MIT EECS Undergraduate Research and Innovation Scholar
Deep Learning for Finance
This research project is motivated by the idea that technology is disrupting and expanding the financial services industry. Underpinning this transformation is a blend of big data technologies intersecting with modeling and analytics, which provide new and innovative ways of investing. In this project, we will explore how deep learning can be used to model high-level abstractions from financial data. Deep learning is a branch of machine learning that is very compatible for market data, as it uses many layers of algorithms to successfully recognize increasingly complex features from unstructured data. Our goal is to develop and apply methods in deep learning that will deliver a powerful edge in investing by automatically recognizing and learning market trends in near real time.
I obtained some exposure to artificial intelligence and machine learning methodologies from previous summer internships and coursework, which got me very interested in exploring a long term research project in machine learning. Moreover, after interning with several financial institutions, I became eager to learn how these technologies could be applied to the financial services industry.