About me
I am a 5th year doctoral candidate at the MIT Operations Research Center, advised by Prof. N. Trichakis. My research interests lie in Online Optimization and approximation algorithms, in Machine Learning coupled with Operations Management applications. I further work on bandit problems, online optimization and exploration-exploitation tradeoffs.
I earned my BS and MS from the Ecole Polytechnique in Applied Mathematics and Computer Science. I've had the pleasure to research at the Technion in Robust optimization.
Passionated about applying data-driven methods to solve complex decision-making problems, I look for challenges to get involved in high-impact projects. For instance, I was lucky to intern within the dispatch team at Uber Inc., optimizing real-time and large-scale systems.
Working Papers
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Demand Estimation and Personalized Assortments from Cross-Store Data for Beer Retailer
with Vivek Farias, Patricio Foncea and Nikolaos Trichakis -
Distribution Free Algorithms for Network Revenue Mangement
with Nikolaos Trichakis -
The Second-Price Knapsack Problem: Near-Optimal Real Time Bidding in Internet Advertisement
with Nicholas Renegar & Haihao Lu -
Efficient Estimation in Linear Bandits
with Nikolaos Trichakis -
Dynamic Approach to Elliciting Customer Preferences
with Nikolaos Trichakis
Projects
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Infection Modeling for COVID-19 Policy Alliance
within Covid Alliance -
Deep Reinforcement Learning for 2048
Class project - Dynamic Programming - MIT -
Constructing Uncertainty Sets from Data: an Unsupervised Learning Perspective
Class project - Robust Optimization - MIT -
Interval Data Classification with Mu-D Partial information and Geometric Interpretation of Robustness
with Aharon Ben-Tal and Tamir Hazan -
Most Relevant Path in a Network of Friends
Research project for ShorTouch -
Estimating Joint Spectral Radius and Applications
Research project for CMAP - Polytechnique -
Indoor Localization, Optimization of Supply Chain
Research project for Polestar - Finalist for PSC award at Polytechnique