Ke Ni

Ke Ni

he/him

Applied Scientist at Amazon. The Joint CMU–Pitt Ph.D. Program in Computational Biology (CPCB). I work on multimodal models, LLMs, computer vision, and AI for science.

Graph-Dynamo: Learning stochastic cellular state transition dynamics from single-cell data

Published in BioRxiv, 2023

Co-authored paper.

Recommended citation: Yan Zhang, Xiaojie Qiu, Ke Ni, Jonathan Weissman, Ivet Bahar, Jianhua Xing. (2023). Graph-Dynamo: Learning stochastic cellular state transition dynamics from single-cell data. BioRxiv.