Shu-Ching Chen - US grants

97-11582 Rishe, Naphtali Barton, David Florida International University (FIU) CISE MII: Infrastructure for Research and Training on High-Performance Heterogeneous Distributed Database Management. This award is to be used to attract and retain minority students, encouraging high-performance database research. Planned is a special mentoring program modeled after the "Affinity Groups" of the University of Texas at El Paso. The groups, consisting of undergraduate and graduate students, post-docs, and faculty members, provide the framework that enables deepening knowledge of a field by procuring a physical setting in a cooperative research-engaging environment. Structured activities facilitate knowledge transfer and serve to ascertain progress. Summer internships for undergraduates are budgeted to involve them in research projects. The affinity groups, within the FIU High Performance Database Research Center at FIU performs research towards the development of a heterogeneous distributed database management system (HDBMS) providing fast integration of disparate data sources and efficient interoperability through the application and utilization of a semantic database management system to define a global schema of the heterogeneous data. A semantic interpretation of SQL is used for efficient interoperability of relational and object-oriented databases. Dynamically-dispatched agent technology is used to interface the distributed heterogeneous databases. Query optimization techniques in the presence of heterogeneous networks are being evaluated and investigated.

A planning meeting will be held to determine the organization and viability of forming a new multi-university Industry / University Cooperative Research Center (I/UCRC) for Data Search, Analytics, and Architectures, with Indiana University as the lead research site and the Florida International University as a research site. The Center will focus on an area of technical and economic importance. It will study the representation, management, storage and analyses of large multi-modal data. Managing large complex data sets and analyzing them is problem common to many industries. The proposed center should benefit significantly from the resources available at the two institutions including unique and extensive facilities funded by NSF on Emerging Techniques for Advanced Information Processing at Florida International University.

Cyberinfrastructure (CI) is a critical enabler of national importance for expanding scientific discovery and industrial applications. To realize CI?s full potential, domain scientists need to easily run their existing applications on the CI available to them. Scientists also need to be able to design their future applications in a way that allows them to take advantage of an ever-changing and growing CI. However, the current technology used to create CI applications presents two problems: (1) they are either too generic and do not provide the right level of abstraction to allow experts in diverse domains to easily code their application logic; or (2) they are too specific, in most cases following a stove-pipe development process, resulting in rigid and expensive solutions that do not promote the reuse of commonalities across domains.

Leveraging an innovative and successful international industry and university partnership called Latin American Grid (LA Grid) for this PIRE project, Florida International University's (FIU) School of Computing and Information Sciences, Florida Atlantic University's (FAU) Department of Computer Science and Engineering, and IBM Research Worldwide (China, France, India, Japan, USA), together with the Instituto Tecnológico y de Estudios Superiores de Monterrey (Mexico), Tsinghua University (China), the Universidad Nacional de La Plata (Argentina), the Barcelona Supercomputing Center and the Universitat Politècnica de Catalunya (Spain), are developing methodologies, platforms, and tools for creating CI applications in a way that eases the application development process and makes the resulting applications more adaptive to future changes of CI. The approach is application-driven and is focused on: (1) supporting CI-enablement for carefully chosen critical application domains, e.g. hurricane mitigation, bioinformatics and healthcare, and (2) developing common methodologies, services and tools for CI-enabled applications in these domains. The technology and tools created by the partners have broad significance and utility to both scientific discovery and industrial/societal applications.

Students from U.S. universities, including underrepresented minorities, are engaged and each participant receives multiple perspectives in each of three different aspects of collaboration as they work with local and international researchers, in academic and industrial research labs, on basic and applied research projects. Consequently, PIRE students are able to participate in the full research pipeline from inception of ideas, through basic research, to practical applications with a wide choice of collaborators and international experiences.

By training a globally engaged workforce and by driving sustainable international partnerships with shared infrastructure and resources, through which faculty, students and industry scientists/engineers collaborate to solve critical and nationally-important complex scientific problems, this activity aims to have a major impact on American competitiveness.

This PIRE project is funded by the Office of International Science and Engineering (OISE) with co-funding from the Office of Cyber Infrastructure (OCI).

