Albert Esterline - US grants

EIA-0002217
Kim, Jung H.
North Carolina A&T State University

MII: Infrastructure for Intelligent Mobile Information Systems

This proposal involves the creation of an infrastructure for research and graduate education in Intelligent Mobile Information Systems (IMIS) at North Carolina A&T State University. The infrastructure will support the efforts by the Department of Computer Science, the Department of Electrical Engineering and t he College of Engineering to enhance the effectiveness of North Carolina A&T State University as a pipeline to graduate study by African-Americans in computer science and computer engineering. The proposal outlines an aggressive mentoring program oriented toward encouraging African-American students to continue to graduate school. This will involve identifying undergraduate students with high academic performance and recruiting them to participate in the IMIS research program.

North Carolina Agricultural and Technical State University (NCAT) proposes a novel, 2-way collaboration between HBCUs and research universities in order to increase the number of African Americans who obtain graduate degrees and enter faculty and research careers in computing. Alliance participants include HBCU's - NCAT, Bennett College, Dillard University, Jackson State University, and Norfolk State University - and majority, research universities - the University of Colorado, Georgia Institute of Technology, and Virginia Polytechnic Institute and State University. North Carolina State and the United Negro College Fund Special Programs will provide consulting.

The program will have three components. Firstly, it will strengthen undergraduate computing programs at the HBCUs by changing curriculum and pedagogy to include collaborative learning environments, discovery-based and hands-on learning. The Alliance will create research and educational experiences for undergraduates and graduate students providing authentic learning in the form of design, research, industry and workshop experiences. The students will be given social, academic, and career support through peer-, step- and faculty-student mentoring. Secondly, Alliance activities will institutionalize two-way research opportunities and teaching partnerships for students and faculty. This will be done with the development of joint research and teaching, both remotely and through student and faculty visits and exchanges. Faculty will partner on research teams and graduate student supervision. Thirdly, the Alliance will support ongoing research partnerships among faculty members and will provide pathways for HBCU students to pursue faculty careers after graduation. All of these activities are based on a unique, dual feeder model that allows some HBCU undergraduates to pursue Master's study at a research intensive HBCU (NCAT) before going on to Ph.D. study at a research university. The collaborations developed under this Alliance will be meaningful, two-way relationships that will be built from the PIs' experience in facilitating collaborations between research universities and HBCUs.

The Targeted Infusion Project entitled - Developing a Social Computing Program at North Carolina A&T State University - has the goal to establish a Bachelor of Science in Computer Science (BSCS) concentration in Social Computing. Graduates with training in social computing are prepared to inform empirical research, professional practice, and public and social policy as it pertains to both information technology and social change in a globalized society.

The project is a joint effort of the Departments of Computer Science, Mathematics, and Sociology and will strengthen partnerships among the departments. The project will create a new, interdisciplinary curriculum model for a BSCS concentration in Social Computing. Such a curriculum will allow students in the field of computer science to learn about social computing and social computational systems, allow students in mathematics to apply mathematics to social computing, and allow students in sociology and psychology to learn about social computational systems. New courses such as introduction to social computational systems, mathematics for social computing science, and social issues relating to social computing will be developed. The curriculum and instructional materials developed by this project can be adopted by faculty at other colleges and universities. The project team will host a workshop at the ASE/IEEE International Conference on Social Computing. The team will disseminate instructional materials for the new courses and introduce the software tools that were developed in the social computing lab. This project will increase the educational and career opportunities for African American students majoring in computer science, mathematics, and sociology at NCA&T State University.

This funding establishes a new Research Experiences for Undergraduates (REU) Site at North Carolina A&T University. Undergraduate students from across the nation will participate in summer research focused on cyber identity. The digitization of our everyday lives has increased the need to establish safer and more secure ways to provide accurate identification for online transactions and to protect personal information. The students will participate in research projects that investigate methods to help users control the security of their digital identity. Cyber identity research and its applications hold great promise for establishing trusted online identity, reducing identity theft, and ensuring privacy. The challenges of cyber identity research provide an exciting opportunity to bring together faculty researchers and students to investigate fundamental principles and design strategies in computing systems to develop real-world, secure systems that we can all trust. This project is co-funded by the Cyber Corps (R): Scholarship for Service Program.

