**Aaditya Ramdas **—
aramdas [@] cs [dot] cmu [.] edu

# Aaditya Ramdas

I just graduated with a PhD in Machine Learning and Statistics at Carnegie Mellon University. My thesis advisors were Larry Wasserman (Stats)
and Aarti Singh (ML).

I am now a postdoc working with Martin Wainwright and Michael Jordan at UC Berkeley (EECS and Statistics).

[Curriculum Vitae]

In Dec. 2014, I co-organized (with Suvrit Sra, Zaid Harchaoui, Alekh Agarwal, Miro Dudik, Martin Jaggi) a workshop on

In Nov. 2014, I was the lead organizer (with great help from MLD students) of a full-day

I also organized the CMU's weekly

I am now a postdoc working with Martin Wainwright and Michael Jordan at UC Berkeley (EECS and Statistics).

[Curriculum Vitae]

### Research Interests

I actively work in the following research areas, along with some representative publications. Click here for the full list, along with coauthors, bibliography, links to talks, etc.- Machine Learning (active learning)

An Analysis of Active Learning with Uniform Feature Noise (AISTATS'14)

Algorithmic Connections Between Active Learning and Stochastic Convex Optimization (ALT'13)

- Statistics (nonparametric hypothesis testing)

On the High Dimensional Power of a Linear-Time Two Sample Test under Mean-shift Alternatives (AISTATS'15)

Nonparametric Independence Testing for Small Sample Sizes (IJCAI'15)

- Optimization (for statistics/ML)

Fast & Flexible ADMM Algorithms for Trend Filtering (JCGS'15)

Margins, Kernels and Non-linear Smoothed Perceptrons (ICML'14)

- Optimization (general theory)

Convergence properties of the randomized extended Gauss-Seidel and Kaczmarz methods (in submission)

Towards A Deeper Geometric, Analytic and Algorithmic Understanding of Margins (in submission)

### Workshops, Seminars

In Jul. 2015, I co-organized (with Akshay Krishnamurthy, Nina Balcan and Aarti Singh) a workshop on**Advances in Active Learning: Bridging Theory and Practice**at ICML 2015.In Dec. 2014, I co-organized (with Suvrit Sra, Zaid Harchaoui, Alekh Agarwal, Miro Dudik, Martin Jaggi) a workshop on

**Optimization for Machine Learning**at NIPS 2014. [VIDEOS]In Nov. 2014, I was the lead organizer (with great help from MLD students) of a full-day

**Machine Learning Department Student Research Symposium**at CMU.I also organized the CMU's weekly

**Machine Learning Lunch Seminar**for over two years, and also a member of the**Statistical ML Theory Group**. Contact me if you want to speak at either!