Author: William Kennedy

The Research Colloquium on Computational Social Science/Data Sciences speaker for Friday, September 27, 2019, will be Anamaria Berea, Visiting Research Assistant Professor, Complex Adaptive Systems Lab, University of Central Florida. Dr. Berea’s talk entitled “Exploring what is universally possible for life with a wealth of computational methods” will begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA
For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/
For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

We hope to see you on Friday, September 27, 2019 at 3:00.

Abstract: In this talk I will discuss the advances made at NASA/SETI Frontier Development Lab AI Research Accelerator with respect to understanding the coevolution of biospheres and atmospheres, from cellular metabolisms to planetary environments. The current challenge presented by the sample of 1 when we consider the evidence of life and living systems in the Universe is overcome by a series of computer simulations and simulated data that give enough potential combinations of stable biospheres to be explored by machine learning algorithms. While we are only scratching the surface now with respect to the promise and perils of constructing well informed simulations and feeding them into more advanced algorithms, this approach will hopefully help identify possible life on observable exoplanets identified in the Kepler and TESS data. Methodologically, we explored Monte Carlo simulations, agent-based models, machine learning and dockerization in a complex data architecture supported by Google, in order to simulate more than 250,000 stable atmospheres, 500 types of synthetic genomes (metabolic networks) and more than 37,700,000 chemical reactions.

Bio: Anamaria Berea has dual PhDs in economics (2010) and computational social science (2012). Her research is focused on the emergence of communication in biological and social networks, by applying theories and methods from economics, complex systems and information theory to understand fundamental aspects of communication from cells to societies. Dr. Berea was one of the data scientists part of the NASA/SETI Frontier Development Lab (2017) in the heliophysics team and a data science mentor for the astrobiology team in the following year. She is the author of the book “Emergence of Communication in Socio-Biological Networks”, Springer, 2018. She is currently a Blue Marble Space Institute of Science research scientist and a Visiting Research Assistant Professor, Complex Adaptive Systems Lab, University of Central Florida.

Dr. Vadim Sokolov, Assistant Professor, Department of Systems Engineering and Operations Research, will be the presenter at Friday’s
Research Colloquium on Computational Social Science/Data Science. His topic will be “Dimensionality Reduction for Agent Based Models.”

Friday, September 20, 3:00 p.m.
Center for Social Complexity Suite, 3rd Floor Research Hall

All are welcome to attend.

Abstract:
Bayesian algorithms such as Markov Chain Monte Carlo or Bayesian optimization can quickly become computationally prohibitive or even infeasible for high dimensional ABM problems. In many applications, however, the underlying dynamics of an ABM typically can be represented in a lower dimensional space. We will review existing linear and nonlinear dimensionality reduction methods, such as Laplacian eigenmaps and restricted Boltzmann machines. Further, we will present some new results for nonlinear dimensionality techniques based on deep learning models. We will demonstrate our approach in the context of Bayesian optimization algorithms applied to a transportation agent-based model. Finally, we discuss directions for future research.

Bio:

Vadim Sokolov is an assistant professor in the Systems Engineering and Operations Research Department at George Mason University. He works on building robust solutions for large scale complex system analysis, at the interface of simulation-based modeling and statistics. This involves, developing new methodologies that rely on deep learning, Bayesian analysis of time series data, design of computational experiments and development of open-source software that implements those methodologies. Inspired by an interest in urban systems he co-developed mobility simulator called Polaris that is currently used for large scale transportation networks analysis by both local and federal governments. Prior to joining GMU he was a principal computational scientist at Argonne National Laboratory, a fellow at the Computation Institute at the University of Chicago and lecturer at the Master of Science in Analytics program at the University of Chicago.

