INSPIRE: Teaming Citizen Science with Machine Learning to Deepen LIGO's View of the Cosmos

This newly funded project (INSPIRE 15-47880) will develop a citizen science system to support the Advanced Laser Interferometer Gravitational wave Observatory (aLIGO), the most complicated experiment ever undertaken in gravitational physics. Before the end of this decade it will open up the window of gravitational wave observations on the Universe. However, the high detector sensitivity needed for astrophysical discoveries makes aLIGO very susceptible to noncosmic artifacts and noise that must be identified and separated from cosmic signals.

Focusing attention to improve the performance of citizen science systems: Beautiful images and perceptive observers

This SOCS project (NSF 12-11071) examines strategies for dealing with the flood of digital data that confronts researchers. New techniques, tools and strategies for dealing with massive data sets, whether they consist of vast numbers of base-pair sequences or terabytes of data from all-sky astronomical surveys, present an opportunity to establish a 'fourth paradigm' of scientific discovery, but the task is not easy. In many areas of research, the relentless growth of data sets has led to the adoption of increasingly automated and unsupervised methods of classification.

SoCS: Socially intelligent computing to support citizen science

The SOCS project (NSF grant 09-68470) investigates the capabilities and potential of social computational systems (SoCS) in the context of citizen science. Citizen science projects are a form of social-computational system. Whether it be volunteers playing a role in massive, distributed sensing networks exploring the migration of birds, or applying their unique human perceptual skills to searching the skies, human motivation and performance is fundamental to system performance. However, undertaking science through a social computational system brings unique challenges.

Theory and Design of Virtual Organizations for Citizen Science

This completed project was a two-phase theory-based study of virtual organizations that enable massive virtual collaboration in scientific research. The virtual organizations studied have a core of scientists and project leaders coordinating the work of a larger number of volunteer contributors, a format called citizen science. The project was directed at advancing the understanding of what constitutes effective citizen science virtual organizations and under what conditions citizen science virtual organizations can enable and enhance scientific and education production and innovation.

Keynote address at the Chais Conference 2016

On 16 February 2016, I gave a keynote address at the Chais Conference 2016 with the title "Citizen Science: Learning to effectively contribute in virtual organizations". A recording of the talk is available on YouTube if you don't see if below.

NSF INSPIRE project funded

An NSF INSPIRE project on which I'm a co-PI (along with Carsten Østerlund) was just funded! The project award 15-47880, titled "INSPIRE: Teaming Citizen Science with Machine Learning to Deepen LIGO's View of the Cosmos". The project, joint with Northwestern University, Cal State Fullerton and the Adler Planetarium, will develop a novel citizen science project to classify glitches from the LIGO gravitational wave detector. You can read more here.

Pages

Subscribe to Citizen Science Research at Syracuse RSS