Pramod Chunduri

Graduate Student, Georgia Tech Database Group.

avatar.jpg

I’m a PhD Candidate in Computer Science at Georgia Tech advised by Prof. Joy Arulraj, where I’m building efficient systems for AI applications, with a particular emphasis on video analytics and large language models (LLM).

My research focuses on accelerating query processing on AI platforms with a goal of achieving low latency and high accuracy. Through my research, I have developed advanced video analytics systems capable of answering complex queries involving multiple objects, actions, and motions in videos. Presently, I am optimizing Retrieval-Augmented Generation (RAG), a state-of-the-art LLM paradigm, to enhance question-answering efficiency.

In addition to my academic pursuits, I gained valuable industry experience as an Applied Scientist Intern at AWS AI Labs, where I built a state-of-the-art tabular QA system leveraging LLMs as task-specific verifiers. I also worked as a Research Scientist Intern at Adobe, where I utilized machine learning to devise personalized video editing tools that recommend optimal highlights and edits from raw footage.

news

Aug 19, 2024 I will be at VLDB’24 in Guangzhou, China, to present the demo of our SketchQL visual query interface for video moment querying!
Feb 29, 2024 SketchQL is accepted at SIGMOD’25! SketchQL introduces a novel sketch-based interface to query videos efficiently.
Feb 15, 2024 I will be interning at AWS AIRE as an Applied Scientist Intern in summer’24.
Dec 3, 2023 Actively seeking internship opportunities in efficient LLM and video analytics pipelines. Contact me!
Oct 28, 2023 Exciting news! Our GitHub repository exploring advanced LLM-based RAG pipelines has been trending on Hacker News!
Sep 30, 2023 Check out the stargazers-reloaded application to analyze your favorite GitHub communities using the power of LLMs.
Apr 18, 2023 Seiden is accepted at VLDB’23! Seiden builds an efficient query-agnostic index to accelerate video analytics.
Aug 15, 2022 Concluded a rewarding internship at Adobe Research on personalized video editing using ML.
Jun 20, 2022 Presented my Video Analytics paper Zeus on efficient action localization at SIGMOD’22.

selected publications

2025

  1. SIGMOD
    SketchQL: Video Moment Querying with a Visual Query Interface
    Renzhi Wu*, Pramod Chunduri*, Ali Payani, Xu Chu, Joy Arulraj, and Kexin Rong
    SIGMOD, 2025

2022

  1. SIGMOD
    Zeus: Efficiently localizing actions in videos using reinforcement learning
    Pramod Chunduri, Jaeho Bang, Yao Lu, and Joy Arulraj
    In SIGMOD, 2022