News
[June 16th] Workshop schedule (tentative) is online!
[May 29th] The list of accepted papers is online!
ACM MobiSys 2025 Workshop on Networked AI Systems
The 3rd International Workshop on Networked AI Systems (NetAISys), AI at the Edge & Beyond for Emerging Computing Frontiers, colocated with MobiSys 2025, aims to bring together leading experts in the field to explore the latest advancements and challenges in the integration of AI and networking technologies. Such integration is driving the development of intelligent and autonomous systems that are capable of making decisions and performing tasks in real-time. The workshop will provide a platform for the presentation and discussion of cutting-edge research, the demonstration of innovative networked AI systems and applications, and the exchange of ideas, experiences, and case studies. The significance of this workshop to the ACM MobiSys community lies in the growing reliance on AI systems that are connected to and operate within wireless networks. With AI/ML migrating to the network edge, there is an increasing demand for efficient and effective AI systems that play a crucial role in powering various intelligent and autonomous systems in dynamic network environments with varying network conditions. By bringing together researchers, practitioners, and industry professionals, we hope to create a collaborative environment and a one-of-kind and valuable opportunity to delve into the challenges and latest advancements presented by networked AI systems and applications. We look forward to sharing our experience and insights with the ACM MobiSys community.
Workshop on Networked AI Systems
In its third edition, NetAISys '25 builds upon the success of NetAISys '23 and NetAISys '24, which were among the most well-attended workshops at ACM MobiSys '23 (Helsinki) and ACM MobiSys '24 (Tokyo). The positive reception of previous editions motivates us to continue this initiative in collaboration with ACM MobiSys '25.
Schedule
In 2025, we are pleased to announce that the NetAISys Workshop will once again be merged with the EnvSys Workshop, forming a combined, day-long event. While the two workshops focus on different yet complementary aspects of AI, they share a common vision: integrating AI into real-world systems. EnvSys emphasizes applying AI technologies to environmental sensing—addressing pressing environmental issues through tech-driven solutions—whereas NetAISys explores the use of AI in networking systems, investigating the challenges and opportunities it presents. We believe this merger will encourage vibrant discussions and promote the exchange of ideas across a broader spectrum of research at the intersection of networking, AI, and environmental sensing. The focus areas of EnvSys, in particular, provide compelling real-world use cases for networked AI systems. The joint workshop program will feature eleven papers, including five from the EnvSys workshop and six from the NetAISys workshop. Each paper presentation is allocated 15 minutes, followed by a 3-minute Q&A session. The event will also include two keynotes to foster interactive and cross-disciplinary dialogue.
- 08:00 – 09:00: Registration and Breakfast
- 09:00 – 09:05: Opening Remarks
- 09:05 – 09:45: Keynote Speaker – Prof. Yasamin Mostofi, University of California Santa Barbara
- Title: Environmental Sensing and Perception with Wireless Signals
- Abstract: Communication signals are ubiquitous these days. This has inspired using them beyond communication, e.g., for sensing and learning about the environment. In this talk, I will provide an overview of some of our work on mathematical modeling, design principles, and practical applications for wireless sensing and perception. I will start by examining crowd analytics, with an emphasis on understanding collective behaviors and uncovering emerging crowd patterns. Along this line, I will present a new mathematical modeling framework, using tools such as stochastic geometry and queuing theory, that captures and extracts key collective crowd parameters. Next, I will focus on scene understanding. I will set forth that the scattered RF signals off of objects carry rich information about the edges of the objects. Based on this observation, I then propose a new way of thinking about RF imaging and scene understanding, via edge tracing. More specifically, I will show how the Geometrical Theory of Diffraction (GTD) and the corresponding Keller cones can be exploited to image edges of the objects. I will then demonstrate the applicability of this approach by showing how WiFi can image and read the English alphabets through walls. In the third part of the talk, I will then address one major issue in applying deep learning to RF sensing problems: lack of large enough RF training data to achieve generalizable results. Along this line, I will show how recent advances in computer vision can be harnessed to develop generalizable machine learning models for RF sensing, and further discuss how this approach has enabled a large, successful clinical trial for gait disorder assessment using commodity WiFi signals. Finally, I will discuss how unmanned vehicles can expand the capabilities of wireless sensing systems.
