PSB Workshops

Pacific Symposium on Biocomputing

Big Island of Hawaii - January 3-7, 2026

PSB is offering four workshops during the meeting. These workshops were created to provide an opportunity for a gathering that will not be based on peer-reviewed papers included in the proceedings book. The workshops will consist of presentations by invited speakers. Abstract submissions for the workshops will be evaluated by the workshop co-chairs.

Each workshop has a chair who is responsible for organizing submissions. Please contact the specific workshop chair relevant to your interests for further information. Links on each of the titles below lead to more detailed calls for participation.

Advances of AI methods in single cell spatial omics

Organizers: Lana Garmire, Xiuwei Zhang, Joshua Levy

This workshop will bring together researchers developing and applying artificial intelligence to analyze spatially resolved single-cell data, including spatial transcriptomics, proteomics, and metabolomics. This rapidly evolving field presents unique computational challenges and opportunities for discovering spatially organized cellular interactions and disease mechanisms. The workshop will feature invited talks, contributed presentations, and discussions focused on cutting-edge methods and their biological applications.

Contact: Xiuwei Zhang
Email: iuwei.zhang at gatech.edu

AI for Health: Leveraging Artificial Intelligence to Revolutionize Healthcare

Organizers: Ruowang Li, Tiffani Bright, Brian D. Davison, Lifang He

Artificial Intelligence (AI) is poised to transform healthcare, offering groundbreaking capabilities in disease diagnosis, treatment, drug discovery, and patient care. By improving access to health services, reducing costs, and addressing workforce shortages, AI can play a pivotal role in tackling global health challenges. However, successfully integrating AI into healthcare requires careful consideration of regulatory frameworks, governance structures, data equity, and privacy protections. As interest in applying AI to healthcare grows, close collaboration between academia, clinical practitioners, and the healthcare industry becomes increasingly crucial to ensure that AI technologies are inclusive, equitable, and ethical. This workshop will bring together AI researchers, clinicians, and industry experts to foster dialogues and insights that contribute to responsible AI development. Focus areas will include AI for medical data analysis, clinical decision support systems, drug discovery, personalized medicine, and digital health platforms, all of which promise to reshape the future of health services.

Contact: Ruowang Li
Email: ruowang.li at cshs.org

Applications of AI & ML in Biomanufacturing of Cell and Gene Therapies

Organizers: Eric Neumann, Karen Weisinger, Tom Londo

This workshop will highlight how AI/ML technologies are beginning to be applied to biomanufacturing and bioengineering of cell and gene therapies (CGT). AI/ML have demonstrated their utility in biocomputing and biomedical research applications, and are poised to become central to design, scaling, and optimization of bioengineering processes such as CAR-T cells, iPSC, and biomolecule production. Invited speakers from academia and industry will speak of their experience in leveraging these new intelligent technologies.

Contact: Eric Neumann
Email: ekneumann at gmail.com

The Evolving Cyberinfrastructure at the National Institutes of Health to Support Data and AI in Biomedical Research

Organizers: Ojas A. Ramwala, Nick Weber, Sean D. Mooney

The rapidly transforming landscape of acquiring, sharing, and processing data has fueled the burgeoning volume of biomedical and clinical data. It is imperative to support biomedical computing investigators in utilizing this wealth of biologically meaningful information. Advancements in AI techniques, in conjunction with improved capabilities in implementing large-scale data processing pipelines, have led to the development of robust computational methods and algorithms to solve complex biological problems. However, there are many challenges associated with providing researchers with secured systems for accessing biological data and computational resources that must be addressed. The NIH has established a novel set of tools that provides for secured biomedical data sharing mechanisms, affordable access to cloud services, and secure data analytics workspaces to enable the biomedical research community to achieve the potential of the emergent data and AI ecosystem. This workshop aims to showcase the major challenges impeding researchers’ access to biomedical datasets and computing infrastructures and will cover the key components of the NIH’s cyberinfrastructure developed to advance data science and AI research for biomedical applications.

Contact: Ojas A. Ramwala
Email: ramwala at uw.edu

Trust, Reproducibility, and Progress: The Role of Assessment & Benchmarking in Computational Biology

Organizers: Gaia Andreoletti, Serghei Mangul, Mark Robinson, Predrag Radivojac, Steven E. Brenner

This workshop will explore the critical role of assessment and benchmarking in computational biology, emphasizing its importance in ensuring reproducibility, robustness, and innovation across disciplines such as genomics, structural biology, and biomedical data science. With the increasing reliance on AI and deep learning, the need for reliable assessment has never been greater. Participants will gain insights into best practices for designing assessment, selecting gold-standard datasets, and establishing meaningful performance metrics.

Contact: Gaia Andreoletti
Email: gaia.andreoletti at sagebase.org