Abstract: Ecosystem health issues abound worldwide with environmental implications, and impact for animal and human populations. The complexity of addressing problems systemically in the policy arena on one side, and the lack of use of computational technologies for quantitative public policy on the other side has determined a worsening of ecosystem health.

We propose to enhance existing adaptive management efforts with an integrated decision-analytical and environmental dynamic model that can guide the strategic selection of robust ecosystem restoration alternative plans. The model can inform the need to adjust these alternatives in the course of action based on continuously acquired monitoring information and changing stakeholder values. We demonstrate an application of enhanced adaptive management for a wetland restoration case study inspired by the Florida Everglades restoration effort. This has implication for the environment, animal and human health and embraces the sustainability paradigm quantitatively. In terms of diseases we particularly look into waterborne diseases. In relation to the Everglades, we find that alternatives designed to reconstruct the pre-drainage flow may have a positive ecological and animal health impact, but may also have high operational costs and only marginally contribute to meeting other objectives such as reduction of flooding that has catastrophic human impact and morbidities in terms of deaths and infectious disease symptoms. Enhanced adaptive management allows managers to guide investment in ecosystem modeling and monitoring efforts through scenario and value of information analyses to support optimal restoration strategies in the face of uncertain and changing information. Thus, the model allows decision makers to explore the full landscape of possible scenarios before taking decisions and to dynamically design the system considering stakeholder values, economical and political constraints, ecosystem dynamics and surprises.

In this way, ecosystem health is considered as a public good affected by many objective and subjective factors treated all together via a computational technology that informs about the decision or policy with the highest value.

Bio: Dr. Convertino, PI of the HumNat Lab, is involved in the promotion of complexity science and engineering design of natural and human systems for population health. In a broader perspective this effort is committed to the diagnosis, etiognosis and prognosis of diseases via smart and multiscale global system science and art-in-science. My deep interest is in the identification of the fundamental factor interactions (”processes”) leading to observed patterns by integrating system biology/ecology (with particular focus on the environmental dynamics — e.g. ecohydrological dynamics — in systemic macro-epidemiology) and in the translation of that knowledge to applications for stakeholders via decision science and engineering methods. The quest for universalities, system states and state transitions via tipping points is a key in the research of Dr. Convertino. Theories and models that have been developed are: Optimal Transmission Networks, Morphological Effective Systemic Epigraph, Information-theory based Global Sensitivity and Uncertainty Analysis, MaxEnt Model in geomorphology and epidemiology, Portfolio Decision Models for Enhanced Adaptive Management, Reverse Engineering Traceback Model, and Game-based Mental Modeling. The conversion of these models to software (STEM and DECERNS) is ongoing as well as ”science as art” initiatives. Fun fact: How did Dr. Convertino got interested into this? His hometown: Venice! He started to be interested in the design of bridges, the dynamics of water ecosystems, and later on in people dynamics and how that can be analyzed by combining methods used to design bridges and water ecosystems. In one word: connectomics (!), i.e. how everything is connected to everything.

Abstract: Training future scientists is critical for all federal scientific agencies and for the future of scientific research in the United States. The National Institutes of Health (NIH), the federal scientific agency tasked with enhancing health and reducing disability and illness through research advancements, dedicates significant funding to training the next generation of biomedical researchers. NIH invests in postdoctoral research training to increase independent research and professional experiences and to promote future research career success for emerging biomedical scientists. Given exponential increases in biomedical postdoctoral appointments since 1995 and widely-held expectations that these opportunities enhance future research career success, this paper presents new evidence about the impact of postdoctoral fellowship participation on research career outcomes. We estimate the causal effects of F32- NIH postdoctoral fellowship programs on the probability to continue doing research in areas of NIH interest using a fuzzy regression discontinuity design. We examine a dichotomous RPG award outcome and find that receiving an individual postdoctoral fellowship award at the margin increases the probability of receiving a RPG grant in about 6 percentage points after 4 years or more of their last F32 application.

Bio: Maria I. Larenas has strong expertise in the analysis and management of complex data sets as well as a solid understanding of the theoretical issues in areas of labor economics and economics of education. She had worked as a research economist in different organizations such as the research group of the Nobel Laureate James Heckman, RCF Economic and Financial Consulting in Chicago, SENDA (Chilean government agency of prevention and rehabilitation of alcohol and drugs abuse), and International institutions (IADB and World Bank). Maria holds a B.A and Master Degree in Economics from her native country (Chile) and a Master in Public Policy from the University of Maryland. Her area of interest is the analysis and policy implications of school-to work transitions and their impacts on long-term outcomes.

