Machine Learning for Edge-Cloud Systems (ML4ECS)
CfP

The second edition of the Machine Learning for Edge-Cloud Systems (ML4ECS) workshop will be jointly organized by three Horizon Europe projects: CODECO, Edgeless, and MLSysOps. This collaborative event will highlight cutting-edge research and innovation in ML-based, autonomic end-to-end system management and application deployment and execution across the IoT-Edge-Cloud continuum—an area of growing importance due to the increasing complexity of such systems.

The workshop focuses on the research outcomes of the three organizing projects. Key topics include machine learning (ML) models to improve efficiency, reduce latency, and enhance performance across the edge-cloud continuum, integration with edge and cloud systems, optimization, security, and privacy-preserving decentralized learning.

The workshop will feature:

• Technical sessions showcasing the latest research outcomes and practical use cases from the three organizing projects,
• A keynote speech by a prominent expert in the field, and
• An interactive discussion panel addressing future challenges and opportunities in ML-driven optimizations of system functionality across IoT-Edge-Cloud environments.

The ML4ECS workshop aims to bridge academic and industrial perspectives, fostering dialogue and collaboration on deploying machine learning models to enable intelligent, adaptive, and efficient system and application management throughout the IoT-Edge-Cloud continuum.

9:30 – 10:45
HiPEAC Conference Welcome and Keynote

11:00 – 12:00
ML4ECS Keynote Speech

TBA

12:00 – 12:30
Coffee Break

12:30 – 14:00
EDGELESS

• 12:30 – 12:45: Manolis Marazakis (FORTH, Greece). Edge and Cloud Systems Based on Open Standards.
• 12:45 – 13:00: Ioannis Morianos (Dienekes, Greece). Hardware (FPGA) Accelerated Deep Learning for Edge Intrusion Detection Systems.
• 13:00 – 13:15: Claudio Cicconetti (CNR, Italy). Enabling the Stateful FaaS Agent Pattern in EDGELESS.
• 13:15 – 13:30: Jonathan Cacace (Eurecat, Spain) and Francisco Vicente Parra (Worldline, Spain). EDGELESS Videos: Internet of Robotic Things & The Function Repository.
• 13:30 – 13:45: Markus Sauer (Siemens, Germany). Beyond the Cloud: Industrializing Serverless with FaaS at the Edge.
• 13:45 – 14:00: Bruno Pereira (Ubiwhere, Portugal). EDGELESS: A use case on Smart City Analytics.

14:00 – 15:00
Lunch

15:00 – 16:30
CODECO

• 15:00 – 15:15: Rute C. Sofia, (fortiss, Germany). CODECO Federated Operation Framework.
• 15:15 – 15:30: Giorgios Papathanail (Intracom-Telecom). CODECO OSS Across Multi-Clusters (Demo).
• 15:30 – 15:45: Panagiotis Karamolegkos (University of Piraeus Research Center) and (Alejandro Espinosa, I2CAT). Privacy-Preserving Decentralised Learning (Demo).
• 15:45 – 16:00: George Koukis (ATHENA).CODEF Demo.
• 16:00 – 16:20: Panagiotis Karamolegkos (University of Piraeus Research Center). CODECO Use Cases and real-world applications.

16:30 – 17:00
Coffee Break

17:00 – 18:30
MLSysOps

• 17:00 – 17:05: Spyros Lalis (U Thessaly, Greece). MLSysOps Overview and Architecture.
• 17:05 – 17:20: Bruno Pereira (Ubiwhere, Portugal). Smart cities.
• 17:20 – 17:35: Phivos Papapanagiotakis, Giorgos Giannios (CNH, Greece). Enhancing Targeted Weed Spraying with Drone-Tractor Collaboration. ​
• 17:35 – 17:50: Theodoros Aslanidis, Dimitris Chatzopoulos (UCD, Ireland). AI Pipelines, MLOps, and AutoML in the Continuum.
• 17:50 – 18:05: Marcell Feher (Chocolate Cloud, Denmark). Traffic-Aware Object Storage via ML-Based Dynamic Policy Reconfiguration.
• 18:05 – 18:20: Alexandros Patras (U Thessaly, Greece). Optimizing ML Inference in FPGAs Using Reinforcement Learning.
• 18:20 – 18:35: Anastasios Nanos (NUBIS, Greece). Make your Object Detection Pipeline Smarter with MLSysOps and vAccel.

18:30
End of Workshop

• MLSysOps: Nikolaos Bellas (University of Thessaly, Greece), Raffaele Gravina (University of Calabria, Italy)
• EDGELESS: Claudio Cicconetti (CNR, Italy), Jesús Omaña Iglesias (Telefónica, Spain)
• CODECO: Rute C. SOFIA (fortiss GmbH, Germany)

Technical Program Committee:

TBA