Data Science Institute
About the data science institute
The Data Science Institute (DSI) at Temple University is at the pinnacle of the field of data science with its cutting-edge research and data science and analytics education. Focusing on a wide range of challenging methodological problems in data science, information systems, statistics, and other areas, the Data Science Institute works closely with private and public sectors to identify and address problems for which a solution would have a substantial impact in the world.
The Data Science Institute’s mission is to advance the linkage between the role of emerging technologies and data in the digital transformation of organizations, markets, government, the public and private sector, and society in general. The Data Science Institute aims to develop scientific inquiry and academic scholarship on data science and data analytics, serving as a bridge for translational science between academia, industry, and society.
what is data science?
Data science is an interdisciplinary field that incorporates the full functionalities of emerging technologies to encapsulate the transformational potential that large-scale data affords. By harnessing the power of big data, data science and data analytics enable the discovery and extraction of actionable knowledge from data to create digital strategy and infrastructure, transforming organizational operations and objectives. By adopting a digital vision, creating a digital culture, and implementing a robust technological infrastructure, organizations and societies will re-invent themselves with the incorporation of data science and technological advances.
why is data science important?
Data science has a tremendous impact across industries—from improving businesses’ financial performance to understanding how millions of genetic pairs interact to creating the digital transformation of politics and campaigning. Today, data science is entering a new era, where information technology and the proliferation of data is changing the way that business and organizations operate. By leveraging analytic capabilities, organizations can enhance processes, develop new products and services, and create more personalized interactions through the availability of large-scale data. With data science, the opportunity exists to use emerging technologies to extract valuable, complex, and varied information to develop strategies to maintain a competitive advantage.
The Data Science Institute focuses on a wide range of challenging methodological problems in data science, information systems, statistics, and other areas and works closely with collaborators at other universities and industry to identify and address problems for which a solution would have a substantial impact in the world.
Model-assisted design of experiments in the presence of network-correlated outcomes
EDOARDO M. AIROLDI
Exploiting social influence to magnify population-level behaviour change in maternal and child health: study protocol for a randomised controlled trial of network targeting algorithms in rural Honduras
EDOARDO M. AIROLDI
Call for Papers—Special Issue of Information Systems Research—Humans, Algorithms, and Augmented Intelligence: The Future of Work, Organizations, and Society
PAUL A. PAVLOU
Modeling Mobile User Actions for Purchase Recommendations using Deep Memory Networks
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Zoran Obradovic, PhD
College of Science and Technology
Professor, Laura H. Carnell Data Analytics
Director, Center for Data Analytics and Biomedical Informatics
Professor, Computer and Information Sciences Department
Zoran Obradovic is a L.H. Carnell Professor of Data Analytics at Temple University, Professor in the Department
of Computer and Information Sciences with a secondary appointment in Statistics, and is the Director of the Center for Data Analytics and Biomedical Informatics.
He is the executive editor at the journal on Statistical Analysis and Data Mining, which is the official publication of the American Statistical Association and is an editorial board member at eleven journals. He is the chair at the SIAM Activity Group on Data Mining and Analytics for 2014 and 2015 years, was co-chair for 2013 and 2014 SIAM International Conference on Data Mining and was the program or track chair at many data mining and biomedical informatics conferences.
His work is published in more than 300 articles and is cited more than 15,000 times (H-index 48). In year 2015 he become an elected member of Academia Europaea (the Academy of Europe).
Paul A. Pavlou
Fox School of Business
Professor, Milton F. Stauffer Information Technology and Strategy
Senior Associate Dean of Research, Doctoral Programs, and Strategic Initiatives
Chief Research Officer, Fox School of Business
Edoardo M. Airoldi
Fox School of Business
Professor, Millard E. Gladfelter Statistics and Data Science
Co-Director, Data Science Institute