Abstract: Corporate social responsibility (CSR) has emerged over the years as a mitigation strategy to unanticipated negative externalities of industrial technologies and markets. However, the scope, scale and impact of what has been possible through CSR in addressing these major societal challenges is clearly insufficient, as are the efforts deployed by governments and actors from the not-for-profit (NFP) sector. We develop and argue a computational model of convergent innovation (CI), a cross-sectoral approach to mainstream the societal issues targeted by CSR into core for-profit (FP) activities, placing them upfront as a driver of commercially successful technological innovation, business strategy, and market transformation, while having FP actors join governments and NFP actors to enact behavioral change and ecosystem transformation at scale. CI also entails social and institutional innovation to enable such a shift in the drivers of supply and demand at market level and in broader society. Using socio-economic inequity in access to healthy food in industrial Western society as a context, this paper lays the foundations for the dynamic modeling of equitable nutrition market transformation in the agri-food sector. We first deconstruct the existing ecosystem to specify the major inertial forces constraining change. We then use a stylized behavioral dynamic model to simulate interventions for single-actor and collective actions by FP and NFP actors and governments and examine economic change and inequity reduction outcomes over time. Results show that the economic viability of lasting social change requires cross-sectoral convergence between CSR-mainstreaming business strategy and market transformation and actions by NFP actors and government.

Bio: Jeroen Struben is Assistant Professor in the Strategy & Organization Area at the Desautels Faculty of Management Faculty and Fellow of the Marcel Desautels Institute for Integrated Management, McGill University. Jeroen received his PhD at MIT’s Sloan School of Management. Jeroen is a social and systems scientist with research focused on the dynamics of market formation and transformation towards more sustainable pathways. Empirically Jeroen studies energy, alternative fuel vehicle, and nutrition markets. Jeroen is particularly interested in the question: How do alternative products, ideas, and practices successfully penetrate in the marketplace or society at large, rather than falter? To examine this, Jeroen’s research focuses on how social processes and evolution of the built environment jointly condition the formation of self-sustaining markets. His research combines empirical, analytical, and systems science-based analysis, producing insights related to coordination, collective action and commitment across organizations, industries and governments.

Abstract: The United States has experienced an unsustainable expansion of the biomedical research workforce over the past three decades. This has led to a myriad of consequences, including imbalance in the number of researchers and available tenure track faculty positions; extended postdoctoral training periods; rising age of investigators at first NIH R01 grant; and exodus of talented individuals seeking careers beyond traditional academe. Without accurate data on the biomedical research labor market, challenges will remain in addressing these issues and in advising trainees of viable career options and necessary skills to be productive in their careers.   Herein we analyzed workforce trends, integrating both traditional labor market information and real-time job data. We generated a profile of the current biomedical research workforce, performed labor gap analyses of occupations in the workforce at regional and national levels, and assessed skill transferability between core workforce occupations and complementary occupations. We conclude that although supply into the workforce and the number of job postings for occupations within that workforce have grown over the past decade, supply continues to outstrip demand. Moreover, we identify technical and foundational skill gaps in the workforce through analysis of real-time job postings. Addressing these skill gaps could potentially equip trainees for multiple career pathways beyond academic research and lead to a more sustainable workforce.

Bio: Dr. Julie Bronder Mason is the Associate Director of the National Cancer Institute (NCI) Center for Cancer Training (CCT), where she leads training program development and evaluation, workforce analysis, and strategic planning. Dr. Mason recently led a labor and skills gap analysis of the U.S. biomedical research workforce. She has over 12 years of experience at the NCI. Before joining CCT, she was a health science analyst in NCI’s Office of Science Planning and Assessment, where she managed program evaluations and performance reporting. Dr. Mason earned a Ph.D. in Pharmacology and Toxicology from the Medical College of Virginia, and performed postdoctoral research in the NCI Laboratory of Molecular Pharmacology. Several notable awards Dr. Mason received include the NIH Plain Language Award, Award of Merit for service on the NIH American Recovery and Reinvestment Act committee, and the American Evaluation Association’s Best Paper Award for her career development program outcome evaluation.

Abstract: What drives regional innovation and economic performance? This paper reviews the major topical areas in the study of innovation and applies those theories and findings to developing measures for innovation and economic performance across regions. Attempts to create indices for innovation have focused almost exclusively on countries or states, thus precluding the ability to analyze the drivers of regional development. In addition, these indices are often under-appreciated by academics and researchers because many of the measures used to construct the indices lack theoretical and empirical support.

