FDS Talk: Yuning You (TAMU), “Generalizable Graph AI for Biomedicine”

decorative

Webcast

NOTE: This talk will be virtual only by Zoom.
Click the button below or go to: https://yale.zoom.us/j/96546710246

Abstract: AI is revolutionizing the world with unprecedented impacts rippling to the field of biomedicine. Yet, fundamental challenges remain to curb the AI power. In comparison to the fields of vision/language, AI models encounter the greater challenge of generalization in biomedical modeling, with the reasons concerning data: In terms of complexity, biomedical data in nature involve complicated structural features such as topology, geometry, or hierarchy, and moreover, such data are often restricted in quality, for instance, lacking sufficient supervised annotations due to the limitations of biotechnologies. Eyeing such a challenge, I will introduce my efforts on how to build more generalizable AI systems on structural data (e.g. graphs), on in-distribution and out-of-distribution data, and in discriminative and generative modeling. I will also demonstrate how they can be useful in the real-world biomedical problems, including predicting protein-ligand interactions and designing small-molecule drugs conditioning on properties.

NOTE: This talk will be virtual only by Zoom.
Click the box above or go to the following link: https://yale.zoom.us/j/96546710246


Yuning You (Texas A&M)

Speaker Bio: I am a fifth-year Ph.D. candidate (2019 – expected 2024) in the Department of Electrical and Computer Engineering at Texas A&M University, advised by Prof. Yang Shen and co-advised by Prof. Zhangyang Wang. I received my bachelor’s degree from Xi’an Jiaotong University. 

Website: https://yyou1996.github.io/