The explosive growth in the number and resolution of sensors and scientific instruments, of enterprise and scientific databases, and of internet traffic and activity has engendered unprecedented volumes of data. The frameworks, metadata structures, algorithms, data sets, search and data mining solutions needed to manage the volumes of data in use today are largely ad-hoc. The goal of this proposal is to initiate a new Industry/University Cooperative Research Center (I/UCRC) for Advanced Knowledge Enablement. The proposed center will study the representation, management, storage, analysis, search and social aspects of large and complex data. The proposed center, hosted at Florida International University (FIU), will facilitate research on problems of relevance to industry and in a forum that protects the proprietary nature of the asset. The research program will involve state-of-the art techniques for enhancing semantics, internet technology and knowledge representation techniques for improvements in applications.

The activities proposed by FIU will have a wide ranging impact on the industry for improved application of data management and access. The investigators at the proposed center will leverage their track record of involving FIU?s predominantly Hispanic student population in research with programs such as ?affinity groups? that enable research performed by the graduate and undergraduate students to be shared with other students. The Center also plans to expand opportunities of mentoring and graduating computer scientists from under-represented populations at the BS, MS, and PhD levels. The center plans to build a cohesive structure spanning multiple institutions, in part by enabling extended research visits at partner sites for faculty and doctoral students.

Florida International University?s (FIU?s) proposed second-phase NSF CREST Center for Innovative Information Systems Engineering brings together a multidisciplinary group of researchers, large-scale collaborative relationships, and a broad ecosystem of partners to perform research that will lead to information technologies that help to solve critical societal problems of national priority.

Intellectual Merit: Each of the Center?s mutually-supportive subprojects builds on the strong research foundation established by FIU?s first-phase CREST award and each sets ambitious research goals that will result in the increased competitiveness of FIU?s CISE researchers. By intertwining these multidisciplinary research goals with CREST?s comprehensive education environment and by leveraging the synergistic academic and industry partnerships introduced above, the Subprojects provide one another with strong impetus for cohesiveness and potential for new research findings and educational breakthroughs: Subproject 1: Effective Access to Complex Multimodal Data with Applications in Disaster Mitigation will focus on developing effective techniques for managing and providing access to data that varies in type, source, location, time, and certainty by addressing storage optimization, data management, indexing and search, query techniques, and data presentation. Among its applications, it seeks to develop techniques to get the right information to the right people at the right time, thereby helping to mitigate disasters and to recover from them quickly. Subproject 2: Integrated Approach to Information Processing in Neuroscience focuses on an integrated imaging/signal processing approach that will result in comprehensive views of the human brain in greater depth and detail through faster, affordable, more effective, and less invasive methods. Subproject 3: Human Computer Interaction for Universal Access has a long-term goal of enabling any prospective computer user to interact with computer-based systems, regardless of their disability status and regardless of the interaction challenges derived from the context in which the interaction is taking place. Subproject 4: Complex System Modeling, Analysis, and Realization will focus on essential methodologies for modeling complex systems, a unified underlying semantic model, fundamental methods for compositional model analysis, and model-driven engineering technologies.

Broader Impacts: The Center will build upon the solid research foundation and flourishing educational pipeline developed over the course of FIU's first-phase CREST funding. Its research program will develop effective techniques for managing information, for modeling information, natural, and man-made systems, and for providing access to information while its educational program strives to become the nation?s leader in training underrepresented Ph.D. students in Computer Science and Computer Engineering.

The proposed research areas cross the boundaries of computer science and engineering, information processing, situational awareness, assistive technology, and neuroscience; this integrative approach of research will significantly advance the body of knowledge in these important fields and will make strides to solving some of society?s critical problems.

ACM Special Interest Group of Multimedia, ACM Multimedia has contributed significantly to the advance of all aspects of multimedia research, technologies and applications since 1993. Through the continuous efforts of the community, ACM Multimedia has become a dynamic and comprehensive program for publication, education, and interaction, including presentation and discussion of research papers, participation in tutorials, demos, doctoral symposium, industrial grand challenge competitions, and art exhibitions. All these activities provide a unique opportunity for students to share their knowledge, experience, and their current research with internationally recognized researchers from both academia and industry. ACM Multimedia 2011 (ACM MM 2011) is to be held in Scottsdale, Arizona, November 28 - December 1, 2011 and is expected to attract many US and international attendees from academia and industry.

