Artificial Intelligence & Machine Learning Methods
Our team on GitHub
Our paper on artificial intelligence foundation for therapeutic science is published in Nature Chemical Biology.
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.
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.
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.
Yasha won the National Defense Science and Engineering Graduate (NDSEG) Fellowship. Congratulations!