Joy Arulraj

Joy Arulraj is an Associate Professor in the School of Computer Science within the College of Computing at Georgia Institute of Technology. His research focuses on data systems, machine learning, and database systems, with a particular emphasis on video analytics and adaptive query processing. He leads the Data Systems and Analytics Group and is developing the EVA AI-Relational Data System.

Dr. Arulraj's research interests span data systems, machine learning, database systems, video analytics, and adaptive query processing. His work centers on developing systems that efficiently process complex queries, particularly for video analytics and machine learning workloads. He has made significant contributions to GPU database systems, non-volatile memory database management, and adaptive query processing techniques. His research often bridges the gap between theoretical database principles and practical implementations for modern hardware architectures.

His recent publications show a strong trend toward video analytics systems, adaptive query processing for machine learning workloads, and GPU-accelerated database systems. The EVA system represents a major focus of his recent work, providing end-to-end exploratory video analytics capabilities. His research also addresses fundamental database concepts like buffer management, query optimization, and storage management, adapting these principles for modern hardware and application requirements.

Dr. Arulraj has advised numerous graduate students including Pramod Chunduri, Gaurav Tarkok Kakkar, Jiashen Cao, and Sayan Sinha. His graduated students have gone on to work at companies like ServiceNow, Meta Research, and the Korean Army. He actively teaches database system courses at Georgia Tech, including Database System Implementation (CS 4420/6422) and Advanced Database System Implementation (CS 4423/6423), where students build database systems from scratch using C++ and the BuzzDB framework.

He maintains an active research program with consistent publication output across top database and systems conferences. His work spans from theoretical database principles to practical system implementations, with a recent emphasis on video analytics, machine learning integration with database systems, and leveraging modern hardware like GPUs and non-volatile memory for database applications.