Embry‑Riddle partners with private and public entities to assist in developing solutions to today's and tomorrow's aeronautical and aerospace problems. Here at the world's largest aviation-oriented university, our focus on applied research is unique.
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211-220 of 271 results

  • Big Data Analytics for Injury Data

    PI Dothang Truong

    This project leverages big data analytics tools for the exploration and transformation of injury data for a major Part 121 carrier with the goal of predictive modeling. This project offers graduate students an opportunity to work with a substantial airline dataset under the supervision of a faculty member. The outcomes have the potential to lead to more extensive future projects in the realm of big data analytics. (This project is under strict NDA).


    Categories: Faculty-Staff

  • Pilot’s Willingness to Operate in Unmanned Aircraft System Integrated Airspace

    PI Lakshmi Vempati

    PI Scott Winter

    The interest in Unmanned Aircraft Systems (UAS) use for private, civil, and commercial purposes such as package delivery, inspection, surveillance, and passenger and cargo transport has gained considerable momentum. As UAS infiltrate the National Airspace System (NAS), there is a need to not only develop viable, safe, and secure solutions for the co-existence of manned and unmanned aircraft, but also determine public acceptance and pilot’s willingness to operate an aircraft in such an integrated environment. Currently there is little or no research on pilot’s perceptions on their willingness to operate an aircraft in UAS integrated airspace and airports.



    The purpose of this study was to determine what effect the type of UAS integration, the type of UAS operations, and the airspace classification will have on pilot’s perspectives and willingness to operate an aircraft in UAS integrated airspace and airport environment. This study surveyed the eligible pilot population in hypothetical scenarios using convenience sampling to measure their willingness to operate an aircraft in UAS integrated airspace and airports using the Willingness to Pilot an Aircraft Scale, which has been shown to be valid and reliable by Rice, Winter, Capps, Trombley, Robbins, and Milner (2020). A mixed factorial design was used to study the interaction effects between the independent variables and the effects on the dependent variable, i.e., willingness to pilot an aircraft.

    The results of the mixed analysis of variance (ANOVA) indicated a significant interaction between type of UAS integration and airspace classification. Overall willingness decreased with airspace and differences in willingness to pilot an aircraft were based on segregated and integrated operations. The average pilot’s willingness to pilot an aircraft score differed from the highest score being for Class B, decreasing with decreasing airspace classes, with the lowest being for Class G.

    Analysis of pilot perspectives collected through open ended questions using text-mining techniques showed agreement with mixed ANOVA analysis that the primary factor in the pilot’s perception was airspace. Key concerns voiced by the pilots were situation awareness, risk and safety of operations, aircraft certification and airworthiness, and operator experience and regulatory conformance. The most positive sentiment was observed among pilots presented with the hypothetical scenario of fully autonomous UAS operations in a segregated environment. Findings from the study could aid regulators in developing better policies, procedures, integration solutions, improved training, and knowledge sharing.

    Categories: Graduate

  • Developing Artifact Peer Review Assignment Methodologies to Maximize the Value of Peer Review for Students

    PI Matthew Verleger

    This engineering education research project seeks to develop a proof-of-concept peer review matching algorithm and demonstrate if it is a valuable and viable methodology for conducting peer review. Peer review is a proven method that has positive impact on student learning. The project will test the algorithm on Model Eliciting Activities in the engineering classroom, and investigate how changing peer review can affect student learning.



    ​The broader significance and importance of this project is the transformative potential of improving peer review processes, since peer review is used throughout STEM and medical fields. Thus this preliminary investigation can extend outside the realm of improving student learning. This project overlaps with NSF's strategic goals of transforming the frontiers through preparation of an engineering workforce with new capabilities and expertise. Additionally NSF's goal of innovating for society is enabled by supporting the development of innovative learning systems.

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    Categories: Faculty-Staff

  • Platform for Investigating Concept Networks on the Instrumentality of Knowledge (PICNIK)

    PI Matthew Verleger

    This engineering education research project seeks to develop a concept network for engineering and a platform for helping students identify how concepts are connected across a curriculum.  The goal is to better understand and improve how students value the concepts being taught throughout their education.



    By data mining course materials (i.e., textbooks, course notes, syllabi, video transcripts, websites, etc.), a concept network can be developed for that course. With each additional resource, the network connectedness become more fully representative.  By mapping materials from courses throughout a curriculum, and then overlaying the resulting map on a degree plan of study, students will be able to better identify and value how concepts being taught today are connected and used throughout the rest of their education. For instructors, curricular redesign becomes significantly easier, as they will be able to more fully contextualize how other courses depend on their material.

    Categories: Faculty-Staff

  • Bayesian Analysis of Stellar Evolution

    PI Theodore von Hippel

    Bayesian Analysis of Stellar Evolution is an international collaboration studying stellar evolution with an emphasis on stellar ages. We also develop and support a Bayesian software suite that recovers star cluster and stellar parameters from photometry, currently called BASE-9.

    BASE-9 is useful for analyzing single-age, single-metallicity star clusters, binaries, or single stars, and for simulating such systems. BASE9 uses Markov chain Monte Carlo to estimate the posterior probability distribution for the age, metallicity, distance modulus, and line-of-sight absorption for a cluster, and for the mass, binary mass ratio, and cluster membership probability for every cluster member.

