About

I am currently doing a PhD at EPFL in the LIONS lab with Prof. Volkan Cevher, where I am mostly focused on nonconvex-nonconcave minimax problems.

I have written on a variety of areas outside of this blog prior to the PhD:

• My Master thesis on Scalable Gaussian Processes for Economic Models.

• Bayesian Optimization using an Ensembled Deep Network for Global Optimization which explores the behavior of an ensembled variant of the architecture proposed by (Snoek et al 2015) on various Bayesian Optimization benchmark problems.

• Environmental sound classification using convolutional autoencoders with an custom built unpooling layer in keras.

• Bachelor on markov chain monte carlo and probabilistic programming.

• Compilation of a theorem prover written in Isabelle into Prolog using catamorphism in Haskell.

• A Process Calculus for Design and Modeling of Retro-synthesis (published and presented at EJC 2018 conference).

• A summary of dynamic epistemic logic and game theory.

I have had the joy of being a teaching assistant in the following courses:

• 02405 Probability theory (fall 2015)

• 02180 Introduction to artificial intelligence (Spring 2018)

• MICRO-455 Applied machine learning (spring 2020)

• EE-559 Deep learning (spring 2021)

• EE-618 Theory and methods for reinforcement Learning (spring 2022)

• EE-556 Mathematics of data: from theory to computation (fall 2020, fall 2021, fall 2022)