Call for Chapters - Edited Volume: “Multi-Task Learning in Engineering”
Ludovico Montalcini
Call for Chapters - Edited Volume: “Multi-Task Learning in Engineering”
Dear Colleagues,
We are pleased to invite researchers, scholars, and practitioners to contribute chapters to the forthcoming edited volume entitled “Multi-Task Learning in Engineering”.
This volume aims to provide a comprehensive overview of recent advances at the intersection of Deep Learning, Artificial Intelligence, Generative AI, and Multi-Task Learning (MTL), with particular emphasis on methodologies, theoretical developments, computational frameworks, and real-world engineering applications.
The book will specifically focus on the role of MTL in engineering and applied scientific contexts, including—but not limited to—biomedicine, robotics, intelligent automation, industrial systems, computational optimization, and materials design. Particular attention will be devoted to performance efficiency, scalable architectures, optimization strategies, and domain-specific adaptations of MTL approaches in practical environments.
We welcome contributions including:
* Original research chapters,
* Survey and review chapters,
* Industrial and application-oriented case studies.
Each chapter should be between 20 and 40 pages, including figures, tables, and references.
Deadlines:
1 August 2026: Submission of intention to contribute, including proposed topic(s) and a tentative chapter title
1 October 2026: Full chapter submission
1 December 2026: Notification of review results and editorial feedback
1 February 2027: Submission of revised final chapters
Submission Guidelines:
Chapter submissions should be sent to:
Authors are kindly requested to include the following editors in CC:
Editors
Panos Pardalos — University of Florida, USA
Giuseppe Nicosia — University of Catania, Italy
Giulio Giaquinta — University of Padova, Italy
We look forward to receiving your valuable contributions,
Panos Pardalos, Giuseppe Nicosia and Giulio Giaquinta.