Systems for the Future of AI/ML (SysAI)

Schedule

Monday, 6th January 2025
Venue: SIGMA 1
Time	Title	Speaker/Authors
9:30 - 9:45	Welcome by Workshop Chairs
9:45 - 10:45	Keynote Talk 1: Scaling and Optimizing ML Workloads on Edge Accelerators	Prof. Yogesh Simmhan, IISc Bangalore, India
10:45 - 11:30	Networking and Tea break
Presentation Session: 15 mins (including Q&A)
11:30 - 11:45	Integrated LLM Based Reasoning for Safe and Efficient Decision Modeling in Assisted Driving	Jaswanth Nidamanuri (Woxsen University), Akash Kalasagond (Woxsen University), Kasam Rohith Reddy (Woxsen University), Sunke Durgaprsad (Woxsen University), Jaswanth Nidamanuri (Woxsen University)
11:45 - 12:00	Deep Digital Twin Services for Personalized MPX Treatment	Cephas Iko-Ojo Gabriel (SRM University AP, India), Randhir Kumar (SRM University AP, India), Krishna Prasad (SRM University AP, India)
12:00-12:15	Use of Agent-based Modeling to Gauge Impact of Lockdown Strategies on Spread of COVID-19 on an Educational Campus	Vibha Patil (BITS Pilani, Goa), Vinayak Naik (BITS Pilani, Goa)
12:15-12:30	Phone Patrol: An Intelligent Surveillance System for Mobile-Free Environments	Aritra Dutta Banik (Heritage Institute of Technology), Trisagni Mandal (Heritage Institute of Technology), Anubhab Mukherjee (Heritage Institute of Technology), Sharnabho Chatterjee, Raja Karmakar (Heritage Institute of Technology)
13:00-14:00	Lunch Break
14:00 - 15:00	Keynote Talk 2: Providing High Reliability in the Google Global Network	Ranjita Bhagwan, Google, India
Presentation Session: 15 mins (including Q&A)
15:00 - 15:15	Resource-Aware Monkeypox Diagnosis: Leveraging High-Capacity and Lightweight Models with Knowledge Distillation	Avi Deb Raha (Khulna University, Bangladesh), Mrityunjoy Gain(Khulna University, Bangladesh), Sudip Kumar Saha (United International University, Bangladesh), Shohanur Rahman (KUET, Bangladesh), Apurba Adhikary (Noakhali Science and Technology University, Bangladesh), Rameswar Debnath(Khulna University, Bangladesh), Sujit Biswas (City University of London), Anupom Kumar Bairagi (Khulna University, Bangladesh)
15:15 - 15:30	Enhancing Autonomous Perception: Integrating Multi-Sensor Data for Robust Perception	Kajal Gupta (Gahan AI Pvt Ltd), Adit Singhal (Gahan AI Pvt Ltd), Ajit Kumar (Gahan AI Pvt Ltd), Pallab Maji (Gahan AI Pvt Ltd)
15:30 - 15:45	Hybrid Quantum-Classical Transfer Learning for Real-Time Data Processing	Mahesh Babu Chittem (SRM University AP, India), Ashok Kumar Pradhan (SRM University AP, India)
15:45 - 16:00	Limited Training Approach To Model Latent Fingerprint Data For Time-Constrained Solutions	Gottam Sai Nithin Reddy (Woxsen University), Kiran Kumar Ravulakollu (MNR University), Mayur Jadhav (Woxsen University), Varshith Batti (Woxsen University), Varshtih Kumar Vupputuri (Woxsen University), Rohith Kumar Polishetty (Opplane Inc)
16:00 - 16:30	Networking and Tea break
16:30 - 17:30	Panel Discussion: Empowering Future Systems for Real-World AI/ML Solutions	Moderator: Prasant Misra (TCS Research, India) Panelists: Bindu Sunil (Aptiv), Vaanathi Sundaresan (IISc Bangalore), Amit S. Baxi (Intel Labs, India), Amod Jai Ganesh Anandkumar (Harman International, India)
17:30-18:00	Closing & Best Paper Award announcement

