Please see the CS department's webpage on admissions. There, you'll find information about all aspects of the application process (e.g., deadlines, your chances of being admitted), as well as information about the academic programs themselves.
If you are interested in working with me, you can mention this in your application (and also see the section below); this ensures that I (and others) will review your file. Unfortunately, I do not generally have time to reply to inquiries from prospective students.
I work on algorithmic statistics and machine learning, with emphases on
I am also generally interested in algorithms for unsupervised and semi-supervised machine learning.
Most of my research is theoretical in nature, although I am also very interested in some practical applications (e.g., in natural language processing, computational biology, information retrieval). So the actual work involved in my research is quite varied.
The mathematical background required for research in the above topics includes: algorithms, probability theory, calculus, linear algebra, and convex analysis. Solid programming skills are essential for good experimental work; fluency in C/C++ is helpful for scalable implementations, although prototyping can be done in higher-level environments such as MATLAB and Python.
If you are a current (or already admitted) Columbia student, please feel free to contact me via e-mail (or drop by my office) if you are interested in discussing a project with me.