Our research corrects two deficiencies. One, our geographic unit of analysis for the innovation measures is the county. Using U.S. county definitions enables regional analysis across state boundaries for a single year as well as consistent metropolitan boundary definitions over time. Two, we operationalize key innovation concepts such as knowledge spillovers, venture capital, foreign direct investment, business formation, human capital and technology diffusion, in addition to the traditional drivers and measures of economic performance. The authors also propose metrics for measuring the performance of industry clusters on a county and regional basis as well as classifying patent technologies into a dozen major patent categories. This paper is, in effect, the motivation and theoretical foundation for the Innovation Index 2.0 — currently in beta. (http://www.statsamerica.org/innovationindex/Default.aspx)

Bio: Timothy Slaper {slay-per} leads a research team engaged in industry and workforce analysis, economic impact studies, regional economic analyses, demographic estimates and projections, trade and foreign investment analysis, measuring innovation and educational performance and the drivers of economic growth.

The team is putting the final touches on The Innovation Index 2.0. National in scope, The Innovation Index is a county-based data set and web tool for economic development practitioners as well as policy makers and researchers to assess a region’s innovative capacity and economic performance.

All the work that Timothy oversees puts analytical tools and practical research into the hands of economic development practitioners to help them address the challenges of economic development in today’s rapidly changing world.

Before the IBRC, Timothy served as Senior Economist on the Joint Economic Committee of Congress. He cut his teeth as an economist at the U.S. Bureau of Economic Analysis. ”

Abstract: African-American/Black, Hispanic/Latino, and American Indian/Alaska Native scientists are poorly represented on the faculty of basic science departments in MD-granting medical schools, despite decades of efforts to increase faculty diversity. The authors utilized the National Science Foundation Survey of Earned Doctorates and the Association of American Medical Colleges (AAMC) Faculty Roster to describe changes in the participation of scientists from underrepresented minority (URM) and well-represented (WR) backgrounds in the populations of (i) biomedical Ph.D. graduates, and (ii) full-time assistant professors in basic science departments at MD-granting medical schools between 1980-2013. These data were used to impute faculty-hiring trends, and to calibrate a system dynamics model of the progression from Ph.D. graduates to assistant professorships in basic science departments. The size of the potential candidate pool was significantly associated with the number assistant professors hired each year for scientists from WR (r2=0.48, p<0.0001) but not URM backgrounds (r2=0.12, p>0.07). Between 2005-2013, data indicate that there were 5,824 biomedical Ph.Ds. awarded to URMs, and a 7% growth in the total population of assistant professors, but no growth in the population of URM assistant professors. The system dynamics model explained significant variance in faculty hiring (r2=0.79). The model predicted that given current trends in transition from Ph.D. to assistant professors, URM faculty representation would remain below 8% as late as 2080—even in the context of exponential growth in the population of URM Ph.D. graduates. Faculty diversity cannot be achieved by relying primarily on increasing the pool of URM Ph.D. graduates. Efforts to increase faculty diversity must make meaningful linkages between URM Ph.D. graduates and faculty hiring.

Bio: Kenneth (Kenny) Gibbs, Jr., Ph.D., is a Program Analyst in the Office of Program Planning, Analysis and Evaluation (OPAE) at the National Institute of General Medical Sciences (NIGMS). Prior to joining NIGMS, Dr. Gibbs was a Cancer Prevention Fellow at the National Cancer Institute, and an AAAS Science & Technology Policy Fellow at the National Science Foundation (NSF) in the Directorate for Education and Human Resources (EHR). Dr. Gibbs completed his Ph.D. in the Immunology program at Stanford University, and received his B.S. in biochemistry & molecular biology from the University of Maryland, Baltimore County.

Abstract: We introduce an umbrella framework for defining and characterizing an ensemble of dynamic processes on graphs. It leads to intuitive linear transformations of graphs which can represent the flow of different dynamic processes, including consensus, random walks, as well as information diffusion over networks.

We show some empirical examples of how such transformations can be applied in scholarly networks where additional data is available, such as geographic and disciplinary maps. The goal is to produce multi-layered scholarly networks that better captures underlying scientific activities.

Bio: Xiaoran Yan is an Assistant Research Scientist at Indiana University Network Science Institute. His research concerns mathematical theories and models of networks, with a focus on community structures and dynamical processes on networks. He worked as a Postdoctoral Research Associate at Information Sciences Institute of University of Southern California. Before that, he was a graduate fellow at Santa Fe Institute. He received a Ph.D. in Computer Science at University of New Mexico.