The Research Colloquium on Computational Social Science/Data Science speaker for Friday, September 13, will be Kim McEligot, Ph.D. Candidate, Department of Systems Engineering and Operations Research at George Mason University. Kim’s talk entitled “Sea Bright, New Jersey Reconstructed: Agent-Based Protection Theory Model Responses to Hurricane Sandy” (abstract below) will begin at 3:00 in the Center for Social Complexity Suite (373-381) located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA
For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

Abstract: Coastal flooding is the most expensive type of natural disaster in the United States. Policy initiatives to mitigate the effects of these events are dependent upon understanding flood victim responses at an individual and municipal level. Agent-Based Modeling (ABM) is an effective tool for analyzing community-wide responses to natural disaster, but the quality of the ABM’s performance is often challenging to determine. This paper discusses the complexity of the Protective Action Decision Model (PADM) and Protection Motivation Theory (PMT) for human decision making regarding hazard mitigations. A combined (PADM/PMT) model is developed and integrated into the MASON modeling framework. The ABM implements a hind-cast of Hurricane Sandy’s damage to Sea Bright, NJ and homeowner post-flood reconstruction decisions. It is validated against damage assessments and post-storm surveys. The contribution of socio-economic factors and built environment on model performance is also addressed and suggests that mitigation for townhouse communities will be challenging.

Bio: Kim McEligot is a PhD candidate in the Department of Systems Engineering and Operations Research at George Mason University. His research interests include federation of computational fluid dynamics coastal flood modeling with geo-spatial agent-based modeling for individual and community level flood mitigation policy analysis. He holds an M.S. in Systems Engineering from Johns Hopkins University, and an M.A. in National Security and Military Affairs from the U.S. Naval War College. His email address is kmceligo@masonlive.gmu.edu.

Welcome to the first seminar of the fall semester.

The Research Colloquium on Computational Social Science/Data Sciences speakers for Friday, September 06, 2019, will be Ben Intoy, PhD and Dan Baeder from Deloitte Consulting LLP. Their talk, entitled “Massive-Scale Models of Urban Infrastructure and Populations,” will begin at 3:00pm in the Center for Social Complexity Suite (373-381) located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

We hope to see you on Friday, September 06, 2019 at 3PM.

Abstract:

As the world becomes more dense, connected, and complex, it is increasingly difficult to answer “what-if” questions about our cities and populations. Most modeling and simulation tools struggle with scale and connectivity. We present a new method for creating digital twin simulations of city infrastructure and populations from open source and commercial data. We transform cellular location data into activity patterns for synthetic agents and use geospatial data to create the infrastructure and world in which these agents interact. We then leverage technologies and techniques intended for massive online gaming to create 1:1 scale simulations to answer these “what-if” questions about the future.

Bios:

Ben Intoy is a full stack developer at Deloitte Consulting LLP. He received his PhD in Physics at Virginia Tech in 2015 where he used high throughput computing simulations to study stability properties of cyclically competing species in varying spatial dimensions. After completing his PhD, Ben went to the University of Minnesota, Twin Cities campus, as a postdoctoral research associate where he used tools he learned in his PhD to abstractly study the origin of life on earth and the probability of finding life elsewhere in the universe. In fall 2018, he took a position at the Deloitte Arlington, VA office to work on the FutureScape project (www.futurescape.ai).

Dan Baeder is a data scientist at Deloitte Consulting LLP, and has been on the FutureScape project since joining the firm last year. While at Deloitte, Dan focuses on the use of cellular phone geolocation data for the development of synthetic traffic models, as well as the application of geospatial analysis techniques to human behavior modeling. He is a noted R-phile in a sea of Python users. Dan received an MS in Public Policy and Management with a focus on data analytics from Carnegie Mellon University in 2018.

The Colloquium on Computational Social Science/Data Sciences Research speaker for Friday, May 03, 2019, will be Gary Bogle, who recently defended his CSS doctoral dissertation. Gary’s talk entitled “Polity Cycling in Great Zimbabwe via Agent-Based Modeling: The Effects of Timing and Magnitude of External Factors,” will begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/
For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

NOTE: this is the last seminar for the spring semester; see you in the fall semester!

Abstract: This research explores polity cycling at the site of Great Zimbabwe. It rests on laying out the possibilities that may explain what is seen in the archaeological record in terms of modeling what external factors, operating at specific times and magnitudes. What can cause a rapid rise and decline in the polity? This is explored in terms of attachment that individuals feel towards the small groups of which they are a part of, and the change in this attachment in response to their own resources and the history of success that the group enjoys in conducting collective action. The model presented in this research is based on the Canonical Theory of politogenesis. It is implemented using an agent-based model as this type of model excels at generating macro-level behavior from micro-level decisions.

