Next-generation Data-Intensive Systems Group at USC
Led by Ibrahim Sabek, NEXDIG explores how machine learning, quantum computing, and large language models can make data systems faster, more scalable, more secure, and easier to reason about.
Our work bridges AI and data systems, aiming at intelligent, trustworthy, and high-performance solutions for next-generation applications.
News
All news →-
Shaolin's paper Intrinsic Geospatial Topological Reasoning in LLMs is accepted to 2025 SIGSPATIAL GeoGenAgent workshop!
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Bowen Wang is joining Amazon as a full-time software engineer after graduation. Congratulations Bowen!
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Qihan and Shaolin's paper LIMAO: A Framework for Lifelong Modular Learned Query Optimization is accepted to VLDB'25!
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Hanwen and Shashank's paper Conformal Prediction for Verifiable Learned Query Optimization is accepted to VLDB'25!
Recent papers
All papers →SEFRQO: A Self-Evolving Fine-Tuned RAG-Based Query Optimizer
SIGMOD, 2026
Intrinsic Geospatial Topological Reasoning in LLMs
GeoGenAgent@SIGSPATIAL, 2025
A Demonstration of Q2O: Quantum-Augmented Query Optimizer
Demo@VLDB, 2025
Lab Appearance
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NEXDIG @ SoCal DB Day 2025 -
SIGSPATIAL 2025! -
NEXDIG Amazon Interns - Summer 2025
Join us
We are looking for the NEXt passionate and talented students to DIG with us.