Call for Papers

Download PDF version of the Call For Papers

Camera Ready Guidelines

Download PDF version of the Camera Ready Instructions

Accepted Papers

Integrated LLM Based Reasoning for safe and Efficient Decision Modeling in Assisted Driving
Jaswanth Nidamanuri (MNR University), Akash Kalasagond (Woxsen University), Kasam Rohith Reddy (Woxsen University), Sunke Durgaprsad (Woxsen University)
Deep Digital Twin Services for Personalized MPX Treatment
Cephas Iko-Ojo Gabriel (SRM University AP, India), Randhir Kumar (SRM University AP, India), Krishna Prasad (SRM University AP, India)
Use of Agent-based Modeling to Gauge Impact of Lockdown Strategies on Spread of COVID-19 on an Educational Campus
Vibha Patil (BITS Pilani, Goa), Vinayak Naik (BITS Pilani, Goa)
Phone Patrol: An Intelligent Surveillance System for Mobile-Free Environments
Aritra Dutta Banik (Heritage Institute of Technology), Trisagni Mandal (Heritage Institute of Technology), Anubhab Mukherjee (Heritage Institute of Technology), Sharnabho Chatterjee, Raja Karmakar (Heritage Institute of Technology)
Resource-Aware Monkeypox Diagnosis: Leveraging High-Capacity and Lightweight Models with Knowledge Distillation
Avi Deb Raha (Khulna University, Bangladesh), Mrityunjoy Gain(Khulna University, Bangladesh), Sudip Kumar Saha (United International University, Bangladesh), Shohanur Rahman (KUET, Bangladesh), Apurba Adhikary (Noakhali Science and Technology University, Bangladesh), Rameswar Debnath(Khulna University, Bangladesh), Sujit Biswas (City University of London), Anupom Kumar Bairagi (Khulna University, Bangladesh)
Enhancing Sensor Perception: Integrating Multi-Sensor Data for Robust Sensor Perception
Kajal Gupta (Gahan AI Pvt Ltd), Adit Singhal (Gahan AI Pvt Ltd), Ajit Kumar (Gahan AI Pvt Ltd), Pallab Maji (Gahan AI Pvt Ltd)
Hybrid Quantum-Classical Transfer Learning for Real-Time Data Processing
Mahesh Babu Chittem (SRM University AP, India), Ashok Kumar Pradhan (SRM University AP, India)
Limited Training Approach To Model Latent Fingerprint Data For Time-Constrained Solutions
Gottam Sai Nithin Reddy (Woxsen University), Kiran Kumar Ravulakollu (MNR University), Mayur Jadhav (Woxsen University), Varshith Batti (Woxsen University), Varshtih Kumar Vupputuri (Woxsen University), Rohith Kumar Polishetty (Opplane Inc)

Important Dates

Manuscript Submission Due: ~~27th October 2024 (AoE)~~ ~~10th November 2024 (AOE)~~ 17th November 2024 (AoE) (EXTENDED and FIRM)
Notification of Acceptance: 3rd December 2024
Camera-ready Submission: 10th December 2024
Workshop Date: 6th January 2025

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, author list, abstract, figures, tables, references, appendix) must be no more than six pages long.
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 and/or institutions.
Submissions must follow the formatting guidelines 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 HOTCRP.
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 HOTCRP: https://comsnets25sysai.hotcrp.com/

For any queries please contact us at SysAI Chairs:comsnets.sysai@gmail.com comsnets.workshop@gmail.com

Keynote Speakers

Ranjita Bhagwan

Google, India

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6th January 2025, 2:00 - 3:00 PM, SIGMA Hall 1

Providing High Reliability in the Google Global Network

Google owns and operates one of the world's largest networks, supporting billions of users. Today, this network not only supports the users of Google's various applications such as Search, Youtube, Gmail and Maps, it also forms a critical part of the infrastructure supporting enterprise customers of the Google Cloud Platform. Given the scale and the challenging requirements of such varied applications, the network incorporates many aligned but complementary techniques to ensure high network reliability. In this talk, I will describe some of these techniques, and how they work in tandem to provide a high-reliability network to all of Google's users.