This award provides support for ACM MM 2011 education related events, namely the Doctoral Symposium, Face-to-face Meeting with Leading Researchers, the Open Source Competition and partial travel expenses and registration for about 20 US-based students; in particular, female and minority students and students presenting in the doctoral symposium and participating open source software competition. A Female Student Mentoring Workshop will be supported by a separate funding from the ACM SIGMM.

The intellectual merit includes the opportunity for students to learn about the cutting edge research and interact with experts in the top multimedia conference. The broad impact is to train and develop the future generation of leaders and workforce in this critical field, as well as enhancing the participation of women and minority students in multimedia research.

The ACM Multimedia proceedings are published by ACM. The student award application procedure and results will be announced at the ACM MM 2011 conference website (http://www.acmmm11.org).

Proposal #: CNS 11-26619
PI(s): Rishe, Naphtali D.; Chen, Shu-Ching; Christidis, Evangelos; Li, Tao; Zhao, Ming
Institution: Florida International University
Title: MRI/Dev.: An Integrated, Geospatial Analytics Research Instrument
Project Proposed:
This project, developing an integrated, high performance instrument designed for the domain experts, focuses its domain on environment from which researchers can easily process and store spatial and related data, visualize and explore data relevant to their domains, and analyze data of interest via analytics of their choosing. This instrument will provide a suite of cloud services and user-centric analytic technologies via a Disaster Dataspace Services Cloud (DDSC), open-standard APIs, and cutting-edge data visualization capabilities. The Instrument will utilize a large-scale, optimized infrastructure to deliver high levels of throughput and responsiveness, including an improved Hadoop/MapReduce architecture to enable decision-support and information discovery queries on massive amounts of structured and unstructured data. The proposed multidisciplinary research includes:
- Several areas of Computer Science research, including query and data quality control algorithms on heterogeneous, multisource streaming data, automated discovery approaches, intelligent query/search modeling, GIS, data mining, moving objects, and scientific data visualization;
- Algorithms in data quality control and indexing on heterogeneous, multisource streaming data, and knowledge discovery algorithms with spatially aware information, such as rare event and spatio-temporal change and trend detection; and
- Instrument?s applicability in the decision-making process in various fields, especially in disaster mitigation.
Broader Impacts:
This project, in a minority-serving institution, exhibits strength in broader impacts that may be found In leveraging a number of successful ongoing projects, most notably in computer science and geo-spatial sciences. The instrument carries potential to transform the decision-making process in disaster mitigation. The enabled research should benefit applications in environmental monitoring, transportation, education, public health and safety. The instrument would be used in classroom. Planned is recruitment that targets underrepresented minority students (Hispanics) through innovative research and quality education programs.

The disruption of business caused by a wide-spread disaster such as a hurricane or an earthquake has a huge impact on the economy. A key reason that businesses fail to operate after a disaster is the lack of information on the availability of power and supplies, the road conditions, and so on. While there is no shortage of disaster planning or recovery toolkits and disaster information or news portals, currently there are no effective solutions that will help businesses to revive the business ecosystem interrupted by the disaster.

The goal of this project is to design and develop data-driven solutions to address critical information exchange needs in disaster affected public-private networks and to achieve intelligent (context-aware and user-specific) information delivery, analysis, sharing, and collaboration among both private and public sector participants in disaster management. The project is conducting research on: (1) design and develop effective information integration and summarization methods to help users improve situational awareness; (2) design and develop intelligent information delivery techniques to help users quickly identify the information they need; and (3) design and develop automatic techniques for dynamic community generation. These research components constitute a holistic effort to effectively organize, discover, search and disseminate real-time disaster information and create a collaborative platform for preparedness and recovery that helps disaster impacted communities to better understand what the current disaster situation is and how the community is recovering. The developed techniques are designed to be all-hazard capable so that they can be used in hurricane, earthquake, terrorism, or other unanticipated disaster events, and they can also be applied to other information management domains.

The project fosters the international collaboration between the Florida International University (FIU) team and the Japan team in disaster management and its broader impact is also aligned with the national goal of broadening participation in education. FIU is number one in the nation in awarding bachelor's and master's degrees to Hispanic students and its history of involving the participation of underrepresented groups in research efforts will be leveraged during the course of this project.

