Data Science and Management

This research cluster includes the study and practice of data science and analytics, and extracting information and knowledge from data that can be used for medical, financial, business management scientific and engineering applications. These groups conduct research on bioinformatics, medical informatics, image processing, data mining, solar-terrestrial physics, transportation, financial management, business administration and management, life sciences and healthcare.

The cybersecurity group designs secure cyber systems and improves cyber information and communications technology (ICT). ICT is shaping many aspects of society as the economy evolves rapidly, providing access to unprecedented amounts of information, anytime and anywhere, from any type of device. By 2025, the number of global IoT (internet of Things) connections will increase from 12 billion in 2020 to more than 30 billion according to an estimate by IoT Analytics. Global spending on security hardware, software and services is estimated to almost reaching $175 billion by 2024, according to Statista. This cluster with a broader transdisciplinary scope with diverse applications also includes multidisciplinary research centers focused on mathematical sciences, transportation systems, additive manufacturing and wireless communications technology and industry and business management, as well as on the societal impacts of science and technology.

The Data Science and Management cluster spans over all other research clusters including Bioscience and Bioengineering, Environment and Sustainability, Material Science and Engineering and Robotics and Machine Intelligence for developing data driven approaches in almost all applications from healthcare information systems to industry automation, and to finance and business management.

NAE and NAS Grand Challenges and NSF Big Ideas within the scope of this cluster include “Secure Cyberspace”, “Advance Personalized Learning”, “Enhance Virtual Reality” “Restore and Improve Urban Infrastructure”, “Engineer the Tools of Scientific Discovery”, and “The Future of Work at the Human-Technology Frontier”, “Harnessing the Data Revolution”, “Growing Convergence Research” and “The Quantum Leap: Leading the Next Quantum Revolution”.