Abstract: The growth in scalable sensors is driving opportunities for things and people to work together in expanded methods. Platforms that combine data sets, with machine learning algorithms, curated by people, and used by networks of people are transforming significant aspects of the world in which we live. An example is the combination of online maps, traffic data, handheld devices, and the GPS network, that is generating navigation tools as well as leading to new transportation services for drivers, passengers, cargo, and autonomous vehicles. Looking forward, by integrating networks at exponential scale from sensors through signal processing, edge computation, and cloud computing, the power of linking across these domain is enabling transformative change to agriculture, manufacturing, healthcare, education. To approach this problem at multiple scales of operation, techniques of systems engineering are emerging that incorporate hardware, software, as well as the socio-technical system of designers, operators, regulators, and users. These techniques build on those developed for Safety Design and Analysis developed by Nancy Leveson, of MIT Engineering Systems Division, and application to complex systems engineering curated by Anna McGowan, NASA senior engineer for complex systems design. Highlights of platform requirements and design will be presented together with two illustrative examples from smart agriculture and for the Factory of the Future.

Bio: Bruce Hecht is a designer of sensors and signal processing systems for instrumentation and healthcare with 20 years experience in launching new products and technologies. Bruce is currently leading the New Product Design Quality initiative at Analog Devices and is Advanced Study Program Fellow at MIT in the areas of Engineering, Entrepreneurship and Innovation in Healthcare and Systems Design. He holds a BASc and MASc in EE from the University of Waterloo, was awarded 5 US Patents and is a Certified Six Sigma Black Belt. Bruce is active with the IEEE for the Future of Knowledge and Convening, leading Masterclasses and international conferences on design, engineering, and advanced fabrication in cities from Boston to Bordeaux, Milan & Singapore. In 2015, Bruce presented a TEDx talk on the power of Curiosity and Design at the National University of Singapore and produced TEDxBeaconStreet as a Curator and Founding Member of Ideas in Action. He serves as a mentor for programs on Hacking Medicine, Internet of Things, and with the Canadian Technology Accelerator in Boston.

Abstract: Science, technology, and innovation is a critical component of our efforts to tackle societal challenges we face today. Smart cities would be considered to be a key field in which a variety of science and technological knowledge need to be integrated effectively to address the combined target of energy security and environmental protection. A smart city would involve an advanced technological system for efficient electricity supply and applications, incorporating all the behavior of the actors involved, including generators, distributors, technology developers, and consumers, through an intelligent information network. As a smart city integrates a diverse mixture of hardware as well as software involving a large amount of various kinds of data in a complex way, different approaches would be possible to creating and implementing innovation on smart cities in practice, depending on the economic, social, and environmental factors, such as energy efficiency, operating cost, environmental impact, resilience to external shocks and disturbances, and accessibility and inclusiveness to end users. This study examines the innovation systems of smart cities in Japan, Europe, and the United States. Approximately 200 projects on smart cities are analyzed with regard to the knowledge domain, actors involved, and institutional environment. Information was collected through various sources, such as project reports, academic articles, corporate reports, trade journals, and web sites, and interviews were conducted with relevant stakeholder, including academia, firms, industry association, and government organizations. Network analysis is conducted to identify key stakeholders involved in innovation and to analyze the relationships between them. The innovation systems of smart cities are modeled based on the primary functions involved in the dynamic processes. These include the creation of future visions based on science, setting of concrete and practical goals and targets, joint scenario making with stakeholders, securing active participation and serious engagement of stakeholders, collection and analysis of data on societal needs and demands, development of new technologies and systems through social experimentation at universities as living laboratories, assessment of impacts with transparency, objectivity, neutrality, legitimation of innovation in society, provision of effective feedback to decision makers, incorporation into institutional design, and contribution to agenda setting at regional, national, and global levels. The model developed is applied to explain the differences observed in the direction and process of innovation on smart cities between Japan, Europe, and the United States. In Japan a strong focus is placed on sophistication of application technologies for extensive use of home appliances and electric vehicles. In Europe an emphasis is placed on establishing a basic infrastructure in which information about the behavior of all the stakeholders is collected and distributed among the stakeholders appropriately so that the various objectives of the electricity grid are achieved in a more equitable way. In the United States a strong interest can be observed in creating and maintaining security through improvement in resilience against physical as well as virtual threats. These asymmetries in conceptualizing and implementing smart cities reflect the differences in how knowledge development, stakeholder networks, and institutional environment interact in dynamic and systemic manners.

