# Curriculum Vitae

The detailed PDF verison of my CV can be found here - **Update coming**

## Research Interests

I seek to solve theoretical machine learning problems using ideas from mathematical optimization, probability theory and statistics.

- Research Interests - Statistical Machine Learning, Large Scale Optimization, Interactive Learning, Algorithms.
- Other Learning Interests - Probability theory, Differential Geometry, Complexity Theory, Statistics.

# Education

**M.Sc**. in Computer Science, 2016 - 18

*Chennai Mathematical Institute***B.Sc.**in Mathematics and Computer Science, 2013 - 16

*Chennai Mathematical Institute*

# Work experience

- September 2019 - Present: Research Fellow
- Max Planck Institute for Software Systems, Saarbr$\ddot{u}$cken, Germany
- Adviser: Dr. Adish Singla
- Project: Teaching and Learning complexity of hypothesis classes, e.g., regions induced by intersections of Halfspaces and non-linear ERM learners e.g. kernel perceptrons.

- Summer 2017 : Research Intern
- IBM India Research Lab (Bengaluru, India)
- Supervisor: Dr. Karthik Sankaranarayanan
- Project: Tabular Data Summarization

- Summer 2015 : Research Intern
- Indian Institute of Technology (Kanpur, India)
- Adviser: Dr. Raghunath Tewari
- Project: Circuit Complexity: MCSP (minimum circuit size problem)

- Summer 2014 : Research Intern
- Indian Institute of Technology (Delhi, India)
- Adviser: Dr. Amitabha Tripathi
- Project: Graceful Labelling of Complete Graphs

# Talks

- Evaluating the Robustness of Neural Networks: An Extreme Value Theory Approach (BY CHO JUI HSIEH ET AL)
- SLIDES TALK (2018, Aalto University, Finland)
- Presentation given as part of the seminar course on Adversarial Deep Learning

- Manifold Learning and Tensor Decomposition
- SLIDES TALK (2018, CMI, India)
- Presentation given as part of the defense of the Masterâ€™s thesis at CMI.

- Tabular Data Summarization
- POSTER PRESENTATION (2017-18, IBM Research, India)
- Presentation given as part of the internship at IBM Research.

- The sum of d small-bias generators fools polynomials of degree d (BY E VIOLA)
- SLIDES TALK (2017, IIT Madras, India)
- Presentation given as part of the course Pseudorandomness at Indian Institute of Technology, Madras.

- Hierarchical Optimistic Optimization (HOO)
- BOARD TALK (2017, CMI, India)
- Presentation given as part of the seminar course Advanced Machine Learning. It covers the techniques from the paper $\chi$-armed bandits by Bubeck et al.

- Algebraic Independence and Blackbox Identity Testing (BY MALTE BEECKEN, JOHANNES MITTMANN, NITIN SAXENA)
- BOARD TALK (2016, CMI, India)
- Presentation given as part of the course Arithmetic Circuits.

# Teaching

Teaching Assistant: Machine Learning and Data mining, Fall 2017 (CMI)

Teaching Assistant: Discrete Mathematics, Spring 2016 (CMI)

# Professional Services

- Reviewer for International Conference on Artificial Intelligence and Statistics (AISTATSâ€™21)