Aaditya Ramdas — aramdas [@] cs [dot] cmu [.] edu
8223 Gates (CMU), Pittsburgh

4th Year Joint PhD Student, Machine Learning and Statistics
School of Computer Science , Carnegie Mellon University

My research focuses on revisiting classical problems in statistics and machine learning (like classification, regression, hypothesis testing) with modern viewpoints and tools like nonparametric methods, active learning, randomized algorithms, kernel methods, and stochastic optimization.

I got a B.Tech degree in Computer Science and Engineering from IIT Bombay. I spent a year doing high frequency algorithmic trading at Tower Research Capital, and have done internships at Deutsche Bank (Bombay), INRIA (Sophia-Antipolis), LaBRI (Bordeaux) and Microsoft Research (Cambridge).

My advisors are Larry Wasserman (Stats) and Aarti Singh (ML). Other direct collaborators include CMU professors like Ryan Tibshirani, Barnabas Poczos, Javier Pena, Cosma Shalizi, Rebecca Steorts, and CMU students like Leila Wehbe and Sashank Reddi.

My thesis topic is "Revisiting Classical Statistical Learning with Modern Techniques" and my committee members are Larry Wasserman, Aarti Singh, Ryan Tibshirani, Michael Jordan (UC Berkeley) and Arthur Gretton (UC London). I hope to defend by summer 2015.