About me

Kevin Crowston

Distinguished Professor of Information Science and Associate Dean for Research,
Syracuse University School of Information Studies

Picture of Kevin

Kevin Crowston is a Distinguished Professor of Information Science at the Syracuse University School of Information Studies (aka the iSchool). He received his A.B. (1984) in Applied Mathematics (Computer Science) from Harvard University and a Ph.D. (1991) in Information Technologies from the Sloan School of Management, Massachusetts Institute of Technology. He currently serves as Associate Dean for Research.

His research examines new ways of organizing made possible by the use of information technology. He approaches this issue in several ways: empirical studies of coordination-intensive processes in human organizations (especially virtual organization); theoretical characterizations of coordination problems and alternative methods for managing them; and design and empirical evaluation of systems to support people working together. For more information, please consult his vitae and now quite out-of-date Fall 2005 research statement (both in PDF). Specific domains of interest include free/libre open source software development projects, citizen science projects and research data management.

He is a co-PI on an NSF INSPIRE project: "INSPIRE: Teaming Citizen Science with Machine Learning to Deepen LIGO's View of the Cosmos" (15-47880) and PI on an NSF CHS project: "Supporting Stigmergic Coordination” (16-18444). With colleagues, he heads a Research Coordination Network to develop a socio-technical perspective on work in the age of intelligent machines.

He is co-editor-in-chief of the journal Information, Technology and People and editor-in-chief of ACM Transactions on Social Computing.

Comm493: Analytics and Artificial Intelligence for Business

Type: Syllabus
Author: Tracy Jenkin
Year of Publishing: 2018
Keywords:

This course will introduce students to the development of software applications drawing on artificial intelligence techniques such as deep learning and machine learning.

Developing Skills to Work in the Age of Intelligent Machines: Pre-HICSS workshop

This half-day workshop aims to favor the skill's development among its participants to face the new work market and to collaborate with intelligent machines, and to create a transdisciplinary language for researching and to identify the need resources for working in the age of machines. We define intelligent machines as both material (e.g., robots) and immaterial (e.g., algorithms) computing technologies that can be characterized by autonomy, the ability to learn, and the ability to interact with other systems and with humans.

Impact of Social Science blog post about data reuse paper

Our PLoS One paper on was covered by the LSE's blog.

Round table on The Future of Work: Intelligent Machines, Automation, and Societal Impacts

There was a webcast round table on The Future of Work: Intelligent Machines, Automation, and Societal Impacts. A video of the webcast can be found .

Big Data Factories book has been published!

The book has been published by Springer. The book discusses how to use the increasing flood of data created as a byproduct of online behaviour as a source for research. I have a chapter entitled "".

Subscribe to Kevin Crowston RSS