Undergraduate @ UChicago

Navaneeth K. Rajan

Computer Security, Privacy, & Machine Learning

About

Hello, world! I’m Nav, a fourth-year undergrad studying math and computer science at UChicago. Broadly, I’m interested in computer security: thinking about what technical interventions actually do in the context of real systems, adversaries, and users. Recently, I’ve been thinking a lot about LLMs: how more capable and efficient models change what attackers and defenders can do, and what new security issues emerge when AI systems interpret untrusted information and act with increasing autonomy.

Outside of research, I’m an editor for The Chicago Maroon’s data team, where I also write about tech, math, and privacy. Before coming to Chicago, I spent weekends volunteering at the American Museum of Natural History, which remains one of my favorite places.

My favorite photograph is the Pale Blue Dot, a 1990 photograph taken by Voyager 1 from six billion kilometers away. This website is inspired by a different picture of Earth that I’m also quite fond of: Earthrise, taken in 1968 by astronaut William Anders during the Apollo 8 mission. A few other things I’m fond of include glasswing butterflies, Stirling’s approximation, ulexite, Patagotitan mayorum, and competitive Pokémon.

If you want to talk, whether about computers, science communication, or cool bugs, shoot me an email!

Research

  • Grant Ho’s Research Group, University of Chicago

    Aug 2026 – Present

    Research assistant

    Analyzed 89,000+ forum questions about AWS, Google Cloud, and Azure/Entra to study how access-control problems evolved over time.

  • SAND Lab, University of Chicago

    Jun 2026 – Sep 2026

    Research assistant

    Studied whether black-box fine-tuning can stop frontier LLMs can disrupt alignment training. Built experimental pipelines on Vertex AI and found that safety behavior can degrade substantially even when the tuning data adds no new facts.

  • Amyoli Internet Research Lab (UChicago) and mLab (NYU)

    Mar 2022 – Dec 2025

    Research assistant

    Studied privacy and security in U.S. K–12 schools through interviews with district staff, qualitative coding, and measurement of EdTech links across 15,573 school and district websites.

Publications

  1. Uncovering Privacy and Security Challenges in K–12 Schools

    Jake Chanenson, Brandon Sloane, Navaneeth Rajan, Amy Morril, Jason Chee, Danny Yuxing Huang, Marshini Chetty

    ACM CHI 2023 · Best Paper Honorable Mention

  2. Running the School, Not Just the Classroom: K–12 Cybersecurity Responsibility and Supply-Chain Risk

    Jake Chanenson, Grace McGrath, Yimeng Jiang, Navaneeth Rajan, Noah Apthorpe, Yan Shvartzshnaider, Danny Yuxing Huang, Marshini Chetty

    Under review at ACM CHI 2027

  3. A Longitudinal Study of How Cloud Access-Control Problems Evolve and Respond to Platform Releases

    With Robert Liu, Kyle MacMillan, and Grant Ho

    In preparation

Education

  • University of Chicago

    Expected June 2027

    B.S. in Computer Science and Mathematics · GPA 4.00/4.00

Teaching

  • Algorithms (graduate)

    Fall 2026

    Grader · University of Chicago

  • Design & Analysis of Algorithms

    Spring 2025

    Head teaching assistant · New York University

  • Data Structures & Algorithms

    Fall 2024

    Teaching assistant · New York University

Awards

  • Josh Goldfaden Award

    2025

  • USA Computing Olympiad, Platinum Division

    2024

  • Best Paper Honorable Mention, ACM CHI

    2023

  • AIME Qualifier

    2022