The input parameters to the model presented here are the collective action frequency (CAF) and environmental effect multiplier. The results show that a prehistoric polity can be modeled to demonstrate a sharp rise and fall in community groups and that the rise and fall emerges from the individual decision-making.

The Colloquium on Computational Social Science/Data Science Research speaker for Friday, April 19 will be Francesca Tavazza, Ph.D., National Institute of Standards and Technology, Materials Science and Engineering Division. Dr. Tavazza’s talk entitled “The JARVIS project: Accelerating discovery of materials and validation of models using classical, quantum and machine-learning methods” (abstract below) will begin at 3:00 in the Center for Social Complexity Suite located on the third floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

Please visit https://cos.gmu.edu/cds/calendar/to see list of upcoming seminar speakers.

Abstract: Identifying new materials for technological applications is the goal of the Material Genome Initiative (MGI). As a response, NIST started the JARVIS project, a combination of atomistic databases at the classical and quantum level, and machine learning models. JARVIS-DFT is a collection of physical properties computed using Density Functional theory (DFT) for about 30000 materials. For each material, we determined its heat of formation, conventional and improved DFT bandgaps, dielectric function, elastic, phonon, electronic and transport properties. Statistical analysis of such properties allows to identify novel trends as well as new materials with desirable properties. JARVIS-FF is a database of classically computed properties, designed to facilitate the user in choosing the right classical force field (FF) for their investigation. It uses the LAMMPS code to compute the same property, for the same material, with as many force fields as available (more than 25000 classical force-field). We focused on quantities like relaxed structures, elastic properties, surface energies, vacancy formation energies and phonon vibrations. JARVIS-FF contains these calculations for more than 3000 materials, so that a direct comparison between FF is easily achieved. Lastly, using all the properties in JARVIS-DFT as a training set, and novel descriptors inspired by FF-fitting, we developed machine learning (ML) models for all the properties studied in JARVIS-DFT. This allows to make on the fly predictions, and, therefore, to use ML to pre-screen materials.

Dr. Tavazza’s Short Bio:
Undergraduate degree in Physics in Milan, Italy, 1993 (Universita’ Statale di Milano, Milano, Italy)
Master in Material Science in Milan, Italy, 1996 (Universita’ Statale di Milano, Milano, Italy). Dissertation topic: Tight-binding modeling of Cobalt and Iron Silicides, including fitting of the tight-binding parameters.
PhD in Physics at The University of Georgia, GA, USA in 2003 (PhD. Advisor: Prof. Davis Landau). Dissertation topic: Classical Monte Carlo simulations of Si and Si-Ge compounds under various conditions.
PostDoc at NIST starting in 2003, focusing on Density Functional theory (DFT) modeling of mechanical properties in metals.
Brief hiatus working at the Army Research Laboratory in 2008 for a short time, otherwise at NIST ever since I got there as a postdoc.
Currently: running an atomistic modeling group (both classical and DFT modeling) focused on the investigation of specific, technological relevant materials (TaS2, TaSe2, Bi2MnSe4, for instance) as well as on compiling databases of material properties. My group extensively uses artificial intelligence (AI) tools to accelerate material discovery as well as to build novel force fields (physics-inspired, neuron network-based fitting of Si, Ge, SiGe, AlNi potentials).

The Colloquium on Computational Social Science/Data Sciences Research speaker for Friday, April 12, 2019, will be Melanie Swartz, Computational Social Science PhD Candidate, Department of Computational and Data Sciences. Melanie’s talk entitled “Emoji Use in Social Media During Events” will begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

Abstract: Emoji in social media add more information than just a pictograph to accompany words or convey emotion. Emoji use related to communication about collective social events can provide additional insight about our collective identity and social interactions. Melanie will be presenting preliminary results and welcomes your feedback of her analysis on emoji use in social media for a number of events ranging from national, religious, protests, marches, celestial events, global scheduled events such as International Women’s Day, and more. We look forward to seeing you in person for an engaging discussion on Friday as this event will not be recorded or live streamed.

