Several strong graduates are on the job market this year.
- Alekh Agarwal made the most scalable public learning algorithm as an intern two years ago. He has a deep and broad understanding of optimization and learning as well as the ability and will to make things happen programming-wise. I’ve been privileged to have Alekh visiting me in NY where he will be sorely missed.
- John Duchi created Adagrad which is a commonly helpful improvement over online gradient descent that is seeing wide adoption, including in Vowpal Wabbit. He has a similarly deep and broad understanding of optimization and learning with significant industry experience at Google. Alekh and John have often coauthored together.
- Stephane Ross visited me a year ago over the summer, implementing many new algorithms and working out the first scale free online update rule which is now the default in Vowpal Wabbit. Stephane is not on the market—Google robbed the cradle successfully I’m sure that he will do great things.
- Anna Choromanska visited me this summer, where we worked on extreme multiclass classification. She is very good at focusing on a problem and grinding it into submission both in theory and in practice—I can see why she wins awards for her work. Anna’s future in research is quite promising.
I also wanted to mention some postdoc openings in machine learning.
- In New York Leon Bottou, Miro Dudik, and I are looking for someone. The deadline is December 13.
- In New England, Sham Kakade and Adam Kalai are looking for someone. The deadline is December 13.
- Also in the New York area, Daniel Hsu and Tong Zhang may both be considering a postdoc with no particular deadline.
- In England, Peter Flach is looking for two postdocs on a health & machine learning project with a deadline of December 2. I consider machine learning for healthcare of critical importance in the future.