Our paper on artificial intelligence foundation for therapeutic science is published in Nature Chemical Biology.

New paper on self-supervised contrastive pre-training accepted at NeurIPS 2022. Project page. Thankful for this collaboration with the Lincoln National Laboratory.

Our paper on user-centric AI of drug repurposing received the Best Paper Honorable Mention Award at IEEE VIS 2022. Thankful for this collaboration with Gehlenborg Lab.

New preprint! We present the blueprint for graph-centric multimodal learning.

The recording of our tutorial on using graph AI to advance precision medicine is available. Tune into four hours of interactive lectures about state-of-the-art graph AI methods and applications in precision medicine.

New preprint! We introduce a resource for broad evaluation of the quality and reliability of GNN explanations, addressing challenges and providing solutions for GNN explainability. Project website.

Excited to organize the New Frontiers in Graph Learning workshop at NeurIPS.

We are excited to host the AI4Science meeting at NeurIPS discussing AI-driven scientific discovery, implementation and verification of AI in science, the influence AI has on the conduct of science, and more.

Check out our half-day tutorial with resources on methods and applications in graph representation learning for precision medicine.

Welcoming a research fellow Julia Balla and three Summer students, Nicholas Ho, Satvik Tripathi, and Isuru Herath.

Excited to share a preprint on self-supervised method for pre-training. Project website with evaluation on eight datasets, including electrodiagnostic testing, human daily activity recognition, and health state monitoring.

Excited to welcome George Dasoulas and Huan He, new postdocs joining us this Summer.

Congratulations to George Dasoulas, our incoming postdoctoral fellow, on being named the 2022 Wojcicki Troper HDSI Postdoctoral Fellow. We are delighted to welcome George in our group.

New preprint on building knowledge graphs to enable precision medicine applications.

We created PrimeKG, a precision medicine-oriented knowledge graph to support graph AI analyses in medicine.

Webster is on the cover of April issue of Cell Systems. Webster uses cell viability changes following gene perturbation to automatically learn cellular functions and pathways from data.

Dr. Zitnik will serve on the Science Working Group at NASA Space Biology.

Yasha won the National Defense Science and Engineering Graduate (NDSEG) Fellowship. Congratulations!

We are excited to be selected to organize the AI4Science meeting at ICML 2022. Stay tuned for details. http://www.ai4science.net/icml22

Excited to be organizing a session on Graph Algorithms at PSB 2023. Stay tuned for details.