GFM for Diagnostic Innovation

IEEE BIBM 2025 Workshop on Genomic Foundation Models for Diagnostic Innovation

Co-located with IEEE BIBM 2025, 15–18 December 2025, Wuhan, China

Workshop Description

Overview

The landscape of precision medicine and computational biology is undergoing a rapid transformation with the advent of Genomic Foundation Models (GFMs) — powerful AI systems inspired by large-scale models from natural language processing and computer vision. GFMs are designed to learn generalisable, high-resolution representations of genomic data, enabling intelligent and scalable solutions to some of the most pressing challenges in laboratory diagnostics and clinical decision-making.

About the Workshop

This international workshop, held as part of the IEEE BIBM 2025 Conference, is organised under the framework of the EU-funded GenDAI project (Genomic Applications for Laboratory Diagnostics supported by Artificial Intelligence). It aims to bring together a multidisciplinary community of researchers, clinicians, AI specialists, and industry stakeholders to advance the field of Genomic Foundation Models.

Participants will have the opportunity to engage with cutting-edge research, share practical insights, and identify future directions for integrating foundation models in clinical genomics. By facilitating meaningful dialogue between AI and bioinformatics communities, the workshop seeks to accelerate the translation of research breakthroughs into deployable, ethical, and trustworthy solutions in real-world healthcare contexts.

Key Themes and Topics

The workshop will feature presentations, panel discussions, and paper sessions covering (but not limited to) the following areas:

Design and pretraining of Genomic Foundation Models: Model architectures, tokenisation of genomic sequences, pretraining corpora, and scalability considerations
Fine-tuning strategies for diagnostic applications: Tailoring GFMs for disease classification, variant prioritisation, and patient stratification
Multi-omics integration using transformer-based architectures: Combining genomic, transcriptomic, epigenomic, and clinical data for holistic insights
Deployment of GFMs in laboratory and clinical environments: Case studies, workflow integration, and automation
Evaluation frameworks and benchmarking practices: Standardisation, reproducibility, and performance metrics
Federated learning and privacy-preserving model development: Ensuring secure and decentralised learning with sensitive biomedical data
Ethical, legal, and societal implications of GFMs: Transparency, fairness, and alignment with regulatory frameworks
Bias detection and mitigation strategies: Addressing data imbalance and equity in genomic datasets
Case studies from the GenDAI consortium and beyond

Who Should Attend?

This workshop welcomes:

AI and machine learning researchers working on biomedical applications
Bioinformaticians and computational biologists
Clinical genomics and laboratory medicine professionals
Data scientists from healthcare, pharma, and biotech industries
Regulators and policy experts interested in ethical AI in genomics
Graduate students and early-career researchers seeking exposure to state-of-the-art research

Format and Participation

The workshop will be held in a hybrid format — onsite in Wuhan, China, with full virtual participation options available. All sessions will be streamed live, with opportunities for remote presentations and interactive Q&A. Recordings will also be made available to registered participants post-event.

The organising team will ensure a seamless experience for all attendees, regardless of location, and encourage broad international engagement.

Important Dates

25 June 2025: Call for Workshop Papers issued
15 October 2025: Full paper submission deadline
10 November 2025: Notification of acceptance to authors
23 November 2025: Final camera-ready papers due
15–18 December 2025: Workshop held at IEEE BIBM 2025, Wuhan, China

Paper Submission Instructions

Submission URL:

Types of Papers: We invite long and short research papers. Long paper submissions are expected to describe substantial, original, completed, and unpublished work. Characteristics of short papers include a small, focused contribution; a work in progress; a negative result; an opinion piece; or an interesting application nugget.

Paper Length: As per IEEE BIBM 2025 policy, Long research papers may consist of up to 8 pages of content, plus unlimited references and appendices; final versions of long papers will be given one additional page of content (up to 9 pages) so that reviewers’ comments can be taken into account. Short research papers may consist of up to 4 pages of content, plus unlimited references; final versions of short papers will be given one additional page of content (up to 5 pages) so that reviewers’ comments can be considered.

Submission Formatting: Please follow the IEEE BIBM 2025 official LaTeX or Word templates

Blind Reviewing Policy: The workshop follows a blind reviewing policy. The authors should omit their names and affiliations from the paper and avoid self-references that reveal their identities. Papers that do not conform to these requirements will be rejected without review. Accepted papers will be published in the workshop proceedings.

Double submission policy: Parallel submission to other meetings or publications is possible but must be immediately notified to the workshop organizers.

For further information, please contact Haithem Afli (Haithem.Afli@mtu.ie)

Workshop Organizers

Programme Co-Chairs :

Dr Haithem Afli, ADAPT Centre, Munster Technological University, Ireland
Professor Huiru (Jane) Zheng, Ulster University, United Kingdom

Programme Committee Members :