7th International Workshop on Scalable Machine Learning for Health and Biomedical Data (SMLHBD)
In conjunction with IEEE BIBM 2026
| Agenda for 7th International Workshop on Scalable Machine Learning for Health and Biomedical Data (SMLHBD 2026) Workshop Chairs: Serdar Bozdag and Fahad Saeed Tuesday, December 1, 2026 | 1:00–4:40 p.m. CT | IEEE BIBM 2026, Dallas, TX All contributed paper presentations are 20 minutes, including Q&A. Keynote title to be announced. |
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| Time | Title | Presenter/Author |
| 1:00–1:05 | Opening Remarks | Workshop Chairs |
| 1:05–1:45 | Keynote Address — Title TBA | Junzhou Huang, The University of Texas at Arlington |
| 1:45–2:05 | Semantic Keywords Expansion Retrieval Based on Entity Co-Occurrence Matrices Calculation for Brain-Computer Interface Topics and AI Entity Hit Rating Comparison | Tie Hua Zhou, Zehuan Liu, Chuanwen Lu, and Ling Wang |
| 2:05–2:25 | Stacking Pretrained CNNs for View Recognition in First-Trimester Fetal Echocardiography | Tayyaba Shahwar, Simon Koch, and Mutlu Mete |
| 2:25–2:45 | Does a Correct ATC3 Set Determine the Recorded Drug Names? | Juao Fan |
| 2:45–3:05 | Trustworthy Biomedical AI: Privacy-Aware Independent Evaluation through Zero-Knowledge-Inspired Representation Masking | Olcay Kursun and Simon Koch |
| 3:05–3:35 | Coffee Break | |
| 3:35–3:55 | Empirical Study on Matrix-Preconditioned Optimizers for Peptide-Spectrum Retrieval and Property Prediction for Mass-Spectrometry based Proteomics | Bilal Shabbir and Fahad Saeed |
| 3:55–4:15 | Task-Agnostic Representation Learning for Multimodal Longitudinal Electronic Health Records | Mohammad Al Olaimat, Shaika Chowdhury, Serdar Bozdag, and Alzheimer’s Disease Neuroimaging Initiative (ADNI) |
| 4:15–4:35 | Machine Learning-Based Multi-Class Classification of Various Neurodegenerative Diseases | Anika Anjum and John Michael Templeton |
| 4:35–4:40 | Closing Remarks | Workshop Chairs |
Important Dates and Links
Follow this link to submit your paper: Submit Paper Here
Due date for full workshop papers submission: Sep 27th, 2026 Oct. 18th, 2026 (AEO)
Notification of paper acceptance to authors: Nov 1st, 2026
Camera-ready accepted papers: TBD
Workshop: Dec 1-4th, 2026
Call for Papers
We are pleased to organize 7th 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
| First Name | Lastname | Affiliation |
| Zeeshan | Ahmed | Rutgers University |
| Mohammad | Al Olaimat | University of South Florida |
| Brittany | Baur | University of Michigan |
| Jianlin | Cheng | University of Missouri |
| Behnaz | Ghoraani | Florida Atlantic University |
| Sara | Gosline | Pacific Northwest National Laboratory |
| Xuan | Guo | University of North Texas |
| Nurit | Haspel | University of Massachusetts Boston |
| Yuede | Ji | University of Texas at Arlington |
| Mingon | Kang | University of Nevada, Las Vegas |
| Ziynet Nesibe | Kesimoglu | National Institutes of Health |
| Enrico | Maiorino | Harvard University |
| Ananda | Mondal | Florida International University |
| Sheida | Nabavi | University of Connecticut |
| Giri | Narasimhan | Florida International University |
| Chris | Poellabauer | Florida International University |
| Teresa | Przytycka | National Institutes of Health |
| Anna | Ritz | Reed College |
| Ashok | Srinivasan | University of West Florida |
| Yanzhao | Wu | Florida International University |
| Xiaotong | Yang | University of Michigan |
| Byung-Jun | Yoon | Texas A&M University |
| Wei | Zhang | University of Central Florida |
| Jie | Zheng | ShanghaiTech University |
Keynote Speaker(s)
TBA
Previous Workshops