Prahaladh Chandrahasan

Hi, I am Prahaladh, a graduate student from the School of Computer Science (SCS), CMU. I am currently working as a machine learning engineer at the Language Technologies Institute, CMU,advised by Prof. Chenyan Xiong, where my primary role is to develop tools that aid in multimodal RAG and deep research agents research. I am also on the organizing committee of the NeurIPS competition: MMU-RAG: the Massive Multi-Modal User-Centric Retrieval-Augmented Generation Benchmark (Competition Website) where my primary role involves the system design and implementation of the live evaluation platform along with developing mechanisms for participant registration and leaderboard calculation.

I am also a privacy engineer in the Software and Societal Systems department, CMU, where I worked under Professors Norman Sadeh, Lorrie Cranor and Hana Habib on developing comprehensive case studies for applying the UsersFirst framework.

My primary expertise lies in bringing LLM / Agentic applications to production and developing tools that aid frontier AI research. Being an engineer with a passion for AI research, I help bridge the gap between research and production.

Before joining CMU, I worked as a Software Engineer at Bank of America in their APAC Payments team and also worked as a Software Engineer intern at the middleware engineering division of RedHat.

Outside work, I really love Carnatic music and here is my playlist.

I am actively looking for MLE/SWE/Privacy engineering roles starting Jan 2026. If you feel I would be a good fit to your team lets talk here : Calendly

Want to chat? Send me an email at prahald92 at gmail dot com or a message on LinkedIn!

CV  /  Google Scholar  /  Linkedin  /  Github /  X

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News

  • [Sept,2025] Started my Capstone Project with Meta on "Enhancing Transparency in AI Voice Assistants".

  • [Aug,2025] I am Ogranizing a NeurIPS competition "MMU-RAG: the Massive Multi-Modal User-Centric Retrieval-Augmented Generation Benchmark".(Competition Website)

  • [Jul,2025] Published a Pre-Print "Deep Research Comparator: A Platform For Fine-grained Humann Annotations of Deep Research Agents." (Arxiv)

  • [Jan,2025] Started as a Machine Learning Engineer building software tools that aid in Mutimodal RAG and agentic evaluation as a collaboration between CMU LTI and Amazon AGI.

  • [Jan,2025] Started my independent study in Privacy threat modelling under prof Norman Sadeh, Lorrie Cranor and Hana Habib. (Framework Website)

  • [Sept,2024] Began my master's in Privacy Engineering from CMU. (Linkedin Post)

  • [Sept,2023] Received the Arpit Jain Best Researcher Scholarship for our FL paper.(Website)

  • [Aug,2023] Filed the my first patent through Bank Of America. (Linkedin Post)

  • [Sept,2022] Joined Bank of America as Software Engineer in their APAC Payments team.

  • [Jul,2022] Published the Paper "Federated Learning for Colorectal Cancer Prediction." ( IEEE Link)

  • [Jan,2022] Published the paper "Motion Pattern-based Crowd Scene Classification Using Histogram of Angular Deviations of Trajectories." (Journal Link)

  • [Jan,2022] Joined RedHat as Software Engineer intern in their middleware engineering division.

  • [Oct,2021] Joined a stealth startup as Federated Learning Engineer intern.

  • [Mar,2021] Joined Cloudanix (YC,21) as a Software Engineer intern. (Cloudanix)

  • [Nov,2020] 2nd Place (National) in BRICS Future Skills Aerial Robotics competition, organised by WorldSkills Russia and the Moscow Regional Coordination Centre.

  • [Jun,2019 - Dec 2020] Won various aeromodelling and Drone racing competitions as a part of AeroMIT.

  • [Jun, 2019] Joined the Advanced Drone Research (now Autonomous Drone Research Subsystem) Subsystem in AeroMIT. (AeroMIT)

Research

Publications

[1] Prahaladh Chandrahasan, Jiahe Jin, Zhihan Zhang, Tevin Wang, Andy Tang, Lucy Mo, Morteza Ziyadi, Leonardo F.R. Ribeiro, Zimeng Qiu, Markus Dreyer, Akari Asai, Chenyan Xiong, "Deep Research Comparator: A Platform For Fine-grained Human Annotations of Deep Research Agents," arXiv preprint arXiv:2507.05495, Jul. 2025. (Link) ‌

[2]Yash Maurya, Prahaladh Chandrahasan, and Poornalatha G, "Federated Learning for Colorectal Cancer Prediction," 2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT), vol. abs 2110 9910, pp. 1–5, Oct. 2022, doi: https://doi.org/10.1109/gcat55367.2022.9972224. (Link) ‌

[3]A. K. Pai, Prahaladh Chandrahasan, U. Raghavendra, and A. K. Karunakar, "Motion pattern-based crowd scene classification using histogram of angular deviations of trajectories," The Visual Computer, vol. 39, no. 2, pp. 557–567, Jan. 2022, doi: https://doi.org/10.1007/s00371-021-02356-3. (Link) ‌

Projects

  • Membership Inference attacks on CIFAR 10 using the CIFAKE datset.( Github) ‌

    Online Presence

    Blog

    Checkout my Medium page to read some of my thoughts on technology and my experiences.

    Miscellaneous

    Made Deepseekv3 tell me how to make Cocaine!


    Thanks to Jon Barron for this template.

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