Caredex enables Disaster Resilience in Aging Communities via a Secure Data Exchange.  It empowers organizations to readily assimilate, ingest, store and exchange information, both apriori and in real-time, with response agencies to protect and care for the elderly in extreme events. Using CareDEX, SHFs are able to share information about an individual’s changing health conditions, their personalized needs and identify those in need of specialized triage and critical care.  

TIPPERS is an active testbed at UCI that leverages WiFi connectivity events to enable real-time, privacy-preserving location-based services, such as occupancy tracking, space utilization, and safety applications, used by various communities. Powered by on PostgreSQL, it provides an open architecture with privacy-by-design to support diverse smart applications in areas like public safety, healthcare, and operational efficiency.

EnrichDB  is a novel data management technology that seamlessly integrates data enrichment through the entire data processing pipeline - from ingestion to event-based intermittent enrichment, and progressively during query processing. 

SmartRabbit extends existing database systems with specialized technology for interactive execution of SQL queries over large datasets, allowing applications to remain responsive while meeting the memory constraints of the system. 

LLM DB project is developing a variety of technologies  to seamlessly  integrate GenAI technologies into data processing. This includes mechanisms to support access control, perform data transformations such as data cleaning, and techniques to explore how data processing systems interface with and select amongst diverse LLM technologies including RAG and fine tuning. 

Focused on emergency response, RESCUE develops technology for collecting, managing, and analyzing large-scale data during disasters to improve situational awareness and decision-making in crisis scenarios.

This project targets cyber-physical resilience by creating methodologies and tools for secure, dependable, and privacy-respecting data management across interconnected devices.

The Quality-Aware Sensing Architecture (QUASAR) project addresses the challenges of managing high-rate sensor data in a scalable, efficient infrastructure that meets user-defined quality requirements. By integrating quality-aware mechanisms, QUASAR enables flexible, SQL-like access to data from numerous autonomous sensors, optimizing for bandwidth and energy limitations in sensor-driven applications.

I-SENSORIUM explores intelligent sensory technologies for capturing, processing, and analyzing environmental data to support innovative applications in real-world urban environments.

RADICLE focuses on decentralized data sharing and analytics infrastructures to foster open data ecosystems that respect privacy and data sovereignty.

This project focuses on developing a Fire Incident Command Board (FICB) to support real-time situational awareness for incident commanders through integrated sensor data and centralized systems like CAD and GIS. By enhancing decision-making, coordination, and communication across emergency response roles, the FICB prototype aims to improve firefighter safety under dynamic, high-risk conditions.

MARS focuses on enhancing multimedia information retrieval by incorporating relevance feedback mechanisms. The system allows users to interactively refine search results, improving the accuracy of multimedia searches.

SATWARE focuses on building a satellite-based data infrastructure to enable efficient data collection, integration, and analytics for remote or underserved regions, promoting connectivity and information access globally.