Bio: Masaru Yarime is Project Associate Professor of Science, Technology, and Innovation Governance (STIG) at the Graduate School of Public Policy of the University of Tokyo, Japan. He also has an appointment as Honorary Reader in the Department of Science, Technology, Engineering and Public Policy (STEaPP) of University College London, United Kingdom. He has been awarded Abe Fellowship by the United States Social Science Research Council. His research interests focus on public policy, corporate strategy, and institutional design for promoting science, technology, and innovation for tackling societal or grand challenges, including energy, environment, and sustainability. He received B.Eng. and M.S. in Chemical Engineering from the University of Tokyo and the California Institute of Technology, respectively, and Ph.D. in Economics and Policy Studies of Technological Change from Maastricht University in the Netherlands. Previously he worked as Senior Research Fellow at the National Institute of Science and Technology Policy.

Abstract: Philip Beesley’s Living Architecture System Group at the University of Waterloo is exploring new kind of building systems that raise fundamental questions about how architecture might behave in the future. Might future buildings begin to know and care about us? Might they start, in very primitive ways, to become alive? This experimental new work draws together multiple disciplines that include next-generation lightweight structures, interactive robotics, and synthetic biology in pursuit of a kind of architecture that comes close to being alive. Visualizing this responsive architecture presents formidable challenges, and it also offers striking opportunities for thinking and working with complex systems.

Recent projects are composed of towering transparent acrylic arches and flexible silicon, creating quilt-like patterns and composite structures. Custom glasswork vessels housing synthetic biology and translucent filtering elements expand the skeletons to form hovering surfaces that interplay with shadow and light. Distributed sensors and mechanisms are controlled by arrays of microprocessors that give these environments the power to sense and perceive, reacting to the presence of visitors with machinic curiosity and by delicate waves of light, motion and choruses of murmuring sounds. The work is being created by a group of architects, engineers, scientists, and artists from Canada, the U.S., and Europe within the Living Architecture Systems Group. Their design methods are being used to train new generations of architects and engineers, providing them with skills to work with complex and interconnected sustainable environments. For more information: www.lasg.ca

Bio: Philip Beesley is a practicing visual artist, architect, and Professor in Architecture at the University of Waterloo and Professor of Digital Design and Architecture & Urbanism at the European Graduate School. Beesley’s work is widely cited in contemporary art and architecture, focused in the rapidly expanding technology and culture of responsive and interactive systems.

Beesley was educated in visual art at Queen’s University, in technology at Humber College, and in architecture at the University of Toronto. He serves as the Director for the Living Architecture Systems Group, and as Director for Riverside Architectural Press. His Toronto-based practice, Philip Beesley Architect Inc., combines the disciplines of professional architecture, science, engineering, and visual art. The studio’s methods incorporate industrial design, digital prototyping, instrument making, and mechatronics engineering.

His work was selected to represent Canada at the 2010 Venice Biennale for Architecture, and has received distinctions including the Prix de Rome, VIDA 11.0, FEIDAD, Azure AZ, and Architizer A+.

Abstract: In this paper we use a multi-level multi-theory framework to study the influence of compositional, relation, and ecosystem mechanisms on the assembly of scientific teams in interdisciplinary fields. Specifically, we test the effects of these mechanisms on the assembly of interdisciplinary scientific teams using a novel hybrid agent-based and systems dynamics computational model fitted using data collected from 533 teams and 1,696 researchers working in the scientific field of Oncofertility from its inception in 1996 until 2010. We found that, when a new field emerges, team assembly is influenced by the reputation and seniority of the researchers, prior collaborators, prior collaborators’ collaborators, and the prior popularity of an individual as a collaborator by all others. We also found that individuals are more likely to assemble into an Oncofertility team when there is a modicum of overlap across its global ecosystem of teams; the ecosystem is defined as the collection of teams that share members with other teams that share members with the Oncofertility team. The impact of the assembly mechanisms vary over the 15 year period with clear different trends prior and after 2007. It is noteworthy that the changes that appear around 2006-2007 coincide with National Institutes of Health (NIH) funding the creation of the Oncofertility Consortium. This illustrates the impact of external events such as funding on individual motivations to form teams. This research indicates that NIH’s funding initiative to create a national Interdisciplinary Research Center (IRC) on Oncofertility had the intended consequence of facilitating assembly of teams among those universities funded by the IRC, but had the unintended consequence of chilling research collaborations within the larger community of oncofertility not funded by the IRC.

