 2025 (AoE)
Notification of Acceptance: ~~15^th November 2025~~ ~~20^th November 2025~~ 26^th November 2025
Camera-ready Submission: ~~30^th November 2025~~ 5^th December 2025
Workshop Date: 6^th January 2026

Workshop Overview

The rapid evolution of Artiﬁcial Intelligence (AI) and Machine Learning (ML) has brought unprecedented opportunities and challenges. As organizations increasingly deploy AI/ML solutions at scale and the edge, there is a growing need for expertise in developing, optimizing, and managing these systems. The workshop aims to bring together professionals from academia and industry to discuss and explore the challenges, solutions, and advancements in building robust and eﬃcient systems that support real-world AI and ML solutions operating at scale and at the edge.

We invite researchers, practitioners, and experts in the ﬁelds of Computer Systems, Artiﬁcial Intelligence (AI) and Machine Learning (ML) to contribute to our upcoming workshop on "Systems for the Future of AI/ML." The workshop aims to bring together professionals from academia and industry to discuss and explore the challenges, solutions, and advancements in building robust and eﬃcient systems that support real-world AI and ML solutions operating at scale and at the edge.

Topics of Interest:

We encourage the submission of papers on a wide range of topics related to systems for AI and ML, particularly focusing on developments at scale and the edge. Relevant areas of interest include, but are not limited to:

Updating current systems to support ever-growing ML models
Scalable system architectures for the future of AI/ML
AI/ML for large-scale edge computing solutions
Distributed systems for distributed AI models of the future
Efficient deployment of AI models of the future
Real-time processing and inference at the edge
Resource-efficient algorithms for large-scale data
Optimization techniques for edge-based AI applications
System enhancements to bring AI to the edge
Case studies and practical experiences in deploying AI/ML at scale and the edge.
Hardware-aware AI modelling and deployments
Platform and AutoML for edge AI operations
Generative AI on the edge
Technical benchmarking and experiences from large-scale edge-based AI solutions

Submission Guidelines

SysAI invites submission of original work not previously published or under review at another conference or journal.
Submissions (including title, abstract, all figures, tables, and references) must be no greater than 6 pages in length.
Reviews will be double-blind: Information about the authors will not be shared with the reviewers during the review process. The submitted paper should be anonymous and not have any reference to the authors' names or institutions.
Submissions must follow the formatting guidelines as given on the IEEE Website; and those that do not meet the size and formatting requirements will not be reviewed.
All papers must be in Adobe Portable Document Format (PDF) and submitted through the SysAI Workshop submission site on EDAS.
All workshop papers will appear in the conference proceedings and be submitted to IEEE Xplore and other Abstracting and Indexing (A&I) databases.

Papers can be submitted through EDAS: https://edas.info/N34339

For any queries, please contact the workshop chairs at comsnets.workshop@gmail.com

Technical Program Committee

Sourav Kanti Addya (NIT Surathkal)
Pramit Biswas (Intel)
Soumyajit Chatterjee (Brave)
Debasree Das (University of Bamberg)
Snigdha Das (Ericsson Research)
Ritesh Kalle (Hitachi Research, India)
Ajay Kattepur (Ericsson Research)
Meera Lakshmi (University of Technology Sydney)
Guohao Lan (TU Delft)
Basabdatta Palit (IIEST)
Sugandh Pargal (Fujitsu)
Sougata Sen (BITS PIlani - Goa Campus)
Dulanga Weerakoon (SMART Research Centre, Singapore)
Poonam Yadav (University of York, UK)