I am a doctoral student in the ShaLab supervised by Fei Sha.
My research interest lies at the intersection of decision making and optimization.
Those interests have brought me to work on topics related meta-learning.

I will be spending the summer at Amazon AI in Pasadena, CA.

Decoupling Adaptation from Modeling with Meta-Optimizers - November 17, 2019

Our preprint on Decoupling Adaptation from Modeling with Meta-Optimizers for Meta-Learning is available on ArXiv. Open-source implementation in learn2learn coming soon!
[ArXiv, pdf]

Variance of Policy Gradient - November 17, 2019

Our preprint on Analyzing the variance of policy gradient estimators for LQR was accepted at the OptRL NeurIPS workshop.
[ArXiv, pdf]

Implicit Gradient Transport - September 5, 2019

Our paper on Reducing the variance in online optimization by transporting past gradients was accepted at NeurIPS as a spotlight contribution.
[ArXiv, pdf, website, code]

Open-Sourcing learn2learn - August 20, 2019

Our submission to the PyTorch Summer Hackathon won best in show! Check out the website to learn how to easily implement meta-learning algorithms with learn2learn.
[website, code]

East European Summer School - June 5, 2019

I will be attending the East-European Summer School this summer. Get in touch if you will too!
Edit: My poster got lucky and received the best theory poster award!