The 2023 ICML Workshop on Computational Biology

Each year, machine learning (ML) advances are successfully translated to develop systems we now use regularly, such as speech recognition platforms or translation software. The COVID-19 pandemic has highlighted the urgency for translating these advances to the domain of biomedicine. Biological data has unique properties (high dimensionality, degree of noise and variability), and therefore poses new challenges and opportunities for methods development. To facilitate progress toward long-term therapeutic strategies or basic biological discovery, it is critical to bring together practitioners at the intersection of computation, ML, and biology. The ICML Workshop on Computational Biology (WCB) will highlight how ML approaches can be tailored to making both translational and basic scientific discoveries with biological data, such as genetic sequences, cellular features or protein structures and imaging datasets, among others. This workshop thus aims to bring together interdisciplinary ML researchers working in areas such as computational genomics; neuroscience; metabolomics; proteomics; bioinformatics; cheminformatics; pathology; radiology; evolutionary biology; population genomics; phenomics; ecology, cancer biology; causality; representation learning and disentanglement to present recent advances and open questions to the machine learning community. We especially encourage interdisciplinary submissions that might not neatly fit into one of these categories.

Important Dates

Deadline for paper submissions: May 17th 19th 2023 (11:59 PM Pacific Time)
Reviewer deadline: June 9th 2023
Notification of acceptance: June 19th, 2023
Camera-ready deadline: July 21th, 2023
Workshop date: July 28th/29th, 2023

Call for submissions

We invite extended abstracts dealing with novel algorithms and computational approaches that are robust, scalable to high-dimensional data, and provide interpretable models of biological systems. These can be applications of ML methods or bioinformatics approaches to biological and biomedical data or novel approaches that enable new analyses. Papers will be presented in poster format and some will be selected for oral presentation (contributed and spotlight talks). Through invited talks and presentations by the participants, this workshop will bring together current advances in Computational Biology and set the stage for continuing interdisciplinary research discussions.

All novel Computational Biology approaches are of interest to the workshop.
In addition to the main track, we will hold a special track on “Explainability in Biological data” which will feature submissions focused on interpretable ML approaches and their applications for biological data. This will include inherently explainable and interpretable ML approaches, post-hoc interpretations of existing models, ways to evaluate the quality of explanations, limitations and failure modes of existing methods, and visualization strategies for analyzing models.
We welcome original abstracts on preliminary ideas and findings in the following format:

All submissions must use the ICML WCB template with this sty file. The submission does not need to be anonymized.
Submissions should be made through the Microsoft CMT submission portal. For more information about the submission process using CMT, please check this HOW-TO.
Accepted submissions will have the option of being published on the workshop website.For authors who do not wish their papers to be posted online or become citable, please mention this in the workshop submission.

This year, all presenters must attend in person.

This year we only do in-person poster presentation. The size for poster is recommended to be 24"w x 36"h or smaller than 36"w x 48"h.

Invited speakers

*Listed alphabetically

Su-In Lee

Paul G. Allen School of Computer Science
University of Washington, Seattle

David Van Valen

Assistant Professor
Department of Biology & Biomedical Engineering
California Institute of Technology

Bin Yu

Chancellor's Distinguished Professor
Department of Statistics & EECS
UC Berkeley

Diversity and Inclusion

ICML Workshop on Computational Biology aims to foster an inclusive and welcoming community. If you have any questions, comments, or concerns, please reach out to

We are also featuring other workshops that you might find helpful for diversity and inclusion. Queer in AI

Steering committee

Dana Pe’er (
Debora Marks (
Alexander Anderson (
Elham Azizi ( )
Sandhya Prabhakaran (
Abdoulaye Baniré Diallo ( )
Wesley Tansey (
Bianca Dumitrascu (
Maria Brbic (

Organizing committee

Yubin Xie:
Cassandra Burdziak:
Mafalda Dias:
Cameron Park:
Pascal Notin:
Joy Fan:
Ruben Weizman:
Lingting Shi:
Siyu He:
Yinuo Jin:


For workshop-related queries please contact:

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