Joint work with Nathan Kallus.

arxiv: https://arxiv.org/abs/2211.06457

poster: https://neurips.cc/virtual/2022/poster/53915

(More details to follow!)

Talk I gave on contextual bandits in recommendation. Video will be uploaded in coming months. Here are the slides.

I am again on the organizing committee for the Advances in Approximate Bayesian Inference (AABI) workshop to appear at NIPS 2017. We will be asking for submissions soon.

Update: we had the workshop and there were many highlights. Please see the workshop website for the papers and talks. We uploaded all the talks to YouTube and I wrote a summary of the awesome panel at the end of the day.

My paper "An Empirical Bayes Approach to Optimizing Machine Learning Algorithms" has been accepted at NIPS 2017 for a spotlight presentation this December.

I will teach the Machine Learning course as an Adjunct Assistant Professor at Columbia University this Fall semester. Here is the dedicated course web page.

I recently taught at the Data Science Bootcamp, a 5 day intensive course at Columbia University that I co-created with Kriste Krstovski, Francisco Rodriguez Ruiz and Collabotory@Columbia.

Gave a talk about my workshop paper on hyperparameter averaging using Gaussian processes.

I am looking forward to many things in this job: continuing my research in machine learning with access to terabytes of new data and new problems; the potential for many new collaborations; working at a vibrant and young (still private) company where music is part of the DNA and where you have the chance to make an impact. I'll keep you posted on how it goes!

I am on the organizing committee for the Advances in Approximate Bayesian Inference (AABI) workshop at NIPS 2016. http://approximateinference.org.