Bio: Alina Lungeanu is a Research Scientist at Population Research Institute at Pennsylvania State University. Her research interests focuses on understanding the social dynamics of collaboration and its impact on performance in various contexts including science, health communities, and business. To address these issues, Alina uses computational social science approaches including advanced social network analytic techniques, agent based modeling, machine learning, and text analytics.

Abstract: View more information about The New ABCs of Research: Achieving Breakthrough Collaborations on Amazon.

Bio: Ben Shneiderman (http://www.cs.umd.edu/~ben) is a Distinguished University Professor in the Department of Computer Science, Founding Director (1983-2000) of the Human-Computer Interaction Laboratory (http://www.cs.umd.edu/hcil/), and a Member of the UM Institute for Advanced Computer Studies (UMIACS) at the University of Maryland. He is a Fellow of the AAAS, ACM, IEEE, and NAI, and a Member of the National Academy of Engineering, in recognition of his pioneering contributions to human-computer interaction and information visualization.

Ben is the co-author with Catherine Plaisant of Designing the User Interface: Strategies for Effective Human-Computer Interaction (6th ed., 2016) http://www.awl.com/DTUI/. His latest book is The New ABCs of Research: Achieving Breakthrough Collaborations (Oxford, February 2016).

Abstract: What happens when massive computing power brings together an ever-growing cross-section of the world’s information in realtime, from news media to social media, books to academic literature, the world’s libraries to the web itself, machine translates all of that material as it arrives, and applies a vast array of algorithms to identify the events and emotions, actors and narratives and their myriad connections that define the planet to create a living silicon replica of global society? The GDELT Project (http://gdeltproject.org/), supported by Google Ideas, is the largest open data initiative in the world focusing on cataloging and modeling global human society, offering a first glimpse at what this emerging “big data” understanding of society looks like. Operating the largest open deployments of streaming machine translation, sentiment analysis, global geocoding, and event identification, coupled with perhaps the world’s largest program to catalog local media, the GDELT Project monitors worldwide news media, emphasizing small local outlets, live machine translating all coverage it monitors in 65 languages, flagging mentions of people and organizations, cataloging relevant imagery, video, and social posts, converting textual mentions of location to mappable geographic coordinates, identifying millions of themes and thousands of emotions, extracting over 300 categories of physical events, using deep learning to quantify visual narratives alongside the textual world, and making all of this available in a free open data firehose of human society. This is coupled with a massive socio-cultural contextualization dataset codified from more than 21 billion words of academic literature spanning most unclassified US Government publications, the open web, and more than 2,200 journals representing the majority of humanities and social sciences research on Africa and the Middle East over the last half century. Used by governments, NGOs, scholars, journalists, and ordinary citizens across the world to identify breaking situations, map evolving conflicts, model the undercurrents of unrest, explore the flow of ideas and narratives across borders, and even forecast future unrest, the GDELT Project constructs a realtime global catalog of behavior and beliefs across every country, connecting the world’s information into a single massive ever-evolving realtime network capturing what’s happening around the world, what its context is and who’s involved, and how the world is feeling about it, every single day. Here’s what it looks like to conduct data analytics at a truly planetary scale and the incredible new insights we gain about the daily heartbeat of our global world.

Bio: Kalev H. Leetaru is one of Foreign Policy Magazine’s Top 100 Global Thinkers of 2013, Kalev is a Senior Fellow at the George Washington University Center for Cyber & Homeland Security and a member of its Counterterrorism and Intelligence Task Force, as well as being a 2015-2016 Google Developer Expert for Google Cloud Platform. From 2013-2014 he was the Yahoo! Fellow in Residence of International Values, Communications Technology & the Global Internet at Georgetown University’s Edmund A. Walsh School of Foreign Service, where he was also an Adjunct Assistant Professor. His work has been profiled in Nature, the New York Times, The Economist, BBC, Discovery Channel and the presses of more than 100 nations, while he has been an invited speaker throughout the globe, from the United Nations to the Library of Congress, Harvard to Stanford, Sydney to Singapore. In 2011 The Economist selected his Culturomics 2.0 study as one of just five science discoveries deemed the most significant developments of 2011. Kalev’s work focuses on how innovative applications of the world’s largest datasets, computing platforms, algorithms and mind-sets can reimagine the way we understand and interact with our global world. More on his latest projects can be found on his website at http://www.kalevleetaru.com/ or http://blog.gdeltproject.org