Contribute to Multi-Task Learning Book

Contribute to the edited book Multi-Task Learning in Science and Engineering, exploring the intersection of Deep Learning and Multi-Task Learning (MTL).

We invite researchers, academics, and practitioners to contribute chapters to the upcoming edited book Multi-Task Learning in Science and Engineering.

The book will explore the intersection of Deep Learning and Multi-Task Learning (MTL), offering insights into methods, techniques, and applications across various scientific and engineering domains.

The book will be structured into two volumes:

• Volume I: Science – Dedicated to foundational scientific applications of MTL in fields such as biology, chemistry, physics, and mathematics.
• Volume II: Engineering – Focused on the use of MTL in engineering and practical real-world applications, including biomedicine, robotics, automation, and materials design.

Submissions should be emailed to multitasklearning.book@gmail.com and should include the following editors’ email addresses in CC: pardalos@ufl.edu, giuseppe.nicosia@unict.it, and giulio.giaquinta7@gmail.com.

Don’t miss the opportunity to share your research and expertise. Submit your chapter by the given deadlines.

Tags: Multi-Task Learning, Science and Engineering, Deep Learning, Book Chapters, Research Contributions, Machine Learning, Artificial Intelligence, Academic Publishing