Calendar

COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR

Shane Frasier, Ph.D.
Department of Homeland Security

Data Science and Cybersecurity at the Department of Homeland Security

Monday, TBA,  4:30-5:45
Exploratory Hall, Room 3301

ABSTRACT: Among its many responsibilities, the Department of Homeland Security works to improve the security of the computer networks of the federal government and our nation’s critical infrastructure.  This will be a discussion of some of the ways in which that is done, and some of the ways in which data science can contribute to that goal.

COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR

Jason M. Kinser, D.Sc.,
Chair Computational & Data Sciences
George Mason University

Image Operators – A World Premiere

Monday, November 6,  4:30-5:45
Exploratory Hall, Room 3301

ABSTRACT: The onslaught of digital detectors has created the ability to capture massive amounts of image data. Analysis techniques have been maturing for decades, but this new flood of image data will tax the foundations of information dissemination. Published descriptions of the image processes often consume much more real estate than does the scripts required to execute the processes. Furthermore, many published descriptions are imprecise. This talk will preview a new mathematical language solely dedicated to the fields of image processing and analysis. This language is coincident with implementations in Python and Matlab, thus there is a one-to-one correspondence between mathematical description and computer execution. This talk will present several examples and culminate with an interactive analysis of image processing protocols.

COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR

Benjamin J. Radford, PhD
Principal Data Scientist
Sotera Defense Solutions

Clustering Techniques for Unsupervised Machine Learning

Monday, November  13, 4:30-5:45
Exploratory Hall, Room 3301

Abstract: Cluster analysis represents a broad class of unsupervised algorithms that are applicable to a variety of data science problems. An overview of some clustering models is provided and example use cases for clustering are discussed. Multivariate Gaussian mixture models are then discussed in detail and estimation techniques are outlined. K-selection is also discussed in the context of Gaussian mixture models. The talk concludes with a short discussion about how clustering techniques might be used in the context of cybersecurity.

Dr. Radford is a Principal Data Scientist at Sotera Defense Solutions where he works on data-driven cybersecurity research programs for the Department of Defense. He received his Ph.D. in political science from Duke University in 2016. His research interests include political methodology, security and political conflict, the political implications of cyberspace, and automated event data coding. Dr. Radford’s dissertation demonstrated the semi-automated population of dictionaries for event-coding in novel domains. He is also an avid guitarist.

radford_slides_20171108

There will be no Computational Research and Applications Seminar on Monday, November 20.

Happy Thanksgiving!

COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR

Juan R. Cebral, Ph.D.
Bioengineering & Mechanical Engineering Departments
Volgenau School of Engineering
George Mason University

Hemodynamics of Cerebral Aneurysms: Helping Diagnosis and Treatment

Monday, November 27,  4:30-5:45
Exploratory Hall, Room 3301

ABSTRACT: We use image-based computational fluid dynamics to model the blood flow in human cerebral arteries and aneurysms with three specific goals: 1) identify hemodynamic conditions that predispose aneurysms for instability and rupture and thus help with more precise selection of patients at high risk, 2) advance the understanding of the disease mechanisms and enable drug based therapies targeting specific pathways of wall degeneration and weakening, and 3) evaluation of devices and procedures to improve treatment planning and long term outcomes. In this talk I will summarize some our recent progress and results along these three lines of research, and discuss future directions.

COMPUTATIONAL RESEARCH AND APPLICATIONS SEMINAR

James Glasbrenner, PhD
Assistant Professor
George Mason University

Reproducible Research & Best Practices for Computational Science

Monday, December 4, 4:30-5:45
Exploratory Hall, Room 3301

ABSTRACT:  Have you ever had one of the following thoughts while working on your research?

• I can’t remember where I put that data file.
• 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” ^[1]. 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 ^[2]. 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 ^[3]. 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 ^[4], guidelines for reproducible research [5], 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.

References
[1] G. Wilson, J. Bryan, K. Cranston, J. Kitzes, L. Nederbragt, and T. K. Teal, PLoS Comput. Biol. 13, e1005510 (2017).
[2] 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.
[3] Z. Merali, Nature 467, 775 (2010).
[4] “Software Carpentry,” .
[5] R. D. Peng, Science 334, 1226 (2011).
[6] 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).
[7] 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.