Center for Aquatic Chemistry and the Environment

With National Science Foundation support, Florida International University will establish the Center for Aquatic Chemistry and the Environment. Human-derived environmental contaminants consist of antibiotics and pharmaceuticals, mercury, black carbon, and fossil fuels. These stressors are recognized as having significant effects on ecosystems and biota as well as on human wellbeing. It is critical to understand the biogeochemical processes that govern the fate of these compounds and their impacts on the ecosystem. Center for Aquatic Chemistry and the Environment research will address the sources, transport, transformation and ecosystem responses to contaminants, pollutants and other natural stressors, under changing land-use and environmental conditions.

The Center for Aquatic Chemistry and the Environment will generate significant new knowledge regarding contaminants and pollutants in aquatic environments, as well as produce innovative methodologies for detecting and assessing contaminant quantities and impacts, including the use of molecular detection techniques. The proposed research will advance current efforts on the biological effects, transport, transformation and distribution of contaminants in the environment into new collaborative research areas that investigate the sources and transport of contaminants and pollutants in aquatic systems.

The Center articulates three research subprojects organized around environmental chemistry, biogeochemistry, ecology and data synthesis and modeling as they pertain to regional water resources. The first subproject will advance the effectiveness of approaches for the analysis of traditional pollutants, develop methodologies for the characterization and quantification of previously unknown contaminants and extend the applicability of molecular biology methodologies to assess environmental stressors to aquatic organisms across land-use boundaries. The second subproject uses new sensing techniques to determine biogeochemical cycles including contaminant sources, storage, transport and transformations. The third research subproject develops data analytic methods to enable synthesis across large, complex data sets to allow holistic effects assessment for understanding South Florida's aquatic ecosystem.

The Center for Aquatic Chemistry and the Environment will establish innovative opportunities for students to experience authentic and socially relevant environmental research and foster their development as future STEM professionals.

The NSF Convergence Accelerator supports team-based, multidisciplinary efforts that address challenges of national importance and show potential for deliverables in the near future.

The broader impact/potential benefits of this Convergence Accelerator Phase I project will address a crucial national problem by preparing the nation's workers and businesses in the Architecture, Engineering, and Construction (AEC) industries for an increasingly automated future workplace. This convergent research and development project involves researchers in architecture, construction, engineering, computer science, STEM education and economic development, as well as industry collaborators from the robotics, architecture, engineering, construction and software industries. Its Phase 1 deliverables will benefit businesses, workers and professionals in the AEC industry cluster, as well as regional and national economic development policy. Phase 1 provides the platform for critical solutions: maximizing employment opportunity, minimizing job displacement, and improving national economic competitiveness in the AEC industries. Improving AEC industry performance also promises solutions leading to a more energy efficient and sustainable built environment.

This Convergence Accelerator Phase I project will contribute to research and application of Artificial Intelligence (AI) and immersive virtual environments in education as well as examining economic impacts of automation technology adoption in the AEC industries. The rapid adoption of AI and automation promises new employment and business opportunities, but will also create job displacement and business disruption. The Project's Phase 1 research objectives are to develop 1) a prototype interactive virtual reality robotics training and educational software package, and 2) a new model to measure the economic impact of automation adoption. Phase 1 will provide a platform for an immersive virtual software to teach new skills, improve process workflows, and increase efficiency in the AEC industries. Integrating advanced technologies including Reinforcement Learning, Computer Vision, Augmented and Virtual Reality, the project will advance methods of remote and on-site training for a large segment of employees in the AEC industries. By applying STEM learning strategies, the project will contribute to understanding how people learn in technology rich environments and bridge the gap between technology advancement and application to practice. The Project's economic analysis will utilize a "bottom-up" approach to estimating the employment impacts resulting from the adoption of AI and robotics.

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.

Honey bees are among the most successful invasive organisms worldwide, both on and off islands. They play a key role as pollinators in agricultural systems worldwide, but are also threatened by human activities. This award supports the first conference to examine one strain of non-native honey bee, the Puerto Rico Gentle Africanized honey bee, through the lens of invasion biology and island biogeography. The conference is timely for two reasons. First, the introduction and radiation of invasive organisms, and threats to honey bee health, continue unabated. Second, invasive organisms - and honey bees in particular - have a critical impact on global food security. In this conference, researchers will communicate new findings that aim to stimulate their research and that of their students and interact directly with stakeholders who can apply basic research findings to improve management decisions. The new research directions and improved management decisions are expected to translate into economic benefits for a much-challenged Puerto Rico island economy. Additionally, because the invited participants include a diverse set of student participants from the University of Puerto Rico, this conference has the potential to broaden participation in STEM.

