Overview

  • Data Orchestration for AI develops specialized data agents that orchestrate profiling, discovery, assemblage, integration, knowledge building, and visualization over cross-modal, multi-modal data assets (including tables, text, charts, and time series). It optimizes cost, end-to-end time, computing resources, and solution quality. The resulting workflows support downstream model training, question answering, insight generation, and analytical reasoning.
  • Autonomous AI Database System (AI4DB) advances autonomous, learning-enhanced database components—covering learned indexes, cardinality estimation, index advising, and query optimization—designed to work under realistic storage and workload constraints.
  • Civil Computing focuses on interactive visualized data exploration that brings big data back to a human scale for decision-making, spanning domains such as site selection, house seeking, and intelligent transport.
Last updated on Mar 4, 2026