The Data Science Lab has been dedicated to fundamental research in AI, data science, shallow to deep learning, applied statistics and complex intelligent systems for two decades, mainly motivated by

AI thinking & data science thinking including scientific novel cognitive paradigms and thinking patterns for AI and data science; creative design, statistical, computational and analytical thinking and mechanisms; and analytics and learning design architectures, frameworks, patterns and exceptions;

Significant real-world X-complexities, X-intelligences, X-informatics, and X-analytics in open complex data, behavior and systems, identified in different domains and areas, in particular, public sector, business, finance, online and living societies, core industries, and socio-economic domains;

Fundamental theoretical gaps and innovation opportunities identified in both existing theoretical systems of statistics, data/intelligence sciences and computing, and to address new and significant theoretical and applied gaps, challenges and problems.

Enterprise data are growing increasingly bigger and bigger, more and more complex, and more and more valuable. AI, data science and intelligence science, including shallow to deep analytics, learning and modeling, have played critical roles in discovering the intelligence, value and insight and in recommending smarter decision-making actions for enterprise innovation, productivity transformation and competitive strength upgrading. Our team has been well known for its leadership in industry and corporate engagement, high standard and demonstrated impact in assisting major industry and government organizations in building