The Colloquium on Computational Social Science/Data Sciences Research speaker for Friday, March 08, 2019, will be Cody Buntain, Post Doctoral Researcher with New York University’s Social Media and Political Participation Lab. Dr. Buntain’s talk entitled “#pray4victims: Consistencies In Response to and Automatically Identifying Diverse Information Needs During Disasters on Twitter” is scheduled to begin at 3:00 in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

Abstract: This talk presents commonalities in response across disasters in online social networks (OSNs) and Twitter specifically.

After presenting an algorithm for extracting vocabularies across disasters, we extract type-specific vocabularies for terrorist attacks, earthquakes, and climate-related disasters between 2012 and 2017.

Within similar disasters, commonalities emerge: terrorism responses reference the “attack” and law enforcement, earthquake responses mention the quake and its magnitude, and climate-related responses include safety and requests for aid.

Across disaster types, tweets regularly mention victims/affected and prayer, consistent with communal coping and social support in crisis aftermath.

Using these disaster-type vocabularies, we study Twitter as an alternate measure for severity, correlating casualties to Twitter volume.

These vocabularies better correlate with casualties than baseline crisis lexica, especially in western countries.

Twitter response and casualties diverge at the extreme, and Twitter response is stronger in Western countries, suggesting perceived severity is driven by additional factors.

These vocabularies also potentially represent disaster-type-specific information needs, which we then roll into a machine learning task for automatically identifying crisis-related information in Twitter data.

Bio: Cody Buntain received his PhD from the Computer Science Department at the University of Maryland and is a postdoctoral researcher with New York University’s Social Media and Political Participation Lab. His primary research areas apply large-scale computational methods to social media and other online content, specifically studying how individuals engage socially and politically and respond to crises and disaster in online spaces. Current problems he is studying include cross-platform information flows, network structures, temporal evolution/politicization of topics, misinformation, polarization, and information quality. Recent publications include papers on influencing credibility assessment in social media, consistencies in social media’s response to crises, the disability community’s use of social networks for political participation, and characterizing gender and direction in online harassment.

will present at the Colloquium in Computational Social Science and Computational and Data Sciences Research. Dr. Yu’s talk entitled “Synthesizing Human-centric Architectural Layouts via Affordance Analysis and Crowd Simulations” (abstract below) is scheduled to begin at 2:00 (PLEASE NOTE EARLY START TIME FOR THIS TALK ONLY) in the Center for Social Complexity Suite located on the 3rd floor of Research Hall. The talk will be followed by a Q&A session along with light refreshments.

This session will be live-streamed on the YouTube channel: https://www.youtube.com/channel/UC7YCR-pBTZ_9865orDNVHNA

For announcements regarding this and future streams, please join the CSS/CDS student and alumni Facebook group: https://www.facebook.com/groups/257383120973297/

For a list of upcoming and previous seminars, please visit: https://cos.gmu.edu/cds/calendar/

Abstract: In this talk, I will discuss the recent progress of my team in devising computational design approaches for automatically generating human-centered architectural layouts for real-world design and virtual reality applications. For example, I will talk about the state-of-the-art procedural modeling techniques for generating large-scale architectural layouts that are optimized with respect to human navigation properties; and techniques for automatically generating interior designs for furnishing indoor scenes with furniture objects. In particular, I will discuss how human intentions and functionality considerations can be employed as the key criteria in generating 3D worlds. I will also discuss how human perceptual data tracked from virtual reality can be employed for creating personalized workspace design and for VR training.

Bio: Craig Yu is an Assistant Professor in the Department of Computer Science at the Volgenau School of Engineering. He works on computer graphics, vision, human-computer interaction, and virtual reality, particularly on AI and data-driven techniques for computational design. Yu obtained his Ph.D. in Computer Science from UCLA in 2013 with an Outstanding Recognition in Research Award. Yu was a visiting scientist at the MIT International Design Center and a visiting scholar at the Stanford Computer Graphics Lab. He is the recipient of the Cisco Outstanding Graduate Research Award, the Award of Excellence from Microsoft Research, the UCLA Dissertation Year Fellowship, and the Sir Edward Youde Memorial Fellowship. His research has been featured by New Scientist, the UCLA Newsletter, and the IEEE Xplore Innovation Spotlight. His lab is supported by the NSF, Microsoft, Google, Nvidia, and Oracle.