EMDL 2026: The Role of Mobile Computing in the Generative AI Era

Theme: System Foundations for Generative AI at the Edge

Since its inception in 2017, the EMDL workshop has tracked how breakthroughs in deep learning transformed the interpretation of sensor data for mobile systems like smartphones and wearable devices. In the early years, the community focused on making standard inference feasible, overcoming the severe demands that deep models exerted on local resources. By 2022, these methods had matured, successfully adapting CNN and RNN architectures to meet the stringent needs of mixed-reality and cyber-physical systems.

The Shift: From Discriminative to Generative: However, the landscape has shifted once again. We are witnessing a transition from Discriminative AI (classifying sensor data) to Generative AI (reasoning, explaining, and acting on context). While Generative AI (GenAI) brings unprecedented capabilities, it also presents a resource wall. Modern edge devices operate under constraints in memory bandwidth and energy availability that standard GenAI architectures—which are memory-bound and autoregressive—fundamentally exceed.

Scope and Goals: EMDL 2026 explores the intersection of Systems and Generative AI. We invite researchers to submit work that answers core technical questions for the GenAI era:

  1. Architecture: How should systems be architected to partition massive workloads between the cloud and the edge?
  2. Efficiency: What is required to integrate memory-bound GenAI into resource-constrained systems?
  3. Edge-Native Design: How do we define edge-native generative models designed explicitly for physical constraints?

See the full Call for Papers for topics of interest and more details.