Practical Adoption Challenges of ML for Systems

Workshop Overview

Using ML for improving computer systems has seen a significant amount of work both in academia and industry. With recent advances in Generative AI models, the potential of ML has been further expanded. However, deployed uses of such techniques remain rare. While many published works in this space focus on solving the underlying learning problems, we find that some of the most critical obstacles to deploying ML for Systems in practice come from non-ML systems aspects, such as feature stability, reliability, availability, ML integration into rollout processes, verification, safety guarantees, feedback loops introduced by learning, debuggability, and explainability.

During this workshop, we will have paper presentations and invited talks with the aim to foster collaboration between systems practitioners (production systems & ML) and academic researchers by providing a venue where real-world deployment challenges and related research work are discussed. We believe that starting this conversation between the academic and industrial research communities will facilitate the adoption of ML for Systems research in production systems, and will provide the academic community with access to new research problems that exist in real-world deployments but have received less attention in the academic community.

To this end, we invite position papers that explore new challenges and design spaces, short papers that describe completed or early-stage work, and abstracts that summarize works published in the past two years in the broad area of challenges associated with using machine learning in computer systems. A paper accepted to PACMI would not preclude its future publication at a major conference. Accepted papers will have the option to be included in ACM proceedings. For more details about submissions, please refer to the Call for Papers.

Important Dates (AoE)

Paper titles due: TBD
Paper submissions due: TBD
Notification to authors: TBD

Final version due: TBD

Previous Workshops

PACMI'25, PACMI'24, PACMI'23, PACMI'22

Contact Chairs (Yawen Wang and Kostis Kaffes)

Email: pacmi26-chairs@googlegroups.com