Varun Nagaraj Rao

Varun Rao

PhD Candidate in Computer Science

Princeton University

Email: firstnamelastname@princeton.edu

About

I am a computer scientist and social computing researcher focused on the societal impacts of AI, particularly in labor and technology policy. My research covers explainable AI, multimodal machine learning, and the broader societal implications of AI.

Bio

Varun Rao, is a Ph.D. student in Computer Science at Princeton University advised by Prof. Andrés Monroy-Hernández, currently part of the Workers Algorithm Observatory (WAO). His research combines system building and empirical studies to understand and mitigate AI's impact on labor. Current projects include FairFare, examining black-box rideshare algorithms, and OpenDeli, exploring decentralized food delivery platforms. Earlier in his Ph.D., Varun's work exposed discrimination in job ad image selection on platforms like Facebook, revealing how this practice circumvents existing protections.

In his professional experience, Varun has interned at Microsoft Research (FATE), AWS and Apple, was a Google Policy Fellow at the Center for Democracy and Technology (CDT), and worked full time at Amazon.

Varun engages in tech policy outreach, influencing legislation on rideshare transparency such as Colorado's SB 24-75 . He is passionate about CS Education Research focusing on introductory algorithms courses and developing concept inventories. He has won a Google Policy Fellowship in 2025. His research has earned several recognitions, including the COLING 2020 Outstanding Paper Award, MIT/DARPA Graph Challenge Honorable Mention 2017, and the Hamsa Kartik Alumni Award for ranking first in his undergraduate class.

Affiliations at Princeton: HCI Group, Center for Information Technology Policy (CITP), Computer Science

News

  • [June
    2025]
    • Began my internship at Microsoft Research NYC Lab (FATE) mentored by the wonderful Solon Barocas, Su Lin Blodgett, Aylin Caliskan, and Agathe Balayn! A dream come true!

    • Thanks to the Center for Democracy and Technology (CDT) for publishing a blogpost about all my research!

  • [May
    2025]
  • [April
    2025]
    • Thank you to CITP for a Meet the Researcher blogpost about me!

  • [March
    2025]
    • Thank you to CITP (and especially Lydia Owens and Prof. Steven Kelts) for a wonderful blogpost about all my research!

  • [Feb
    2025]
    • New Preprint: FairFare: A Tool for Crowdsourcing Rideshare Worker Data to Empower Labor Organizers. Wonderful collaboration with co-authors from Princeton, Penn State, CU Boulder and UC Berkeley. I'm very proud of our nearly 2 years of research having a real impact on rideshare workers.

    • 4 system papers (CrowdLLM, GPTFootPrint, PolicyPulse, ConversAR) accepted to CHI Late Breaking Work (620/1888, 32.8% acceptance rate). All papers began as course projects I helped define and mentor while a TA as part of Prof. Andrés Monroy Hernández's "Introduction to HCI" course (COS 436, Fall 2024, Princeton University). Stay tuned for the papers!

    • Co-Presented our paper on a Dynamic Programming Concept Inventory at SIGCSE 2025, Pittsburgh, PA | Slides

    • Helped design an Agile Ethics Rideshare Roleplay with Prof. Steven Kelts for a Future of Work course (Prof. Andrés Monroy-Hernández, EGR 371, Spring 2025, Princeton University)
  • [Jan
    2025]
  • [Dec
    2024]
  • [Oct
    2024]
  • [September
    2024]
    • New paper: Rideshare Transparency: Translating Gig Worker Insights on AI Platform Design to Policy (to appear in CSCW 2025). [preprint]
      TLDR: We use a novel methodology of LLM-Driven Reddit Data Analysis and Interviews to Gather Gig Worker Insights on AI Platform Design and translate to a policy solution, proposing the first rideshare transparency report, similar to those for social media platforms and AI models.
    • Invited Talk at National Employment Law Project (NELP) on "Making Rideshare Governable". [slides]
    • I won a Graduate Fellowship of Social Data Science at Data Driven Social Science Initiative, Princeton University.
    • Submitted a response to EU Multi-stakeholder Consultation "Future-Proof AI Act: Trustworthy General-Purpose AI" - website, response.
  • [July
    2024]

    I am co-organizing a workshop on Worker Data Collectives at ACM CSCW 2024, Costa Rica.

    Apply here
  • [June
    2024]

    New Preprint, Blogpost and Policy Memo calling for Rideshare Transparency.

