View Proposal

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Proposer

Santiago Chumbe

Title

Improving the quality of scientific publications through AI agents

Goal

Develop AI agents capable of automating key editorial tasks to speed up submission and peer-review workflows

Description

AI agents have the potential to positively transform scientific publishing by acting as autonomous or semi-autonomous editorial assistants in the triaging and processing of manuscripts submitted for peer review. They could automate and streamline repetitive and time-consuming editorial tasks such as screening of new submissions, intelligent matching of reviewers with manuscripts, balancing the workload of editorial agents (authors, editors, reviewers, and administrative staff), "pre-flight" editorial checking, "first-pass" reviewing, key content summarising, reformulating reviewer comments to be professional and constructive, etc. This project will develop AI agents capable of automating these tasks, with the aim of significantly speeding up submission and peer-review workflows, increasing the productivity of editorial agents, and improving the quality of publications.

Resources

Background

Url

Difficulty Level

Moderate

Ethical Approval

InterfaceOnly

Number Of Students

1

Supervisor

Santiago Chumbe

Keywords

artificial intelligence, scientific publication, peer-review, ai agents

Degrees

Master of Science in Artificial Intelligence
Master of Science in Data Science
Master of Science in Information Technology (Business)