YINS Seminar: Marinka Zitnik (Harvard)
YINS Seminar: “Infusing Structure and Knowledge into Biomedical AI Algorithms”
Speaker: Marinka Zitnik
Assistant Professor of Biomedical Informatics, Harvard Medical School
Zitnik Lab: https://zitniklab.hms.harvard.edu
Talk summary: Grand challenges in biology and medicine often lack annotated examples and require generalization to entirely new scenarios not seen during training. However, standard supervised learning is incredibly limited in scenarios, such as designing novel medicines, modeling emerging pathogens, and treating rare diseases. In this talk, I present our efforts to overcome these obstacles by infusing structure and knowledge into learning algorithms. First, I outline our subgraph neural networks that can disentangle distinct aspects of subgraph topology. I then present a general-purpose approach for few-shot learning on graphs. At the core is the notion of local subgraphs that transfer knowledge from one task to another, even when only a handful of labeled examples are available. This principle is theoretically justified as we show the evidence for predictions can be found in subgraphs surrounding the targets. I conclude with applications in drug development and precision medicine where the algorithmic predictions were validated in human cells and led to the discovery of a new class of drugs.
To participate:
Join from PC, Mac, Linux, iOS or Android: https://yale.zoom.us/j/95292478213
Or Telephone:203-432-9666 (2-ZOOM if on-campus) or 646 568 7788
Meeting ID: 952 9247 8213
International numbers available: https://yale.zoom.us/u/abCoS8cam8
Speaker bio: Marinka Zitnik is an Assistant Professor at Harvard University with appointments in the Department of Biomedical Informatics, Broad Institute of MIT and Harvard, and Harvard Data Science. Dr. Zitnik leads the Machine learning for Medicine and Science Lab, focusing on methods and applications for networked systems that require infusing structure and domain knowledge. This research won best paper and research awards from the International Society for Computational Biology, International Conference of Machine Learning, Bayer Early Excellence in Science Award, Amazon Faculty Research Award, Rising Star Award in EECS, and Next Generation Recognition in Biomedicine, being the only young scientist who received such recognition in both EECS and Biomedicine.
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