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 with critical `beyond thinking' traits and cognitive paradigms for X-AI and Trans-AI/DS; creative design, statistical, computational and analytical thinking mechanisms and patterns; and original architectures, frameworks, patterns and exceptions for AI/DS systems and products;

Significant real-world X-complexities, X-intelligences, X-informatics, X-modeling, and X-analytics in open complex data, behavior and systems across different disciplines, domains and areas, in particular, natural, physical, social, economic and technical spaces and domains for X-AI and Trans-AI/DS;

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 and behaviors grow 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, play critical roles in discovering X-intelligences and data and behavioral value and insights and in enabling smarter decisions and actions for enterprise innovation, productivity transformation and competitive strength upgrading. Our lab is recognized for its AIDS leadership in enterprise innovation, high standard and demonstrated socioeconomic impact in assisting major industry and government organizations in building