    Grateful to have worked with the CITP Tech Policy Clinic, Colorado Fiscal Institute and Towards Justice and helped influence bill language of Senate Bill 24-75 Transportation Network Company Transparency

    From Feb 2025, rideshare platforms in Colorado must disclose rider prices and rider wages at dropoff. A big transparency win!

  • [May
    2024]

    New preprint on using LLMs to translate unstructured online forum discussions to structured text resembling a survey.

    See QuaLLM.

    Presented this at the CHI LLM as Research Tools Workshop at CHI 2024

  • [May
    2024]

    I passed the Princeton Computer Science PhD General Exam!

    Committee: Andrés Monroy-Hernández, Peter Henderson, Arvind Narayanan

    Title: Societal Impacts of AI on Labor

    Presentation Assets: Slides, Reading List, Notes

Education

Princeton University

Doctor of Philosophy in Computer Science, Aug 2022 - Present

Research: Societal Impacts of AI on Labor

Selected Coursework: HCI (TA), Technology Policy and Law, Privacy, Ethics of Computing (TA), Responsible AI (TA)

Carnegie Mellon University

Master of Science in Electrical and Computer Engineering, Dec 2019

GPA: 3.96/4.0

Coursework: Computer Vision, Machine Learning (PhD), Convex Optimization, Security and Fairness in Deep Learning, Advanced Multimodal Machine Learning, Foundations of Cloud and ML Infrastructure

PES Institute of Technology

Bachelor of Engineering in Computer Science and Engineering, May 2018

GPA: 9.97/10 (Rank 1/132)

Delhi Public School Bangalore North

CBSE Class XII (Science), May 2014

Score: 96.6% (Rank 1)

Vidyashilp Academy

ICSE Class X, May 2012

Score: 98.8% (Rank 1)

Ongoing Projects

Workers Algorithm Observatory (WAO)

Understanding gig worker concerns and building tools to measure and mitigate AI and algorithmic systems harms; Focus on rideshare and delivery platforms. Contributed to FairFare Project.

Academic paper in progress

Project Website

OpenDeli

Designing a decentralized food delivery protocol and a reference implementation consisting of a frontend mobile app, backend and admin interface.

Academic paper in progress

Project Website

Publications

Societal Impacts of AI and Technology, HCI and Tech Policy:

Explainable AI and Multimodal Machine Learning

High Performance Computing

Computer Science Education

Teaching Experience

Professional Experience

Research Intern

Microsoft Research NYC Lab, FATE Group

June - Aug 2025

  • Designed a conceptual framework about AI use transparency artifacts and led qualitative research with AI policy stakeholders (government, industry and civil society) to understand how uncertainty about general purpose AI model use shapes regulation.

Google Policy Fellow

Center for Democracy and Technology (CDT)

Jan - May 2025

  • Design and evaluation of deterrence messaging strategies for NCII content in a search setting across diverse platforms and traditional search engines

Applied Scientist II Intern

Amazon Web Services, AWS Bedrock

May - Aug 2023

  • Showed that captioning, VQA and image classification can be modeled through a unified retrieval augmented encoder-decoder vision-language architecture, with no pretraining and additional trainable parameters; paper under review.
  • Experiments demonstrate the benefits on image captioning (+1 CIDEr on MSCOCO, +4 CIDEr on NoCaps) and VQA (+3 % accuracy on VQA v2) tasks compared to the non-retrieval baselines.

Applied Scientist II

Amazon.com Inc, Multimodal AI - Product Assurance, Risk and Security (PARS)

Feb 2020 - July 2021

  • Explainable multimodal text-in-image and classification models to help protect customers and build seller trust.
  • Invited Talk "Explainable Multimodal TextVQA Models" - Amazon Machine Learning Conference (AMLC) 2020
  • Outstanding Paper Award for "Misspelling Detection from Noisy Product Images" (top 2.5% - 16/644) at COLING 2020

Computer Vision Intern

Apple, Inc - Core Recognition Team

May - Aug 2019

  • Enhanced the accuracy of the OCR system by up to 28% and expanded support for handwritten text.

Software Development Intern

Akamai Technologies - Analytics Database Team

Feb - Apr 2018

  • Designed and implemented a release checklisting framework that reduced the time for checklisting in a sprint by up to 2 days.

Awards

Broader Outreach

Service

Designed Agile Ethics Roleplay on Rideshare Platforms

Organizing Committee Member

Reviewer / Program Committee Member

Community Outreach

Invited Talks

Workshops and Summer Schools

Mentorship

I am fortunate to work or have worked closely with many excellent undergrad students at Princeton: