Calendar

COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
AND THE DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES (CSI 898-Sec 001)

Local Structure Analysis in Simulated Materials via Voronoi Topology

Emanuel A. Lazar
Laboratory for Research on the Structure of Matter
School of Engineering and Applied Science
University of Pennsylvania
Philadelphia, PA

Describing how atoms are arranged in real and simulated materials is a very natural problem that arises in numerous computational materials science applications. However, aside from perfect crystals, insightful yet tractable descriptions of local arrangements of atoms can be tricky to develop.   We consider several conventional order-parameter methods for describing local structure and highlight their theoretical and practical limitations.   We then introduce a topological approach more naturally suited for structure analysis and highlight its versatility and robustness. In particular, the Voronoi tessellation method can aid in the study of materials at high temperatures, close to melting, without uncontrolled modification of raw data. Applications to the study of grain boundary evolution and melting will be briefly presented.

September 26, 2016, 4:30 pm
Exploratory Hall, Room 3301
Fairfax Campus

Refreshments will be served at 4:15 PM.

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Find the schedule at http://www.cmasc.gmu.edu/seminars.htm

COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
AND THE DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES (CSI 898-Sec 001)

Embedding Context in Intelligent User Interfaces Using Data Analytics

Dieter Pfoser, Associate Professor
Department of Geography and Geoinformatics
George Mason University
Fairfax, VA

October 24, 2016, 4:30 pm
Exploratory Hall, Room 3301
Fairfax Campus

Making sense of user-generated Web content such as social media data, blogs, or even Wikipedia entries poses interesting research challenge considering its lack of structure, amount, and associated noise. This work introduces a range of online content summaries for such unstructured data. Besides the typical spatial, temporal and thematic summaries, we introduce two additional views. Geoevents are emerging events that are limited in spatial scope hashtags and that are detected automatically by comparing their spatial distribution to a global topic search.

Links-of-Interests (LOIs) are connection summaries between geographic locations, people and concepts. These content summaries are available as part of the functionality of a Web-based tool that allows for the interactive visualization, querying and exploration of such unstructured data. This talk will discuss research results and demo the capabilities of the visualization prototype.

Refreshments will be served at 4:15 PM.

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Find the schedule at http://www.cmasc.gmu.edu/seminars.htm

COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
AND THE DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES
(CSI 898-Sec 001)

Scientific Data Mining and Its Applications in Tropical Cyclone Research

Ruixin Yang, Associate Professor
Department of Geography and Geoinformatics
George Mason University
Fairfax, VA

October 31, 4:30 pm
Exploratory Hall, Room 3301
Fairfax Campus

In this talk I will give an overview of of scientific data mining (SDM) followed by a few examples of SDM applications to the analysis of tropical cyclones (TCs), focusing on their intensity changes. Because rapidly intensifying (RI) tropical cyclones are the major error sources in TC intensity forecasting, association rules facilitate the RI process by mining for sets of conditions that have strong interactions with rapidly intensifying TCs. The technique of association rules explores associations among multiple conditions in a simple manner identifying a predictor set with fewer factors but improved RI probabilities. Furthermore, in searching the “optimal” RI condition combinations, a peculiar condition combination was identified that gives a very high RI probability. Such combination can be considered as a sufficient condition for RI that almost guarantees that a RI will take place. Applications of classification techniques to the intensity forecasting will also be discussed. Several drawbacks and future directions for SDM with the TC intensity change problem will be discussed at the end of the talk.

Refreshments will be served at 4:15 PM.

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Find the schedule at http://www.cmasc.gmu.edu/seminars.htm

COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
AND THE DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES
(CSI 898-Sec 001)

Robust Estimation of Value-at-Risk for Quantitative Risk Management: Applications to Climatology, Insurance, Accidents and Financial Analysis

Sabyasachi Guharay
U.S. Department of the Treasury
Washington, D.C.

