My name is Behzad Tabibian, I am a PhD student at Max Planck Institute, Emperical inference department with Prof. Dr. Bernhard Schölkopf and Dr. Manuel Gomez Rodriguez. I studied Computer Science at Edinburgh University and graduated in June of 2012 and completed my masters at university of Pittsburgh. My main research interests are Machine Learning, Statistics and Inference. I primarily apply Machine Learning on (Social) Networks problems.

Previously I was interested in robotics and software engineering. In my free time I enjoy talking about books, particularly history, political philosophy and philosophy of science.

Recent News

Design and Analysis of the NIPS 2016 Review Process

In this report, we analyze several aspects of the data collected during the review process, including an experiment investigating the efficacy of collecting ordinal rankings from reviewers (vs. usual scores aka cardinal rankings). Our goal is to check the soundness of the review process we implemented and, in going so, provide insights that may be useful in the design of the review process of subsequent conferences. We introduce a number of metrics that could be used for monitoring improvements when new ideas are introduced.

2017 Machine Learning Summer School

I am part of organization team for MLSS2017. The MLSS is a renowned venue for graduate students, researchers, and professionals. It offers an opportunity to learn about fundamental and advanced aspects of machine learning, data analysis and inference, from intellectual leaders of the field.

Recent Posts

Tutorial on Latent Dirichlet Allocation

I gave a tutorial on Latent Dirichlet Allocation as part of PhD tutorials at our department. Here you can find the contents I covered in this talk.