Research Scientist, Google Brain
Hanie Sedghi is a research scientist at Google Brain. She works on large-scale machine learning, especially latent variable probabilistic models. Her approach is to bond theory and practice in machine learning by designing algorithms with theoretical guarantees that also work efficiently in practice and lead the state of the art.
Prior to joining Brain, she was a research scientist at Allen Institute for AI. Hanie received her PhD in Electrical Engineering from University of Southern California with a minor in Mathematics in 2015. She was also closely collaborating with Professor Anima Anandkumar at UC Irvine during her PhD studies. She received her M.Sc. and B.Sc. degrees from Sharif University of Technology, Tehran, Iran.
There are various challenges in learning with big data which resemble trying to find a needle in a haystack; e.g., signal scarcity, massive datasets and nonconvexity of the model. In this talk, I cover some of my recent works on efficient methods to tackle prominent AI problems using new perspectives. Guided knowledge completion for generics: […]