    Categories: Faculty-Staff

  • Diagnosing Kinematic Processes Responsible for Precipitation Distributions in Hurricanes

    PI Joshua Wadler

    This project studies physical processes behind why the spatial distribution of different types of precipitation are related to hurricane intensity change.

    Tropical cyclones, also called hurricanes or typhoons, pose a significant threat to coastal communities through high winds, storm surge, and heavy rainfall. Poor predictions of tropical cyclones can lead to underprepared communities, exacerbating the impacts of these powerful storms. This project aims to understand how different types of precipitation, or rainfall, impact tropical cyclone maximum sustained wind speed. Precipitation is divided into four categories based on how fast the air is rising in clouds. Clouds that have faster rising air are called convection, with the tallest clouds called deep convection and the shallower clouds called moderate convection and shallow convection. The lightest precipitation is called stratiform rain and has the least amount of rising air. The type of precipitation can be identified based on its appearance on radar measurements. This project addresses how each type of precipitation influences the maximum sustained wind speed of the storm through their impact on storm structure. Since different types of precipitation can be identified on radar, this project may offer new insights into forecasting of tropical cyclone maximum sustained wind speed. In addition, this project will support undergraduate student research, an undergraduate mentorship program, a scholarship for a high achieving student, and outreach activities that will help communities susceptible to tropical cyclones understand and prepare for their impacts.

    Categories: Faculty-Staff

  • Air-Deployed sUAS and StreamSonde Measurements of Turbulence in the High Wind Tropical Cyclone Surface Layer

    PI Joshua Wadler

    ​The primary objective of this proposal is to use uncrewed aircraft technology and atmospheric profilers to measure turbulence in the tropical cyclone (TC) boundary layer and to use those measurements to improve NOAA’s operational models.

    ​Over the past decade, NOAA has deployed low-altitude small uncrewed aircraft systems (sUAS) from the WP-3D (P-3) to improve operational situational awareness for tropical cyclones (TC), enhance parameterization routines in NOAA forecast models for TC structure and intensity change, and NOAA’s operational data assimilation methods. sUAS sample near the air-sea boundary, where energy and momentum are exchanged with the sea and where severe winds at landfall can directly affect the lives and property of millions of Americans every year. Even though this is a critical region of a TC, detailed analyses of atmospheric turbulence below 500-m altitude are limited due to safety concerns and other logistical constraints that make in-situ data collection within the lowest and most dangerous areas of the hurricane prohibitive. Enhanced, reliable, and high-resolution observations in the TC boundary layer are necessary to address this critical data void. This proposal will seek to take measurements of turbulence in the TC boundary layer using sUAS as well as a new, versatile atmospheric profiler called StreamSonde.

    Categories: Faculty-Staff

  • Optimizing Countermeasures for Spaceflight-Induced Deconditioning

    PI Christine Walck

    This research focuses on understanding space deconditioning and developing comprehensive systems to mitigate the adverse physiological effects of microgravity on astronauts.

    Spaceflight-induced deconditioning presents a major challenge to human health during and after long-duration missions, contributing to muscle atrophy, bone loss, cardiovascular dysfunction, and sensorimotor impairment. This research investigates the underlying mechanisms of physiological decline in microgravity and evaluates integrated mitigation strategies using a combination of ground-based analogs (e.g., head-down tilt, LBNP), biomechanical modeling, and real-time physiological monitoring. By developing a modular countermeasure system — featuring tools like the Lower Extremity Force Acquisition System (LEFAS) and personalized exercise protocols — we aim to preserve musculoskeletal and cardiovascular integrity throughout space missions. The findings contribute to NASA’s broader efforts in preparing astronauts for lunar and Mars exploration.

    Categories: Faculty-Staff

  • Small UAS (sUAS) Mid-Air Collision (MAC) Likelihood

    PI Ryan Wallace

    CO-I Dothang Truong

    CO-I Scott Winter

    CO-I David Cross

    This research focuses on sUAS MAC likelihood analysis with general aviation (GA) and commercial aircraft. Because severity research varies based on where a collision occurred on a manned aircraft, this likelihood research will not only look at the probability of a MAC, but also the likelihood of colliding with different parts of a manned aircraft.

    Complete Mid-Air Collision (MAC) risk assessments require estimates of both collision severity and collision likelihood. This research focuses on sUAS MAC likelihood analysis with General Aviation (GA) and commercial aircraft. Because severity research varies based on where a collision occurred on a manned aircraft, this likelihood research will not only look at the probability of MAC but also the likelihood of colliding with different parts of a manned aircraft.

    Categories: Faculty-Staff

  • Best practices in teaching statistics and research methods within an aviation curriculum

    PI Robert Walton

    Student learning assessment is necessary at most universities, the question is whether or not student learning assessment though the use of tests can be turned into a less anxiety-provoking experience and, most ideally, into a summative learning experience for students. Using a three-test format student assessment this research examined an alternate testing paradigm, aiming directly at anxiety associated with tests and grades.



    This research will examine an alternate testing paradigm, aiming directly at anxiety associated with tests and grades. The research question for this study is whether or not student assessment though the use of a traditional testing format could be made less anxiety provoking and, most ideally, be turned into a teaching/learning experience for students. Students in a statistics course will be assessed using a three-test format. Tests will be scored immediately after completion, with the student present and incorrect responses explained. The student can then retake an alternate exam and will receive the highest grade on any version of the test they take. Data will be examined for statistically-significant indicators from version 1, to 2, to 3 of the examinations.

    Categories: Faculty-Staff

211-220 of 271 results