Contact: shengliu@nyu.edu

Bio: Sheng Liu was a Ph.D. student at the Center for Data Science, NYU, co-advised by Professor Carlos Fernandez-Granda, Professor Jonathan Niles-Weed, and Professor Narges Razavian. His research interests were in the general area of machine learning, particularly in robust deep learning with imperfect datasets (corrupted data, limited supervision, small dataset, etc.) as well as their medical applications such as Alzheimer’s automatic detection. He was a member of the Math and Data (MAD) group at NYU where he worked on inverse problems and optimization. Out of school, he loves tennis, scuba diving, surfing and most water sports.

Link to Sheng Liu’s Website