- Biography: Yasamin Mostofi received the B.S. degree in electrical engineering from Sharif University of Technology, and the M.S. and Ph.D. degrees from Stanford University. She is currently a professor in the Department of Electrical and Computer Engineering at the University of California Santa Barbara. Yasamin is the recipient of the Presidential Early Career Award for Scientists and Engineers (PECASE), the Antonio Ruberti Prize from the IEEE Control Systems Society (research contribution award for 40 and under), the National Science Foundation (NSF) CAREER award, and the IEEE Outstanding Engineer Award of Region 6 (more than 10 Western U.S. states), among other awards. She is a fellow of IEEE. She was a semi-plenary speaker at the 2018 IEEE Conference on Decision and Control (CDC) and a keynote speaker at the 2018 Mediterranean Conference on Control and Automation (MED). Yasamin's research is multi-disciplinary, in the two areas of wireless systems and robotics. Current high-level research thrusts include 1) RF sensing for several different applications such as occupancy analytics, collective behaviors, through-wall imaging, context inference, smart health, and smart spaces; and 2) communication-aware robotics, UAV-assisted connectivity, and joint robotic path planning and communication. Her research has appeared in several reputable news venues such as BBC, New Scientist, Daily Mail, Engadget, TechCrunch, NSF Science360, ACM News, and IEEE Spectrum, among others. Yasamin has served in many different professional capacities over the years. Recent samples include serving on the inaugural editorial board of NPJ Wireless Technology as part of Nature Portfolio, serving on the Board of Governors of IEEE CSS, serving as a senior editor for IEEE TCNS, and serving as a program co-chair for ACM MobiCom 2022, among others.
- 09:45 – 10:55: Session 1 – Edge AI and Intelligent Sensing Systems
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Bringing Edge Intelligence to Wildlife Camera Traps with Hyperdimensional Computing (NetAISys)
Jida Zhang, Timothy Jacques, Joseph Chen, Zerina Kapetanovic (Stanford University) -
Sensor-free Microclimate Monitoring Using Existing LoRaWAN Signal Characteristics (EnvSys)
Fateme Nikseresht, Victor Ariel Leal Sobral, Moeen Mostafavi, Brad Campbell (University of Virginia) -
Wi-Chat: Large Language Model-powered Wi-Fi-based Human Activity Recognition (EnvSys)
Yili Ren (University of South Florida); Haopeng Zhang, Haohan Yuan (University of Hawaii at Manoa); Jingzhe Zhang, Yitong Shen (University of South Florida) -
Presto: Hybrid CPU-GPU Preprocessing Framework for Video-based AI Inference System (NetAISys)
Jihyuk Lee (Chung-Ang University); Dongsu Han (KAIST); Jaehong Kim (Carnegie Mellon University) - 10:55 – 11:00: Break
- 11:00 – 11:55: Session 2 – ML Pipelines, Metadata, and Infrastructure
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MRM3: Machine Readable ML Model Metadata (NetAISys)
Andrej Čop, Blaž Bertalanič, Marko Grobelnik, Carolina Fortuna (Jožef Stefan Institute) -
SensorMCP: A Model Context Protocol Server for Custom Sensor Tool Creation (NetAISys)
Yunqi Guo, Guanyu Zhu, Kaiwei Liu, Guoliang Xing (The Chinese University of Hong Kong) -
Empirical Analysis of LLMDPP: Advancing Log Parsing in the LLM Era (NetAISys)
Kehan Wang, Siqin Zhang, Haijing Nan, Xueyu Hou (China Telecom Cloud Computing Corporation); Jiaqi Zou (Tsinghua University); Zicong Miao (China Telecom Cloud Computing Corporation) - 11:55 – 14:00: Lunch Break
- 14:00 – 14:45: Keynote Speaker – Juheon Yi, Senior Researcher (Microsoft)
- Title: Edge-Cloud Cooperative Platform for Interactive Video Analytics
- Biography: Juheon Yi is a senior researcher at Microsoft Research Asia. His research interests lie in edge AI systems and video analytics. Specifically, his research focuses on characterizing the workloads of interactive video analytics applications and building core mobile/edge systems to support them. Juheon’s work has been consistently recognized at top-tier conferences and journals, including ACM MobiCom, MobiSys, Multimedia, IEEE INFOCOM, and IEEE Transactions on Mobile Computing. He is a recipient of the Microsoft Research PhD Fellowship, Best Paper Award in ACM Students in MobiSys 2021 Workshop, and Best PhD Dissertation Award from the Department of Computer Science and Engineering (CSE), Seoul National University (SNU).
