Welcome to my page! I am a fifth-year PhD candidate at the MIT Operations Research Center, advised by Rahul Mazumder. My primary research interests are at the interface of optimization and data science. Currently, I am working on interpretable machine learning problems, in which models with a small number of comprehensible parameters are desired. These problems require discrete optimization and are difficult to scale using existing solvers. My work is focused on:
Developing scalable discrete optimization methods for interpretable machine learning
Leveraging interpretable machine learning models in business analytics applications
The applications I have been working on include recommender systems and insurance through internships and ongoing collaborations with Google AI and Liberty Mutual Insurance.
Before coming to MIT, I did my masters in Computer Science at the University of Illinois at Urbana-Champaign where I worked with ChengXiang Zhai on optimizing information recall in search engines. During my masters, I also had internships and collaborations with Amazon and Jump Trading. Before that, I obtained my undergraduate degree in Electrical and Computer Engineering from the American University of Beirut.
Best Student Paper Award, MIT Operations Research Center (2020)
Honorable Mention, INFORMS Computing Society (2020). Link.
Honorable Mention, Mixed Integer Programming Workshop (2019)