Mengye Ren
 

Mengye Ren

Assistant Professor
New York University

Email: mengye@cs.nyu.edu

LinkedIn  GitHub  Google Scholar  CV 



Bio

Mengye Ren is an assistant professor of computer science and data science at New York University. He is also a visiting researcher at Google Brain Toronto working with Prof. Geoffrey Hinton. He received B.A.Sc. in Engineering Science (2015), and M.Sc. (2017) and Ph.D. (2021) in Computer Science from the University of Toronto, advised by Prof.  Richard Zemel and Prof. Raquel Urtasun. From 2017 to 2021, he was also a senior research scientist at Uber Advanced Technologies Group (ATG) and Waabi. His research focuses on making machine learning more natural and human-like, in order for AIs to continually learn, adapt, and reason in naturalistic environments.


Research

Areas: machine learning, computer vision, meta-learning, representation learning, few-shot learning, brain & cognitively inspired learning, robot learning, self-driving vehicles

My key research question is: how do we enable human-like, agent-based machine intelligence to continually learn, adapt, and reason in naturalistic environments? Towards this goal of building a more general and flexible AI, my research has centered on developing meta-learning and representation learning algorithms.

Some recent research highlights include:


Teaching


News


Group


Selected Papers

[Full List] [Google Scholar] [dblp]


Selected Talks

[Full List]