Skip to main content
Go to the home page of the European Commission (opens in new window)
English en
CORDIS - EU research results
CORDIS

AutoML Co-Designer: A Collaborative Framework for Accelerated AI Development

Project description

Bringing humans back into automated AI design

Building reliable AI systems requires complex choices, from selecting the right model to adjusting the many settings that influence how they learn. Automated machine learning (AutoML) tools can simplify this process by testing different models and tuning their hyperparameters. For example, such systems might compare different neural network architectures on a given dataset, such as credit scoring or customer satisfaction. With this in mind, the ERC-funded AutoML Co-Designer project seeks to make these design processes collaborative. Specifically, it will develop a prototype platform where developers can guide AutoML systems, contribute domain knowledge and interpret results. The goal is to accelerate AI development and ensure more robust applications.

Objective

The growth of the AI market depends on our ability to rapidly and efficiently develop robust AI applications, for which AI developers can be supported by Automated Machine Learning (AutoML), e.g. in model selection, neural network design, or hyperparameter settings. However, current AutoML systems are designed as rigid 'black boxes' and thus create a critical bottleneck. They sideline expert developers, preventing the integration of crucial domain knowledge. This inflexibility slows down development cycles, hinders innovation, and limits the creation of sophisticated, market-ready AI solutions for complex, high-value problems.

This project, AutoML Co-Designer, will deliver the proof of concept for a collaborative development paradigm that directly addresses this efficiency gap. Our objective is to validate a framework that transforms AutoML from a simple automation tool into a powerful interactive system between AutoML and AI developers.
We will engineer and validate a prototype platform with novel interactive interfaces. This platform will serve as the core of our proof of concept, enabling developers to inject domain knowledge, steer optimization towards market-critical goals like robustness and efficiency, and gain actionable insights through advanced explanations.

The successful validation of the AutoML Co-Designer framework will provide a clear business case for a new class of AI development tools. This PoC will establish a new framework for efficiency, demonstrating a faster path from idea to deployment. It will unlock new markets for specialized AI applications previously too complex or resource-intensive to build. This project will lay the groundwork for a commercially viable product that empowers development teams to innovate faster, creating a competitive advantage in the rapidly expanding AI economy.

Fields of science (EuroSciVoc)

CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.

You need to log in or register to use this function

Programme(s)

Multi-annual funding programmes that define the EU’s priorities for research and innovation.

Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-ERC-POC - HORIZON ERC Proof of Concept Grants

See all projects funded under this funding scheme

Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) ERC-2025-POC

See all projects funded under this call

Host institution

GOTTFRIED WILHELM LEIBNIZ UNIVERSITAET HANNOVER
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 150 000,00
Address
WELFENGARTEN 1
30167 Hannover
Germany

See on map

Region
Niedersachsen Hannover Region Hannover
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

No data

Beneficiaries (1)

My booklet 0 0