November 7, 4:30 pm
Exploratory Hall, Room 3301
Fairfax Campus

Establishing robust quantitative metrics which allow decision makers to determine the amount of risk in a system with extreme loss events is a problem of interest in many scientific fields. One of the fundamental metrics which is universally accepted in all fields of risk management is the quantity known as Value-at-Risk (VaR). A subfield of risk management, modern Operational Risk Management (ORM), closely investigates methodologies on robustly estimating VaR, “Robust Estimation of VaR.” Currently, academic researchers and industry practitioners are actively looking at ways to make this estimate more statistically robust and accurate with minimal assumption requirements.

In this talk I will present two new quantitative approaches for estimating VaR that are agnostic regarding the relationship between frequency and severity: (1) Data Partition of Frequency and Severity (DPFS) using K-means to estimate VaR; (2) Distribution based partitioning (DBP) of frequency and severity using copulas. Verification is conducted on five simulated scenario datasets while validation is conducted on five publicly available datasets from four different domains:   –US Financial Indices data of Standard & Poor’s 500 and Dow Jones Industrial Average;   –Chemical Loss spills as tracked by the US National Coast Guard;   –Australian automobile accidents;   –US hurricane data. It is observed that previous VaR calculations inaccurately estimate the VaR for 80% of the cases in simulated data and 60% of the cases in real-world data studies while new methodologies attains accurate VaR estimates which are within the 95% confidence interval bounds for both simulated and real-world data.

Refreshments will be served at 4:15 PM.

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Find the schedule at http://www.cmasc.gmu.edu/seminars.htm

COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
AND THE DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES
(CSI 898-Sec 001)

Using Coarse-Grained Models to Access Expanded Length and Time Scales for Nanoscience Applications

K. Michael Salerno, Jr.
Center for Computational Materials Science
Naval Research Laboratory
Washington D.C.

November 14, 4:30 pm
Exploratory Hall, Room 3301
Fairfax Campus

Polymers and other soft materials have an important role as a coating for nanoscale building blocks like metallic nanoparticles (NPs) and nanorods. This coating mediates interactions between these building blocks and their environment. Atomistic molecular dynamics (MD) simulations are ideal for examining the role of chemistry and atomic interactions at the sub-nanometer scale, for example in the interactions between a NP and a solvent, or between pairs of NPs. Unfortunately, atomistic MD simulations are limited to lengths of order 50 nm and times of order 50 ns. The time scale limitation precludes modeling nanoscale self-assembly, and limits dynamic simulations to extremely high rates of deformation or thermalforcing. These simulations are also limited to sizes that represent a small number of NPs, making it impossible to model large assembled structures.

Faced with these limitations, we have developed coarse-grained (CG) models of polyethylene, a simple polymer used to coat NPs and nanorods. These models have enabled simulations of bulk polymer melts that overcome the limits of atomistic MD by providing a computational speedup of greater than 104 while retaining fundamental details at the sub-nanometer scale. These details produce the viscoelastic properties and semi-crystalline behavior that are intrinsic to polyethylene and that are missed by generic CG models. When applied to a NP coating the CG models capture the coating morphology, indicating the value of using these CG models in nanoscale applications.

Refreshments will be served at 4:15 PM.

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Find the schedule at http://www.cmasc.gmu.edu/seminars.htm

COLLOQUIUM OF THE COMPUTATIONAL MATERIALS SCIENCE CENTER
AND THE DEPARTMENT OF COMPUTATIONAL AND DATA SCIENCES (
CSI 898-Sec 001)

Topological Quantification of Microstructures

Tom Wanner
Department of Mathematical Sciences
George Mason University
Fairfax, VA

November 21, 2016, 4:30 p.m.
Exploratory Hall, Room 3301
Fairfax Campus

Many applied processes generate complex microstructures or patterns which are hard to quantify due to the lack of any underlying regular structure. These patterns may evolve with time or include some element of stochasticity. The resulting variations in the detail structure frequently force one to concentrate on rougher geometric features. From a mathematical point of view, several notions from algebraic topology suggest themselves as natural quantification tools in such a setting.   In this talk I will describe some of these tools, in particular homology and persistent homology, and how they can be efficiently computed using open source software. I will also present some applications motivated by materials science problems.

Refreshments will be served at 4:15 PM.

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Find the schedule at http://www.cmasc.gmu.edu/seminars.htm

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.