Faisal Hasan, General Manager, Data and Public Policy, CARFAX

Srinidhi Melkote, Head of Business Analytics CARFAX

COLLOQUIUM ON COMPUTATIONAL SCIENCES AND INFORMATICS

Leveling the Playing Field:  Information Asymmetry in the Used Vehicle Buying Process

Monday, January 29, 4:30-5:45
Exploratory Hall, Room 3301

Abstract

In 1970, Economist and Nobel Prize winner (2001) George Akerlof published a study: “The Market for “Lemons”: Quality Uncertainty and the Market Mechanism” (The Quarterly Journal of Economics, Vol. 84, No. 3. (Aug., 1970), pp. 488-500).   In the study, Akerlof attempts to show where, in a market where as seller of a product has more data/information than the buyer of the product, about the product’s quality, will potentially result in “an adverse selection of low-quality products.”   In no place is Akerlof’s theory more represented than in the used vehicle market, where buyers and sellers don’t always have the same information about a vehicle’s quality, potentially resulting in low-quality cars being bought and sold.   In 1986, CARFAX sought to begin to “level the playing field” between buyers and sellers of used vehicles by collecting, analyzing and making relevant data/information available in the marketplace to both buyers and sellers.

• What data does CARFAX collect?
• Why this data vs other data?
• How does the market drive the type of data collected?
• How does CARFAX analyze and make this data available to answer real world questions?

  • Is this car safe?

  • How much should I pay for it?

  • What’s it worth?

  • What’s the risk to insure it?

  • What’s the risk to finance it?

Faisal Hasan is the General Manager, Data & Public Policy at CARFAX.   In his over 17 years at CARFAX, Faisal has been responsible for helping to build CARFAX’s Vehicle History Database through public and private data acquisition efforts across North America, including overcoming legislative and regulatory hurdles to data access. Faisal focuses on CARFAX’s efforts to secure and analyze data to feed the CARFAX “Onetime to Lifetime” Game Plan and develop future CARFAX products. Faisal earned his B.A. in Government & Politics at George Mason University and his M.A. in Government at the Johns Hopkins University. Faisal has been a Fairfax County resident for over 35 years. He is married w/four kids, including a GMU Junior studying Biology and a 2017 GMU Kinesiology graduate.

Sri Melkote is Head of Business Analytics at CARFAX.  Sri has been at CARFAX for 2 years and leads teams responsible for valuation modeling, pricing analytics, marketing research, media measurement and optimization. He has over 12 years of data science experience. Prior to joining CARFAX, Sri developed dynamic pricing systems, personalized recommendation engines and inventory planning systems for the travel industry. He holds a Master’s degree in Mathematics from Purdue University and a Bachelor’s degree in Chemical Engineering from Indian Institute of Technology, Madras. He is the author of several journal articles and a recipient of the 2011 INFORMS Revenue Management and Pricing Practice Award.

COLLOQUIUM ON COMPUTATIONAL SCIENCES AND INFORMATICS

Feras A. Batarseh
Research Assistant Professor
Department of Geography and Geoinformation Science
College of Science
George Mason University

Why an open mind on open data can transform our collective intelligence

Monday, February 5,  4:30-5:45
Exploratory Hall, Room 3301

Abstract:  In 1822, the founding father James Madison said: “A popular government, without popular information, or the means of acquiring it, is but a prologue to a farce or a tragedy, or perhaps both”. Recent technological waves have evidently served Madison’s vision of government transparency. The latest advancements in Artificial Intelligence (AI), Data Science, and Machine Learning can make federal data openness a low hanging fruit. Moreover, the big data and open government initiatives (signed in 2012 and 2013) are major enablers for transforming government into a new era of intelligent and data-driven policy making. However, to be able to use data in reforming the political discussion, public federal data needs to devise the promised openness.

Besides benefiting government, Open Data benefits many other domains and applications of data science, such as healthcare, finance, and academia. For example, Open Data could lead to a general openness in science (i.e. Open Science), clearer experimental research, and begin reshaping the human knowledge in general. These topics and other facets will be discussed in this talk.

