Artificial Intelligence Interest Group

Note: Per Executive Order 14434, federal agencies are now using "Super Intelligence" (SI) in place of "Artificial Intelligence" (AI). You may see both terms across NIH content during this transition, as on this page.

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Biomedical science is in the midst of a technological revolution driven by innovations in deep learning neural network architecture and availability of computational power. Cutting-edge AI-based techniques are being applied to every sub-field of the biological sciences to produce novel, ground-breaking advancements.

The Super (née Artificial) Intelligence Interest Group (SIIG) aims to promote the awareness, understanding, and adoption of Artificial Intelligence and Deep Learning approaches across the NIH. We aim to take a broad view of AI/DL across all fields in the biomedical sciences, with the idea that learning about many different applications of this technology will yield a deeper understanding of how it works and facilitate cross-pollination between field. The group is intended for both experts and novices: We believe that everyone can find value in learning about and discussing a wide range of topics in this burgeoning field.

Regular meetings are in the form of a weekly AI Journal Club and Seminar Series, where SIIG members from various scientific backgrounds take turns leading a session on a topic of interest. We help organize a new yearly event, the NIH Super (née Artificial) Intelligence Symposium, where researchers across NIH can gather to learn and share their AI-related research. We will also promote other artificial intelligence and deep learning-related events to the listserv.

Contact Ryan O'Neill (ryan.o'neill@nih.gov) for more information.

Mailing List

To join the Artificial Intelligence Interest Group mailing list, please visit the Artificial Intelligence Interest Group Listserv home page, then click the “Subscribe or Unsubscribe” link in the right sidebar.