I’m a senior computer science and math major at the University of Maryland, a 2021 Goldwater Scholar, and a 2022 CRA Outstanding Undergraduate Research finalist. I'm working with John Dickerson on introducing fairness methods to ride-pooling algorithms. I'm also working with Jordan Boyd-Graber on extending Entity Linking to improve down stream performance on entity linking. I am interested in working on problems involving machine learning, artificial intelligence, and mechanism design for applications such as fairness, healthcare, and criminal justice.
This summer (2021) I'm working as a research intern on the artificial intelligence team at MIT Lincoln Labs under Dr. Michael Yee. Last summer (2020), I worked as a Software Engineering Intern at Facebook in the Feed-Ranking team. I worked on full stack web application using React and Hack.
You can reach me at nraman1 [at] umd [dot] edu.
Improving Learning-to-Defer Algorithms Through Fine-Tuning
Naveen Raman, Michael Yee
NeurIPS WHMD Workshop 2021.
Data-Driven Methods for Balancing Fairness and Efficiency in Ride-Pooling.
Naveen Raman, Sanket Shah, John Dickerson
Machine Learning for Economics Policy at NeurIPS 2020.
Stress and Burnout in Open Source: Toward Finding, Understanding, and Mitigating Unhealthy Interactions.
Naveen Raman, Minxuan Cao, Yulia Tsvetkov, Christian Kaestner, Bogdan Vasilescu
ICSE 2020 - NIER .
Entity Linking for Quizbowl.
Naveen Raman, Pedro Rodriguez, Jordan Boyd-Graber
In my free time, I enjoy playing basketball, reading books, and watching movies.