Alex N. Wang

I am a CS graduate student currently working with Richard Zemel at the University of Toronto. My undergraduate degree (B.A.Sc. in Engineering Science, robotics specialization) was also completed here.

I am still in the early stages of my research career, so I’m frequently interested by new topics that I come across – interesting models, generaliazation and statistical methods. So far, my work has been in vision, generative models, representation learning and learning in low-data regimes.

Looking forward, I hope to work on representation and transfer learning. I believe that many phenomena are interrelated, and that there is work to be done on using unlabelled, loosely-aligned data to solve complex problems. I’m interested in learning about statistical methods to characterize this and how we can learn structured models and representations, as well as relaxing the rigid problem-dataset pairing that is sometimes upheld.

When not trying to fix experiments, I like to work out, run and (try to) host dinner parties for my roommates and close friends.

Feel free to contact me at alexw [at]


Oct 21, 2021 Workshop paper accepted at Meta-Learn NeurIPS 2021.
May 8, 2021 First paper accepted at ICML 2021.