The amount and type of data available for honey bees, including the Puerto Rico Gentle Africanized honey bee, are unparalleled. However, bee researchers do not use an invasive biology perspective, and invasive biology studies typically do not examine the honey bee as a model. The adaptation of Africanized honey bees to the island of Puerto Rico is an example of the changes that can occur to invasive organisms and their ecosystem during island colonization. The invasion process impacts the invading as well as the resident species and the ecosystem in which they navigate. One of the advantages of studying island populations is that such adaptive processes are accelerated. Moreover, adaptive processes may show similar patterns across species and as such, data from island populations can be particularly useful to develop and test models of invasion biology. This three-day conference will develop an integrative analysis approach to honey bee invasions using various types of data generated by different research areas and approaches to invasion biology. These include genomics, morphology, behavior and ecology. On the first day, all participants will give presentations. For the second day, attendees will visit field sites to observe the honey bee population established on the island of Puerto Rico. On the third day, attendees will form breakout groups for round table discussions leading to a strategic plan on research directions, resources, and policy advice on bees and other invasive organisms on islands.

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.

This COVID-19 RAPID research program will focus on addressing the shortage of essential medical supplies, Personal Protective Equipment, and crucial medical technologies. A surge in demand for specialized healthcare has also created a shortage of skilled medical professionals capable of operating highly technical machines while protecting themselves and others against this dangerous virus. Thus, providing rapid training for caregivers and increasing the supply of Personal Protective Equipment and medical technology is an immediate priority for combating this unprecedented pandemic. This project will leverage the research and technology currently under development in a National Science Foundation Convergence Accelerator project to provide an easy to use and access training application for caregivers, as well as networking capacity for problem-solving among stakeholders. This project will also build and foster partnerships among the healthcare community, medical equipment manufacturers and distributors, and grassroots efforts to rapidly deploy prototypes as it strives to create awareness of the project and its novel features.

The specific goals of this project are to provide training support, problem-solving resources, and professional networking for idea exchanges for healthcare professionals, caregivers, and technologists that are on the frontlines in the fight against COVID-19. Artificial Intelligence techniques such as deep learning and self-adaptive autonomous systems will be used to develop an intelligent knowledge network to support virtual communities, as well as, create Augmented Reality technologies for delivering efficient and engaging virtual training. Thus, the research objectives of this project include: 1) development of an Augmented Reality training mobile application for caregivers and technologists responding to the COVID-19 pandemic; 2) deployment of an online repository for equipment problem-solving resources; and 3) development of a professional networking application to disseminate research and best practices in the fight against COVID-19 for all stakeholders engaged in addressing the pandemic. The project's overarching focus is to create a web application with mobile Augmented Reality capability for training healthcare professionals at any location and time, in order to improve access to training with the medical equipment and increase the efficiency and reach of safety training. The project team will advance the knowledge base in computer science and spatial computing as it creates its Artificial Intelligence-powered Augmented Reality training. The team will disseminate its findings and technology through relevant scholarly conferences and journals.

This RAPID award is made by the Convergence Accelerator program in the Office of Integrative Activities using funds from the Coronavirus Aid, Relief, and Economic Security (CARES) Act, and is associated with the Convergence Accelerator Track B: Artificial Intelligence and Future Jobs and National Talent Ecosystem.

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.

Large and unpredictable stressors like new diseases are impacting practically all species with increasing frequency and strength. Understanding how species respond often relies on studies of genetics. Islands are a good place to study such responses because a large fraction of resident species are usually impacted. The COVID pandemic has disrupted the ability of many students – especially those from underrepresented groups -- to get the training and mentoring they need to study genetic responses to stressors. This workshop will help fix that problem by providing students from Puerto Rico and southern Florida with cutting edge skills for analyzing and interpreting genetic data that they may find challenging.

The workshop will help ensure the continued academic progress of participants from STEM underrepresented communities by engaging them in research activities that can be undertaken when most laboratory and fieldwork is limited. Workshop participants will acquire skills to analyze gene expression data from their independent research projects on response of organisms across the span of biological diversity to biotic and abiotic stressors. A high degree of “hands-on” virtual interaction between participants and instructors will be used as a platform. This will be followed with email and chat group communications and coupled with posted recorded sessions and associated supporting instructional materials. Results are likely to yield new insights about how organisms adapt to new environmental challenges.