Bio:  Feras A. Batarseh is a Research Assistant Professor,Department of Geography and Geoinformation Science, College of Science, George Mason University in Fairfax, VA. His research spans the areas of Data Science, Artificial Intelligence, and Context-Aware Software Systems. Dr. Batarseh obtained his Ph.D. and M.Sc. in Computer Engineering from the University of Central Florida (UCF) (2007, 2011), and a Graduate Certificate in Project Leadership from Cornell University (2016). His research work has been published at various prestigious journals and international conferences. Additionally, Dr. Batarseh published and edited several book chapters.

https://www.amazon.com/Federal-Science-Advanced-Analytics-Agricultural/dp/0128124431

Dr. Batarseh has taught data science and software engineering courses at multiple universities including GMU, UCF as well as George Washington University (GWU). Prior to joining GMU, Dr. Batarseh was a Program Manager with the Data Mining and Advanced Analytics team at MicroStrategy, Inc., a global business intelligence corporation based in Tysons Corner, Virginia. During his tenure, he helped several clients make sense of their data and gain insights into improving their operations. For more information on his research, and contact details, please refer to these webpages: http://ferasbatarseh.com/

http://cos.gmu.edu/ggs/people/faculty-staff/feras-batarseh-2/

COLLOQUIUM ON COMPUTATIONAL SCIENCES AND INFORMATICS

Michael Eichler
Strategic Planning Advisor
Metro Office of Planning
WMATA

Metrorail and Metrobus, Data Sources and Information Needs

Monday, February 12,  4:30-5:45
Exploratory Hall, Room 3301

Abstract:  Modernization of nearly all the technology that underlies the provision of rail and bus transit service over the past 30 years has resulted in a vast amount of data that until recently has been more or less neglected.  Meanwhile, challenges that face rail and bus transit systems continue to mount, from maintaining a state of good repair to capturing and keeping riders in the age of Uber/Lyft and bike share.  The key to providing safe, convenient, affordable, and reliable transit service into the next century lies in the hands of data scientists and policy analysts.  This talk will review the different data-generating technologies and the types of data they create, followed by an exploration of the pressing issues faced by transit agencies and the questions begging for answers. 

Bio:    Michael currently serves as Strategic Planning Advisor at WMATA in the Office of Planning’s Applied Planning Intelligence unit, where he focuses on transforming data into information to help inform policy and planning decisions.  He currently focuses on fare policy, crowding, GTFS data and online tools, and customer-focused performance metrics.  Before joining WMATA in 2010, he worked for Oracle Corporation, an IT start-up, and the Metropolitan Washington Council of Governments.   He holds a BS in Systems Analysis and Engineering from The George Washington University, and masters in City and Regional Planning and Transportation Engineering from UC Berkeley. 

COLLOQUIUM ON COMPUTATIONAL SCIENCES AND INFORMATICS

 Sean Mallon, Associate Vice President
Entrepreneurship and Innovation
George Mason University
and
Eric Koefoot
Founder and CEO of PublicRelay

The Journey and Stories of a Data Science Entrepreneur

Monday, February 19, 4:30-5:45
Exploratory Hall, Room 3301

This session will feature conversation between Sean Mallon, Mason’s AVP for Entrepreneurship and Innovation, and Eric Koefoot, founder and CEO of PublicRelay, a venture-backed data analytics and media intelligence startup based in McLean, VA. During the discussion we will explore a wide range of topics, ranging from what inspired the initial business idea, to customer discovery, to product development challenges, to fundraising, to customer acquisition strategies, and much more. This will be a highly interactive seminar and participants are encouraged to come with questions and personal experiences to share.

Sean Mallon, Associate Vice President, Entrepreneurship and Innovation, Office of the Provost. Photo by Ron Aira/Creative Services/George Mason University

Sean Mallon Bio: Sean Mallon is Mason’s Associate Vice President for Entrepreneurship and Innovation. Before joining Mason in 2016, Sean spent many years as an entrepreneur and early-stage technology investor. Sean hold a Bachelor’s in History from Princeton and an MBA from the Wharton School of the University of Pennsylvania.

Eric Koefoot Bio: Formerly the CEO of U.S. News Ventures, CEO at Five Star Alliance, CFO and later VP Global Sales at Washington Post Digital, Eric is the founder and CEO of PublicRelay and brings substantial media experience and understanding. Eric holds a Bachelor’s in Engineering from MIT and an MBA from the Sloan School at MIT.