Summary
Lixi Zhou is a Ph.D. research assistant at Arizona State University with a decade of engineering experience focused on integrating deep learning with database systems (AI4DB/DB4AI) to co-optimize model inference and data preprocessing inside relational databases. Her work has produced dramatic query speedups—up to 400× on realistic workloads—and appears in top venues like SIGMOD and VLDB, demonstrating both theoretical novelty and practical impact. She has industrial experience at IBM, where she accelerated LLM inference by designing parallel execution in the ONNX-MLIR stack, and has built privacy-preserving and testing tools at scale during other internships. Beyond performance wins, Lixi explores storage and lookup efficiency (deduplication and neural compression for key-value lookups), showing a rare blend of systems-level engineering and ML model-aware optimization. Based in the Greater Phoenix Area, she mentors junior researchers and bridges academia and industry to push ML-infused data systems toward production-ready performance.
10 years of coding experience
1 year of employment as a software developer
Computer Engineering, Computer Engineering at Arizona State University
Computer System Engineering - Software Design, Computer System Engineering - Software Design at Northeastern University
Bachelor of Engineering - BE, Measurement and Control Technology and Instruments, Bachelor of Engineering - BE, Measurement and Control Technology and Instruments at Central South University