Welcome
Mobile and wireless networks are rapidly evolving into highly heterogeneous ecosystems that span smartphones, wearables, autonomous devices, and dense edge infrastructures. At the same time, the deep integration of artificial intelligence into these systems has triggered an emerging AI compute–energy crisis, where the computational, thermal, and energy demands of modern models increasingly exceed the capabilities of resource-constrained mobile and edge hardware.
EMPOWER 2026 brings together the machine learning and mobile systems communities to address this challenge.
Aim & Scope
EMPOWER 2026 bridges the gap between the machine learning community and the mobile systems community. We explore the full lifecycle of mobile intelligence, from AI for Networks to Systems for AI, spanning algorithmic innovation to real-world deployment.
Keynote Speaker
Mohammad Malekzadeh
Senior Research Scientist & Tech Lead @ Nokia Bell Labs
Mohammad leads the Device Intelligence team in the Pervasive Systems department at Nokia Bell Labs, Cambridge (UK). His team develops machine learning solutions for private data and personal devices, aimed at advancing personalized healthcare applications through multimodal sensing and on-device machine learning.
His work prioritizes multi-modality, data and compute efficiency, individual privacy, and personalization. Notable open-source contributions include CLEF, PaPaGei, and Salted DNNs.
Previously, he was a Research Associate at Imperial College London, collaborating on Privacy-Preserving and Trustworthy Machine Learning. He earned his PhD in Computer Science at Queen Mary University of London, focusing on privacy-preserving personal data analytics for mobile and wearable devices.
Important Dates
| Event | Date |
|---|---|
| Submission Deadline | April 02, 2026 (AoE) |
| Notification of Acceptance | April 20, 2026 (AoE) |
| Camera-Ready Deadline | April 27, 2026 (AoE) |
| Workshop Date | June 25, 2026 |
(AoE = Anywhere on Earth)