Eduardo "Ed" Salas, Ph.D. - US grants
Affiliations: | Department of Psychological Sciences | Rice University, Houston, TX |
Area:
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The funding information displayed below comes from the NIH Research Portfolio Online Reporting Tools and the NSF Award Database.The grant data on this page is limited to grants awarded in the United States and is thus partial. It can nonetheless be used to understand how funding patterns influence mentorship networks and vice-versa, which has deep implications on how research is done.
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High-probability grants
According to our matching algorithm, Eduardo "Ed" Salas is the likely recipient of the following grants.Years | Recipients | Code | Title / Keywords | Matching score |
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2003 — 2007 | Salas, Eduardo Fiore, Stephen (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Slc Catalyst: Florida Alliance For the Study of Expertise @ University of Central Florida The "Florida Alliance for the Study of Expertise" (FASE) is designed to advance a science of Expertise Studies throughout the United States and throughout the world. FASE leverages the capabilities of world leaders in the study of expertise who are affiliated with Florida Universities with the overarching goal of understanding the nature and development of expertise. This funding will support the creation of a technical and collaborative infrastructure that will unite a multi-university and multi-disciplinary research partnership for the purposes of understanding and encouraging the scientific study of expertise. To understand learning at a fundamental level one must examine learning phenomena up to the level of expert achievement and theories of learning must take such phenomena into account. To address this need, FASE will integrate differing scientific methodologies to enhance the necessary complementarity of laboratory and field research. FASE will support collaboration across universities and across methodologies with the goal of fostering a synergistic combination of methods where the benefits of scientific approaches can be leveraged to improve hypothesis generation and testing along with theory development in a broader context. FASE focuses on the entire human system and how experience alters this system to produce meaningful learning that leads to the highest levels of achievement. FASE will facilitate the understanding of how it is that expert knowledge is acquired in order to determine both how it can be preserved and how others may be taught to engage in the requisite activities to similarly acquire such knowledge. |
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2006 — 2010 | Hughes, Charles (co-PI) [⬀] Harrison, Glenn Rutstrom, E. Elisabet Salas, Eduardo Fiore, Stephen (co-PI) [⬀] |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of Central Florida Our research effort has two overarching goals: the first epistemological and the second methodological. Our epistemological goal concerns naturalistic decision making (NDM) in the context of complex domains. Our application is an important economic problem where the evaluation of the social welfare consequences often leads to conflicting positions by experts and affected non-expert citizens. We argue that much of this conflict is created because experts and non-experts use different cognitive processes when evaluating and forming decisions. We propose a simulation technique designed to facilitate a convergence in these cognitive processes, and hypothesize that this will lead to a reduction in the degree of conflict. We have two methodological goals. First, we will use interactive, immersive virtual-reality (VR) simulation technologies to recreate, in a controlled environment, the rich array of cues and information relied upon by decision-makers in naturalistic domains. The application we have selected, forest management policies, is a good example of a decision environment with a rich set of information cues and interactions, and where the experience of experts is expected to matter in significant ways to the decisions made. Our second methodological goal is to blend the techniques of controlled economics experimentation with those of NDM. The power of experimentation lies in replicability and control, and by extending these capabilities through the power of VR simulations, this research will allow us to explore issues in decision making in ways heretofore not feasible. We will compare decisions made by participants using standard state-of-the-art questionnaires, where scenarios are described in words and with pictures, to those made using the interactive experience of the VR technology. We hypothesize that the differences in values and decisions between experts and non-experts is smaller with the immersive, interactive VR environment than with the standard word and picture descriptions. |
0.97 |
2008 — 2015 | Loughry, Misty Ohland, Matthew [⬀] Layton, Richard Woehr, David Salas, Eduardo |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ Purdue University Engineering - Other (59) |
0.972 |
2009 — 2011 | Kapucu, Naim (co-PI) [⬀] Burke, Shawn Dechurch, Leslie Salas, Eduardo |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Voss: Creating Functionally Collaborative Infrastructure in Virtual Organizations @ University of Central Florida This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Organizations are restructuring into collaborative systems in order to address complex problems by combining expertise distributed across business functions, knowledge specialties, and geographic locations. Often times these systems face complex and multifaceted goals requiring distinct teams to coordinate their efforts and compile crucial information distributed across a network of teams (i.e., multiteam system). This project will render an understanding of the requisite motivational, cognitive, affective, and behavioral dynamics that enable virtual organizations to function effectively. |