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.

The COVID-19 pandemic has resulted in huge amounts of confirmed cases and deaths both in the United States and globally. The nation experienced grave repercussions to citizens’ lives, health, and the economy. Due to its high contagiousness, policies such as quarantine and lockdowns were put in place to slow the virus’ rapid spread. Some major challenges are identifying vulnerable communities to provide immediate help and determining policies that are effective in slowing down the spread with minimal adverse effects on people’s livelihood, mental health, and the economy. This project aims to develop tools that can locate communities in crisis, identify their problems and demands, and predict pandemic transmission trends and impacts in diverse communities based on mobility and social media data. The developed tools and technologies are critical for effective disaster management and pandemic recovery. Furthermore, pandemic and other natural disasters’ co-occurrence is even more challenging given that mass evacuation and sheltering processes may cause a spike in cases of transmissible pandemic diseases. This project will develop new technologies that can aid emergency managers under a pandemic scenario based upon our previously developed tools for natural disaster management.

The proposed research provides potential solutions to solve crucial disaster information management challenges for COVID-19, future pandemics, and compound disasters while leveraging the team's previous work. Furthermore, the proposed techniques will help better understand the disaster situation to assist the preparation and recovery for a broad range of communities, including minority and low-income populations. This project will also have the potential to have societal and economic impacts by providing the most accurate information on pandemics and compound disasters to prevent unexpected losses. The developed solutions could be later expanded for other disaster and information management. This project fosters collaboration between the Florida International University (FIU) and the University of Tokyo, as well as institutions across the public and private sectors (including the cities of Miami-Dade, Florida, and Tokyo, Japan), to develop advanced techniques for effective emergency response and management for COVID-19, future pandemic, and compound disasters. This work’s broader impact is aligned with the national goal of building smart and connected communities by developing innovative disaster information exchange and analysis tools with real-life data. In addition, FIU is one of the nation’s leading minority-serving research universities and ranks first in awarding undergraduate and graduate degrees to Hispanic students. The research findings of this project will be disseminated through workshops, publications, and presentations.

This project is a joint collaboration between the National Science Foundation and the Japan Science and Technology Agency.

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.

The global economy is being rapidly reshaped by sophisticated robots that enhance human dexterity, visual perception, speed, and strength. This intense focus on creating and implementing new automation technologies is bringing disruptive changes to job markets. In Architecture, Engineering, and Construction (AEC) industries, robotics automation is transforming jobs at a speed and scale never experienced before, leading to new demand for skilled workers in advanced technologies and robotics. Addressing the learning needs of AEC students, future professionals, and industry workers is critical for ensuring the competitiveness of a large proportion of the US workforce. Our proposal is inspired by recent technological achievements in self-adaptive, data-driven, and autonomous systems for virtual learning. These technologies bear the promise to transform education by personalization and tailoring the learning content and sequence for differences in ability, experience, and sociocultural background. Leveraging these technologies, we will research, develop, and test a personalized learning tool for delivering an industrial robotics curriculum to prepare the next generation of the AEC workforce. <br/><br/>We plan to achieve this goal with five educational and scientific innovations: 1) Artificial Intelligence (AI)-assisted Adaptive Intelligent Learning System 2) AI-assisted coaching, 3) Novel curriculum content and delivery in virtual reality, 4) Game-based learning user experience, and user interface and 5) AI-enabled learning analytics. The design and implementation of this project will contribute to technological advancement in AI-assisted Adaptive Intelligent Learning systems and our ability to apply state-of-the-art AI and Natural Language Processing techniques for the analysis of learning data. Advancing this frontier is critical for our ability to evaluate learner data at scale. Further, our development of AI-Assisted coaching will lead to broadly applicable advancements in intelligent tutoring systems. It includes a novel capacity to detect and identify learner failure patterns and to apply known remediation to improve learning outcomes. In addition, the design and implementation of a curriculum that dynamically changes in response to learner input, skill level, and advancement toward learning goals can bring new pedagogical approaches to curriculum development, reshaping our current practices. Finally, our project will enrich learning analytics by integrating biometric and performance data leading to a greater understanding of the learning process.<br/><br/>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.