The research projects explored in this site focus on open research challenges in the areas of computational frameworks, attacks on cyber identity, and mitigation strategies. Impacts of the research include an advanced computational framework for numerical and conceptual identities, extended webIDs for online identity and login, new approaches to alleviate replay attacks in Biometric based Access Control Systems, improved analytics for authorship analysis of code associated with malware, and enhanced cyber attack detection and attribution to attackers. The students will use of state-of-the art facilities and devices and work with faculty mentors with significant expertise in cyber identity research. The site will focus on recruiting under-represented minorities, particularly drawing on a large network of colleges in the region around the host institution. The students will participate in professional development activities that make them more aware of graduate school and professional aspects of a computing career. The project should contribute to the development of a diverse scientific workforce with expertise in areas critical to national security in the evolving global society of the future.

Food insecurity occurs when individuals have limited access to safe and nutritious food for an active, healthy life. It is a global issue that affects a significant number of individuals domestically. To address it, humanitarian organizations involved in hunger relief work collaboratively with the government and private sector. Humanitarian organizations rely on uncertain sources of supply, respond to uneven and variable needs, and make careful decisions regarding how to use scarce resources. These organizations generate data on a massive scale about food supply, food distribution, and food need, which helps them to perform their function. Challenges arise from not only the uncertainty of supply and demand but also from variations in information collected by different organizations. This National Science Foundation Research Traineeship (NRT) award to North Carolina Agricultural and Technical State University will develop an innovative, interdisciplinary training model in data science designed to grow the workforce that will help these organizations analyze their efforts and improve the provision of food aid at the local, state, and federal level. This traineeship seeks to provide a unique and comprehensive training experience for a total of 50 masters and doctoral students, including forty-five (45) funded trainees, by combining disciplines in industrial and systems engineering, computer science, mathematics, agricultural economics, sociology, and public policy.

At present, no formal training mechanism exists by which students can acquire the interdisciplinary knowledge needed to derive insight from heterogeneous big data generated by the food aid supply chain because (a) traditional STEM student training in this area does not include the public policy perspective and (b) working with big data is limited to a subset of the STEM population. To answer this need, this project's research and education efforts will use existing data from the domestic humanitarian hunger relief supply chain as the basis for an innovative, evidence-based, scalable approach to training its future workforce. Our program will provide a model for preparing the next generation of data scientists employed in the humanitarian sector. The overarching goal is two-fold: (i) to create a sustainable training model that improves the preparation of students in STEM fields to pursue careers in data science and (ii) to provide training experiences that will orient students on the use of big data to inform and potentially transform the delivery of services that have societal impact. We propose to leverage big data to reduce uncertainty in this supply chain and drive more effective modes of food distribution by addressing information inequality, visualization, and information-driven decision modeling. The program will feature a summer training institute, industry/academia research clusters, professional development seminars, and ongoing evaluation of the training model. Students who complete all requirements will obtain new knowledge and skills with respect to big data collection, interpretation, and its use in decision-making; obtain new knowledge about using big data to address multidisciplinary problems in hunger relief and food security; and obtain the training necessary to pass an industry-level certification exam. At North Carolina Agricultural and Technical State University, the award will help to establish a new certificate-based interdisciplinary graduate training program in data science. In the larger humanitarian sector, the research generated by this work will improve access to food by reducing information inequality, enhance operational decision-making by providing real-time adaptable visualization of information, and create new information-driven decision models that can positively impact food aid policy and operations.

The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The Traineeship Track is dedicated to effective training of STEM graduate students in high priority interdisciplinary research areas, through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs.

This project is co-funded by the Alliances for Graduate Education and the Professoriate (AGEP) program. AGEP funds research and the development, implementation, and investigation of models to transform the dissertation phase of doctoral education, postdoctoral training and/or faculty advancement of historically underrepresented minorities (URMs) in Science, Technology, Engineering and Mathematics (STEM) and/or STEM education research.

