PhD Student, University of Toronto
Engineer II, Uber ATG
Email: firstname.lastname@example.org, email@example.com
Mengye Ren studied Engineering Science with focus on Electrical and Computer Engineering at the University of Toronto. He is now a PhD student in the machine learning group of the Department of Computer Science. His academic advisor is Prof. Richard Zemel. He also works part-time at Uber Advanced Technologies Group (ATG) Toronto, directed by Prof. Raquel Urtasun, doing research related to self-driving.
Deep learning, machine learning, computer vision
One paper got accepted to CVPR 2018!
Two papers got accepted to ICLR 2018!
Google Scholar [link]
Meta-Learning for Semi-Supervised Few-Shot Classification.
Mengye Ren, Eleni Triantafillou
*, Sachin Ravi
*, Jake Snell, Kevin
Swersky, Joshua B. Tenenbaum, Hugo Larochelle, Richard S. Zemel. ICLR 2018.
TensorFlow Forward AD: Forward-mode automatic differentiation for TensorFlow. [github]
PySched: Python-based light weight pipeline scheduler for local and slurm jobs. [github]
Deep Dashboard: Visualize training process in real time. [github]
Teaching assistant for
ECE 521: Inference Algorithms (2017 Winter)
CSC 401/2511: Natural Language Computing (2016 Winter)
CSC 411/2515: Introduction to Machine Learning (2015/2016 Fall)
CSC 190: Data Structure and Algorithm (Engineering Science) (2014 Winter)
SBNet: Sparse Blocks Network for Fast Inference. Borealis AI Lab. 2018/02. [slides]
Meta-Learning for Semi-Supervised Few-Shot Classification. Vector Institute. 2017/11. [slides]
Sequence-to-Sequence Deep Learning with Recurrent Attention. Queen's University. 2017/05. [slides]
Deep Dashboard Tutorial. University of Toronto. 2016/02. University of Guelph. 2016/03. [slides]
Exploring Data and Models for Image Question Answering. Lille, France. ICML 2015 Deep Learning Workshop. 2015/07. [slides]