Data Science
Data scientists at NICO work to mine huge sources of data and build a deep understanding of the patterns and structures that lie beneath the numbers. Their research spans a vast number of information sources and demands enormous computer processing power, but their real work is to address the societal and scientific changes brought about by the exponential spike in access to big data and to discover meaningful and efficient ways of harnessing that data to improve the quality, not only the quantity, of information.
NICO launched the Data Science Initiative initiative to foster data science research across the University. Please visit the Data Science Initiative website to learn more.
Research Topics
Research topics in this area include the following:
- Computational Social Science
- Bio Informatics
- Data Visualization
Faculty
NICO faculty members working in this area:
- Luis Amaral
- Brian Uzzi
- Adam Pah
- Michelle Birkett
- Rosemary Braun
- Fabián Bustamante
- Noshir Contractor
- Steve Franconeri
- Konrad Kording
- Julio Ottino
- Edward (Ned) Smith
- Dashun Wang
- Uri Wilensky
- Hyejin Youn
- Florian Zettelmeyer
Publications
Read the following publications from NICO Faculty:
- Gerlach M, Farb B, Revelle W, Amaral, LAN (2018) A robust data-driven approach identifies four personality types across four large data sets. Nature Human Behavior, 7 September 2018.
- Pah AR, Hagan J, Jennings AL, Jain A, Albrecht K, Hockenberry AJ, Amaral LAN (2017) Economic insecurity and the rise in gun violence at US schools. Nature Human Behavior 1, 0040
- Mukherjee, S, Romero D, Jones B, Uzzi B (2017) The Nearly Universal Link Between the Age of Past Knowledge and Tomorrow’s Breakthroughs in Science and Technology. Science Advances, 19 Apr 2017: Vol. 3, no. 4, e1601315