- 14:45 – 15:05: Coffee Break
- 15:05 – 16:20: Session 3 – Intelligent Environments
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CrashSniffer: UWB-Based Anchor-Free Pedestrian Collision Prediction for Personal Mobility Vehicles (EnvSys)
Taeckyung Lee (KAIST); Juseung Lee (Korea University); Ryuhaerang Choi, Seungjoo Lee, Hyeongheon Cha, Hyungjun Yoon, Song Min Kim (KAIST); Sangwook Bak (Samsung Electronics); Sung-Ju Lee (KAIST) -
Localization using Angle-of-Arrival (AoA) Triangulation (EnvSys)
Amod K. Agrawal (Amazon Lab) -
Adaptive Water pH Sensing in Variable Conditions Using Near Infrared Imaging and Machine Learning (EnvSys)
Fadoua Khmaissia, Nirupama Ravi (Nokia Bell Labs) -
SPATIUM: A Context-Aware Machine Learning Framework for Immersive Spatiotemporal Health Understanding (NetAISys)
Yang Liu, SiYoung Jang, Alessandro Montanari, Fahim Kawsar (Nokia Bell Labs) - 16:20 – 16:25: Closing Remarks
Call For Papers
The integration of AI and networking technologies is driving the development of intelligent and autonomous systems capable of making decisions and performing tasks in real-time. These systems are critical for a wide range of applications, including 5G and beyond networks, IoT, and edge computing. Furthermore, as we transition toward 6G networks, the potential of foundation models and federated learning to revolutionize networked AI systems is becoming increasingly evident. These advancements promise to enhance decision-making capabilities, optimize resource utilization, and enable more seamless collaboration across devices and infrastructures. However, designing, implementing, and deploying AI systems in networked environments presents a number of unique challenges. One of the main challenges is ensuring that AI systems can operate effectively in dynamic network environments with varying network conditions. Another requirement is balancing the trade-offs between the computational and communication requirements of AI systems in networked environments. Additionally, there is a growing emphasis on energy-efficient AI deployment to address sustainability concerns, alongside the need for new algorithms and protocols that can effectively utilize network resources while ensuring robustness and security. Finally, networked AI systems must handle the high-dimensionality and heterogeneity of the data they generate, requiring novel data management and analytics techniques tailored to real-world constraints.
The goal of this workshop is to bring together researchers and practitioners working on the design, implementation, and deployment of AI systems in networked environments. The workshop aims to provide a forum for discussing the latest research and development in this field, as well as for sharing practical experiences and case studies.
By bringing together experts from academia and industry, the workshop aims to foster collaboration and to promote the development of new ideas and research directions in this field. The workshop is co-located with ACM MobiSys 2025 and will be held as an in-person event in Anaheim (California, US). We invite submissions of original research papers, as well as papers describing practical experiences, case studies, and tutorials.
Topics of interest include, but are not limited to:
Distributed and collaborative AI algorithms and systems
Federated and collaborative learning for networked AI systems
On-device & multi-device AI for networked AI systems
IoT, Cyber-Physical Systems (CPS), edge and fog computing for networked AI systems
Edge AI centeric networked AI Systems
End-to-end integration, optimization, and demonstration of Edge AI systems in support of diverse applications
AI-enabled real time networking architectures and protocols for networked AI systems
Enhanced intelligent networking techniques (e.g., slicing, placement, management, control, reconfiguration, virtualisation) for 5G and beyond
Green network intelligence and sustainability for networked AI systems
Security and privacy for networked AI systems
Data management, sharing, and privacy for AI in networked AI systems
Theoretical and/or experimental results addressing the predictability of networked AI systems
Real-world deployment, diagnosis, evaluation and troubleshooting for networked AI systems
Real-time AI-augmented network monitoring and observability
Digital twin platforms enabled by networked AI systems
Generative AI & Agentic AI for networked AI systems
Language and Vision Models in and for networked AI systems
Emerging applications: autonomous systems, AR/VR, and immersive experiences
Submission Format
The 2nd International Workshop on Networked AI Systems will solicit of two different types of submissions:
Full paper submission. Solicited submissions include both full technical workshop papers and white position papers. Maximum length of such submissions is 6 pages (including references), and if accepted they will be published by ACM and appear in the ACM Digital Library.
Work-in-progress and demo submissions. Abstracts describing work-in-progress and demonstrations are also welcome and warmly encouraged. Submissions are limited to 2 pages (excluding references), and if accepted included in the program as a short oral presentation – but will only be published on the workshop website (not the ACM Digital Library). Deadlines for this informal track remain open even past the early registration deadline of MobiSys 2025; author notifications will be rolling (i.e. max of 4 days after submission) to enable early authors to take advantage of available discounts.
NetAISys follows a single-blind review process, but all submissions must be original work not under review at any other workshop, conference, or journal. Submissions must be submitted as a PDF in the double-column MobiSys format. Submissions can use this LaTex template that is known to comply with the formatting requirements. Authors remain responsible for checking that their resulting PDF meets our formatting and anonymity specifications.
Submission Important Dates
Submission Deadline: Saturday April 19th, 2025, AoE [FIRM]
Notification of Acceptenace: Friday April 30th, 2025, AoE
Camera-ready Papers Due: Tuesday May 6th, 2025, AoE [FIRM]
Workshop Date: Friday June 27, 2025
Submission System
Submit your work via HotCRP.
Workshop Venue
ACM MobiSys2025 and NetAISys '25 will take place at Hilton Anaheim. Additional information about the confernece venue can be found here.
Organizers
Steering Commitee
Technical Program Committee (TPC) Chairs
TPC
Contact and Acknowledgements
Homepage picture is an artwork created using OpenAI's DALL·E.