7th International Workshop on Scalable Machine Learning for Health and Biomedical Data (SMLHBD)

In conjunction with IEEE BIBM 2026

Important Dates and Links

Follow this link to submit your paper: Submit Paper Here

Due date for full workshop papers submission: Sep 27^th, 2026
Notification of paper acceptance to authors: Oct 18^th, 2026
Camera-ready accepted papers: Nov 8^th, 2026
Workshop: Dec 1-4^th, 2026

Call for Papers
We are pleased to organize 7^th Workshop on Scalable Machine Learning for Health and Biomedical data (SMLHBD) being organized in conjunction with IEEE BIBM 2026. This workshop will not publish formal proceedings. Instead, selected paper will be invited to submit full-length journal paper at Oxford Bioinformatics Advances. Presentation in the workshop will require at least one author to register to the IEEE BIBM conference.

With the advent of high throughput biotechnology assays, we witness a surge in the complexity and size of biomedical data (i.e., omics, electronic health records, and imaging). Such complex and multimodal datasets have necessitated the development of advanced AI and machine learning models for effective analysis. In the last decade, several AI and machine learning-based methods resulted in scientific discoveries, practical systems biology solutions, and offered clinical diagnostic insights. Efficient and effective machine learning methods to integrate these datasets to decipher biological insights is a challenging problem. Furthermore, the availability of such large and heterogeneous datasets creates challenges to develop scalable machine learning methods. To this end, SMLHBD will introduce novel methods and techniques to harness these datasets effectively and efficiently.

The focus of SMLHBD (previously called HPC-BOD) is the latest machine learning/deep learning algorithms that integrate different biological data modalities to understand a key biological question such as predicting disease-associated genes, patient survival probability, and drug response. Particularly scalable machine learning methods to integrate large and complex biological datasets is the main topic of the workshop.

The workshop will feature submitted papers as well as invited papers and talks from reputed researchers in the field of machine learning, bioinformatics, and big data analytics. The selected papers in the previous versions of the workshop have appeared in PLOS One Special Collection, Frontiers in Bioinformatics and Oxford Bioinformatics Advances.

Areas of interest include (but not limited to):

Machine learning models for computational proteomics and proteogenomics (Big Omics data)
Network biology/Graph representation methods for multi-omics integration (Network Omics data)
Machine learning methods for computational Neuroinformatics and connectomes (Imaging data)
Machine learning models for Clinical Data, Diagnosis, and Prediction (multi modal data)

Submission guidelines
Please submit a full-length paper (up to 10 page IEEE 2-column format, reference pages counted in 10 pages through the online submission system. Papers should be formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines. See link for more info: https://www.ieee.org/conferences/publishing/templates.html

SMLHBD technical program committee will review all submissions based on their originality, technical soundness, significance, presentation, and relevance to the conference attendees.

All submissions will be peer-reviewed by members from the program committee using a double-blind review process. At the time of submission, the author list should be final. Any subsequent changes to the author list post-submission needs to be done with the approval of the program chairs. Acceptance of any of these would mean an oral presentation.

Organization Committee
Workshop Chairs:
Fahad Saeed, Knight Foundation School of Computing, and Information Sciences, Florida International University, Miami, FL, USA (Email: fsaeed@fiu.edu)
Serdar Bozdag, Dept. of Computer Science and Engineering, Dept. of Mathematics, University of North Texas, Denton, TX, USA (Email: serdar.bozdag@unt.edu)

Program Committee
TBD

Keynote Speaker(s)
TBA

Previous Workshops