Networks are ubiquitous and are a part of our common vocabulary. Network science and engineering has emerged as a formal field over the last twenty years and has seen explosive growth. Ideas from network science are central to companies such as Akamai, Twitter, Google, Facebook, and LinkedIn. The concepts have also been used to address fundamental problems in diverse fields (e.g., biology, economics, social sciences, psychology, power systems, telecommunications, public health and marketing), and are now part of most university curricula. Ideas and techniques from network science are widely used in making scientific progress in the disciplines mentioned above. Networks are now part of the public vocabulary, with news articles and magazines frequently using the term "networks" to refer to interconnected entities. Yet, resources for effective use of techniques from network science are largely dispersed and stand-alone, of small scale, home-grown for personal use, and/or do not cover the broad range of operations that need to be performed on networks. Compositions of these diverse capabilities are rare. Furthermore, many researchers who study networks are not computer scientists. As a result, they do not have easy access to computing and data resources; this creates a barrier for researchers. This project will develop a sophisticated cyberinfrastructure that brings together various resources to provide a unifying ecosystem for network science that is greater than the sum of its parts. The resulting cyberinfrastructure will benefit researchers and students from various disciplines by facilitating access to various tools for synthesizing and analyzing large networks, and by providing access points for contributors of new software and data. An important benefit of the system is that it can be readily used even by researchers who have no formal training in computer programming. The cyberinfrastructure resulting from this work will foster multi-disciplinary and multi-university research and teaching collaborations. As part of this project, comprehensive education and outreach programs will be launched by the participating institutions, spanning educators and K-12 students. These programs will include network science courses with students from minority and under-represented groups, and students at smaller institutions who do not have easy access to high performance computing resources.


Resources for doing network science are largely dispersed and stand-alone (in silos of isolated tools), of small scale, or home-grown for personal use. What is needed is a cyberinfrastructure to bring together various resources, to provide a unifying ecosystem for network science that is greater than the sum of its parts. The primary goal of this proposal is to build self-sustaining cyberinfrastructure (CI) named CINES (Cyberinfrastructure for Sustained Innovation in Network Engineering and Science) that will be a community resource for network science. CINES will be an extensible and sustainable platform for producers and consumers of network science data, information, and software. CINES will have: (1) a layered architecture that systematically modularizes and isolates messaging, infrastructure services, common services, a digital library, and APIs for change-out and updates; (2) a robust and reliable infrastructure that---for applications (apps)---is designed to accommodate technological advances in methods, programming languages, and computing models; (3) a resource manager to enable jobs to run on target machines for which they are best suited; (4) an engine to enable users to create new workflows by composing available components and to distribute the resulting workload across computing resources; (5) orchestration among system components to provide CI-as-a-service (CIaaS) that scales under high system load to networks with a billion or more vertices; (6) a digital library with 100,000+ networks of various kinds that allows rich services for storing, searching, annotating, and browsing; (7) structural methods (e.g., centrality, paths, cuts, etc.) and dynamical models of various contagion processes; (8) new methods to acquire data, build networks, and augment them using machine learning techniques; (9) a suite of industry- recognized tools such as SNAP, NetworkX, and R-studio that make it easier for researchers, educators, and analysts to do network science and engineering; (10) a suite of APIs that allows developers to add new web-apps and services, based on an app-store model, and allows access to CINES from third party software; and (11) metrics and a Stack Overflow model, among other features, for producers and consumers to interact (in real-time) and guide the evolution of CINES. CINES will enable fundamental changes in the way researchers study and teach complex networks. The use of state-of-the-art high-performance computing (HPC) resources to synthesize, analyze, and reason about large networks will enable researchers and educators to study networks in novel ways. CINES will allow scientists to address fundamental scientific questions---e.g., biologists can use network methods to reason about genomics data that is now available in large quantities due to fast and effective sequencing and the NIH Microbiome Program. It will enable educators to harness HPC technologies to teach Network Science to students spanning various academic levels, disciplines, and institutions. CINES, which will be useful to researchers supported by many NSF directorates and divisions, will be designed for scalability, usability, extensibility, and sustainability. This project will also advance the fields of digital libraries and cloud computing by stretching them to address challenges related to Network Science. Given the multidisciplinary nature of the field, CINES will provide a collaborative space for scientists from different disciplines, leading to important cross fertilization of ideas.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.