0.97 |
2010 — 2013 | Salas, Eduardo Fiore, Stephen (co-PI) [⬀] Burke, Shawn |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ University of Central Florida The question of shared leadership is growing more important as complex world issues increasingly require distributed collaboration. Organizational researchers lack an understanding of the multiple kinds of leadership roles that virtual teams rely on and of the optimal balance of these roles. Previous research has confounded virtuality and distribution or included only a few combinations of these characteristics. |
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2021 — 2027 | Salas, Eduardo Pearson, Yvette Wettergreen, Matthew |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
@ William Marsh Rice University The project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at Rice University, Texas Southern University, Prairie View A&M University, and Jackson State University. Across all four partner institutions, the project will support roughly 220 academically talented domestic students from low-income backgrounds with demonstrated financial need to pursue and complete master's degrees in engineering, computer science, mathematics and data science. Students will select from among disciplines in one of three technical tracks: biotechnology; sustainability and resilience; and digital twinning. (The latter refers to the use of a virtual model of a system that is updated with real-time data and used to support simulations and decision making.) The core of the project is a carefully crafted combination of scholarships, academic and career development, mentoring, and cohort development based on preliminary student data and the literature on scholar success and workforce development. The programmatic elements are structured to remove barriers and to foster students’ successful matriculation, graduation, and entry into the workforce. Rather than focus on traditional education models that often set up a dichotomy between research experiences and internships that lead to singular career paths, the Flexible Internships-Research-Education (FIRE) model employed here is designed to give students experiences that integrate both research and internships, facilitated by workforce partners, at both the undergraduate and graduate level. Towards this end an important component of the project is a partnership with the Engineer Research and Development Center, a major employer specializing in civil and military engineering, geospatial sciences, water resources, and environmental sciences. |
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2022 — 2026 | Salas, Eduardo Unhelkar, Vaibhav Vasant |
N/AActivity Code Description: No activity code was retrieved: click on the grant title for more information |
Collaborative Research: Sch: An Ai Coach to Enhance Surgical Teamwork in the Cardiac Operating Room @ William Marsh Rice University Cardiac surgery is often needed to address some of the most serious heart problems, resulting in administration of more than 900,000 cardiac procedures each year. The cardiac Operating Room (OR) is a complex environment where healthcare professionals from multiple disciplines -- including surgeons, anesthesiologists, perfusionists, and nurses -- collaborate to administer this life-critical care. To successfully administer care, all members of the surgical team are expected to perform their tasks in lockstep and with full awareness of dynamic situations encountered during surgery. However, achieving such ideal teamwork is difficult in the complex environment of cardiac OR, where human performance is adversely affected by factors such as high workload, fatigue, and interruptions or disruptions during surgery. This project addresses an urgent need for mitigating these preventable human errors and improving patient safety through the design of an Artificial Intelligence (AI)-enabled coaching system (AI Coach) for monitoring, assessing, and enhancing surgical teamwork in the cardiac OR. Central to the functioning of the AI Coach will be a set of novel machine learning and explainable artificial intelligence algorithms to computationally generate interpretable feedback and interventions for enhancing surgical teamwork based on multimodal sensor data. The project will train students in the multi-disciplinary research area of Smart Health. The project will increase public engagement with AI, by incorporating the research results into a planned museum exhibit on human-AI collaboration.<br/> <br/>The project’s overarching goal is to design the AI Coach system comprised of multimodal sensing hardware, data-driven algorithms, and a user interface to enhance surgical teamwork in the cardiac OR. AI Coach will achieve its objectives by pursuing two parallel strategies: (i) addressing the problem of modeling surgical teamwork; (ii) computationally generating feedback to improve this teamwork. The project team will first develop a novel Team Markov Model (TMkM) that reflects the surgical team’s mental model. Then, the computational core of the system will be realized through the development of (a) machine learning algorithms based on novel multi-agent imitation learning methods to arrive at predictive models of teamwork that explicitly depend on latent performance-shaping factors, such as mental models, and (ii) explainable AI techniques to computationally generate interpretable feedback and interventions for enhancing teamwork. Due to the challenge of collecting large data sets of surgical teamwork, the algorithm development will emphasize sample- and label-efficient techniques. The project team will prototype and test usability of the integrated system by employing iterative, user-centered design approaches. The solutions will be developed and evaluated using multi-modal expert-annotated data of surgical teamwork and prototyped in a state-of-the-art OR simulation facility.<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. |
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