Ranjita Bhagwan is currently a Principal Engineer at Google, working on making Google's network highly reliable. Prior to this, she was a Senior Principal Researcher at Microsoft Research India, where she worked for more than a decade on applying machine learning to improve system reliability, security and performance. Recently, her work has focused on using data-driven approaches to improve cloud services and has led to several publications and awards. She is an ACM Distinguished Member, INAE Fellow, and is the recipient of the 2020 ACM India Outstanding Contributions to Computing by a Woman Award. She received her PhD and MS in Computer Engineering from the University of California, San Diego and a BTech in Computer Science and Engineering from the Indian Institute of Technology, Kharagpur.

Yogesh Simmhan

IISc, Bangalore, India

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6th January 2025, 9:45 - 10:45 AM, SIGMA Hall 1

Scaling and Optimizing ML Workloads on Edge Accelerators

Edge accelerators such as Nvidia Jetsons have grown more pervasive and capable, with deployments in urban safety cameras, drones, etc. Besides 100-1000s of CUDA cores, tensor cores and DLA, and a compact power envelope and form factor, they also expose 1000s of power modes that control their CPU cores, and CPU, memory and CUDA frequencies. This offers a viable trade-off space when tuning such platforms for speed and power consumption for ML workloads. This talk will explore such systems optimizations and opportunities for edge accelerators used in ML applications ranging across federated learning, smart cities, drone fleet management and agentic workflows.

Yogesh Simmhan is an Associate Professor in the Department of Computational and Data Sciences and a Swarna Jayanti Fellow at the Indian Institute of Science, Bangalore. His research explores scalable software platforms, algorithms and applications on distributed systems. These span Cloud and Edge Computing, Temporal Graph Processing, and Scalable Machine Learning to support emerging Big Data and Internet of Things (IoT) applications. He has published over 100 peer-reviewed papers, and won the Best Paper Award at IEEE International Conference on Cloud Computing (CLOUD) 2019, IEEE TCSC SCALE Challenge Award in 2019 and 2012, the Distinguished Paper award at EuroPar 2018, and the IEEE/ACM Supercomputing HPC Storage Challenge Award in 2008. He is the recipient of the IEEE TCSC Award for Excellence in Scalable Computing (Mid Career Researcher) in 2020. He is an Associate Editor-in-Chief of the Journal of Parallel and Distributed Systems (JPDC), an Associate Editor of Future Generation Computing System (FGCS), and earlier served as an Associate Editor of IEEE Transactions on Cloud Computing and a member of the IEEE Future Directions Initiative on Big Data.

Yogesh has a Ph.D. in Computer Science from Indiana University, Bloomington, and was previously a Research Assistant Professor at the University of Southern California (USC), Los Angeles, and a Postdoc at Microsoft Research, San Francisco. He is a Distinguished Member of ACM, a Distinguished Contributor of the IEEE Computer Society and serves on the ACM India Executive Council.

Panel Discussion

Empowering Future Systems for Real-World AI/ML Solutions

The panel brings together experts in artificial intelligence, machine learning, and computer systems to explore how technological advancements are shaping AI/ML integration into real-world applications. As the demand for scalable, robust, and ethical AI solutions grows, this discussion will delve into the interplay between hardware innovations, software frameworks, and societal needs. The panel will address the challenges of building systems capable of handling the computational and data-intensive requirements of modern AI while ensuring efficiency, inclusivity, and adaptability. Attendees will gain insights into the cutting-edge research and practices that will enable next-generation systems to empower industries and improve lives globally. This discussion aims to ignite a constructive dialogue on bridging the gap between the oretical advancements and practical implementations of AI/ML, ultimately setting the stage for a more intelligent and interconnected future.

Date & Venue: 6th January 2025, 4:30 - 5:30 PM, SIGMA Hall 1

Panelists

Moderator

Prasant Misra

TCS Research
India

Technical Program Committee

Krishna Chaythanya KV, Qualcomm
Soumyajit Chatterjee, Nokia Bell Labs
Snigdha Das, Ericsson Research
Surjya Ghosh, BITS PIlani - Goa Campus
Ritesh Kalle, Hitachi Research, India
Meera Lakshmi, University of Technology Sydney
Guohao Lan, TU Delft
K P Naveen, IIT Tirupati
Basabdatta Palit, NIT Rourkela
Bharadwaj Satchidanandan, IIT Madras
Sougata Sen, BITS PIlani - Goa Campus
Dulanga Weerakoon, SMART Research Centre, Singapore
Poonam Yadav, University of York, UK