During the fall and spring semester the Computational Social Science (CSS) and the Computational Sciences and Informatics (CSI) Programs holds weekly seminars where students, faculty and guest speakers present their latest research. These seminars are free and are open to the public.
For CSI, the seminars take place in Exploratory Hall, Room 3301 on Mondays from 4:30 p.m. to 5.40 pm.
For CSS, the seminars take place in Center for Social Complexity Suite which is located Research Hall, Level 3. The seminars start at 3:00 p.m. and normally last until 4:30 p.m. For a list of past CSS seminars click here.
In addition we also host ad hoc seminars relating to guest speakers and students dissertation proposals/defenses which don’t fall under our normal seminars.
If you would like to join the seminar mailing list please email Karen Underwood.
COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR
James Glasbrenner, PhD
George Mason University
Reproducible Research & Best Practices for Computational Science
Tuesday, October 10, 4:30-5:45
Exploratory Hall, Room 3301
ABSTRACT: Have you ever had one of the following thoughts while working on your research?
I knew what these variables meant when I wrote them last year.
Did I accidentally delete that email with the final version of our research paper attached?
Why does my collaborator’s program delete the last row and column of this array before entering the main loop?
If so, then you’re not alone, because “most researchers are never taught the equivalent of basic lab skills for research computing” . This situation persists even as the average scientific researcher devotes as much as 30% of their time developing and 40% of their time using scientific software . Underdeveloped skills in programming, project organization, and documentation can lead to general frustration, productivity losses, an increase in the risk that a researcher won’t be able to reproduce his or her work, and can even result in serious computational errors that invalidate a study’s general conclusions . At the same time, the number of scientific research groups that are integrating data science topics and methods into their programs is increasing at a rapid pace1 , further increasing the overall need to address this disparity. In response, a growing movement of researchers has emerged that are interested in tackling this problem, leading to the creation of organizations like the Software Carpentry Foundation , guidelines for reproducible research , and suggestions of “best practices” for scientific computing [1, 6, 7]. However, although there is more awareness about these potential solutions than in past years, these ideas are still not common knowledge. In this seminar, I will review the general background behind these ideas and what computational researchers can learn from other fields such as the software industry. Drawing on my own experience with implementing these ideas, I will provide examples of how you can integrate reproducible research ideas into your work using open source tools. Using the “best practices” suggestions as a guide, I will also show ways in which you can better organize your projects and some ways to make your code more readable, and then explain how this can help streamline scientific collaboration. Finally, I will close by reflecting on the role that automation can play in achieving these principles and goals.
 G. Wilson, J. Bryan, K. Cranston, J. Kitzes, L. Nederbragt, and T. K. Teal, PLoS Comput. Biol. 13, e1005510 (2017).
 J. E. Hannay, C. MacLeod, J. Singer, H. P. Langtangen, D. Pfahl, and G. Wilson, in Proc. 2009 31st Int. Conf. Softw. Eng. ICSE Workshops (2009) pp. 1–8.
 Z. Merali, Nature 467, 775 (2010).
 “Software Carpentry,” .
 R. D. Peng, Science 334, 1226 (2011).
 G. Wilson, D. A. Aruliah, C. T. Brown, N. P. C. Hong, M. Davis, R. T. Guy, S. H. D. Haddock, K. D. Huff, I. M. Mitchell, M. D. Plumbley, B. Waugh, E. P. White, and P. Wilson, PLoS Biol. 12, e1001745 (2014).
 V. Stodden and S. Miguez, J. Open Res. Softw. 2, e21 (2014). 1An arXiv query for all pre-prints with metadata containing the term ”data science” reveals exponential growth, with the number of submissions approximately doubling every year since 2007.
COMPUTATIONAL SOCIAL SCIENCE FRIDAY SEMINAR
William B. Rouse, Ph.D.
Alexander Crombie Humphreys Chair
School of Systems and Enterprises
Stevens Institute of Technology
Computational Social Science at Several Levels
Friday, December 8, 3:00 p.m.
Center for Social Complexity Suite
3rd Floor, Research Hall
ABSTRACT: Computational social science can enable understanding – and design – of a wide variety of phenomena at an enormous range of levels. This lecture will address processes, organizations, ecosystems, and society for phenomena associated with disease and medicine, health and well being, and technology adoption, particularly in automobiles. The process level is addressed in terms of scaling and optimization of medical innovations. The level of organizations is considered in the context of health provider corporations’ responses to the Affordable Care Act. The ecosystem level is discussed in addressing population health – integrated delivery of health, education, and social services – in the highly fragmented US ecosystem. The society level is considered in terms of the expected disruptive impacts of driverless cars on automotive, insurance, and finance industries. Approaches to and challenges of modeling at these differing levels are discussed.