Current ARCS Awards
Dr. Brian Amos
Associate Professor of Political Science
Fairmount College of Political Science
Brian Amos is an associate professor in the political science department. He conducts
research in the area of election administration, and is co-director of IKE Lab (ike-lab.com),
which collects data on Kansas elections and voters.
Project Abstract
The classic description of voter behavior is that federal elections center around national issues, state elections around state issues, and local elections around local issues. However, observers have noted an increase in the “nationalization” of state and local elections – gubernatorial candidates in Kansas might take stances on immigration policy, or a school board election might receive funding from a pro-life group from out of state. One piece of evidence for this trend is the growing alignment of partisan outcomes for president, U.S. Senate, and gubernatorial races, where states elect the same party for each office. Partisan splits do still happen, including in Kansas, but they are rarer than before, and margins of victory have become more similar over time. Furthermore, this trend has seen cycles: there was a peak in partisan alignment in the early 20th century, followed by a decline in the middle of the century, followed by the climb seen today. Nationalization has been noted recently in state legislative races, as well, but while there are widely used datasets of federal and gubernatorial elections available spanning the country’s history, digitized and formatted state legislative race data are only available for recent decades. In this project, I will take on this collection process for Kansas to allow for a comparison of state legislative election results with federal election results across the history of the state. I expect to find a different pattern of cycles than those in gubernatorial elections: in early years the trend will be stronger due to the method of selecting U.S. senators, but in more recent history the trend will be weaker, due the smaller and more personal scale of the elections. Understanding when nationalization has not only increased but also decreased can give clues to practitioners as to how the current political climate can be cooled.
Dr. Eylem Asmatulu
Associate Professor of Mechanical Engineering
College of Engineering
Dr. Asmatulu is currently an Associate Professor in the Department of Mechanical Engineering
at Wichita State University (WSU) and is actively involved in teaching, research,
and service. She received her Ph.D. from the Department of Industrial and Manufacturing
Engineering at WSU in May 2013, with a focus on “Life Cycle Analysis of Advanced Materials.”
She worked in Environmental Health and Safety at WSU and in the Composite Manufacturing
Laboratory at NIAR before joining Mechanical Engineering at WSU. She has been quite
active in research and scholarly production, has published over 160 technical articles,
including peer-reviewed journals, conference proceedings, book chapters, books, and
patent, and presented 27 presentations. Dr. Asmatulu is currently conducting research
on surface structures, biomaterials, machine learning, hydrogen storage, and additive
manufacturing.
Project Abstract
Additively Manufactured Hybrid Invar–Aluminum Packaging for Thermally Stable, High-Performance Aerospace Systems
High-performance electronics for applications such as aerospace, defense, advanced manufacturing, and precision tools require electronics packaging that provides high levels of dimensional stability and thermal dissipation properties in varying temperature conditions and high-power density applications. Although conventional aluminum-based electronics packaging demonstrates high thermal dissipation properties, it also demonstrates high thermal expansion, causing problems such as misalignment and connector stress. Invar (Fe–Ni36) based electronics packaging demonstrates high levels of dimensional stability owing to its ultra-low coefficient of thermal expansion. However, it also demonstrates low thermal conductivity and high density, limiting its potential as an electronics packaging solution for high-power applications. To address these issues, this project aims to design and develop an additively manufactured hybrid Invar-aluminum electronics packaging solution. The objective of this project is to design and develop an additively manufactured hybrid Invar-aluminum electronics packaging solution. The project will involve three main tasks, including the 1) design of topology-optimized, additively manufactured Invar structural frames with alignment features and mechanically interlocking interfaces, 2) the integration of aluminum heat-spreading components via engineered joining techniques that offer high thermal contact conductance and allow for thermal expansion mismatch, and 3) the fabrication and experimental validation of prototype packages under applicable thermal loading conditions, including steady-state heating and thermal cycling (e.g., -40 to 85 °C), with the performance benchmarked against conventional monolithic aluminum enclosures. The hybrid structures will be fabricated via laser powder bed fusion (LPBF) on Invar, along with aluminum plates or fine cold plates to balance thermal and mechanical responses.
Professor Megan Bascom
Assistant Professor of Comtempory Dance
School of Performing Arts
Megan Bascom is a choreographer, performer, dance educator, and somatic practitioner
whose work centers collaboration and the nuanced complexities of human interaction.
Her artistic research integrates choreographic inquiry, somatic practice, cultural
narrative, and movement education, treating the body as an evolving archive of lived
experience. Her choreography has been presented nationally and internationally, including
at multiple venues in New York City, The Dance Complex (MA), Inkub8 Arts Miami (FL),
the University of Michigan, the Asheville Fringe Arts Festival (NC), Artus Studio
in Budapest (Hungary), and Hacettepe University in Ankara, Turkey. She was noted in
Dance Teacher Magazine’s January 2021 article “These College Professors Are Using
Social-Distancing Restrictions to Fuel Creativity,” by Lauren Wingenroth, and has
received the Meta Weiser Performing Arts EXCELerator Grant (2018), and the Andrew
W. Mellon Foundation Space Subsidy at Triskelion Arts (2012–2017). As an educator,
Bascom has served on faculty at the University of Michigan and Gibney Dance Center
(NYC), among other institutions. She holds an MFA from the University of Michigan
and a BA in Dance Studies from the University of South Florida. She is also known
as Megan Hillman Hammer.
Project Abstract
Fabricated Need is a choreographic and community-engaged performance that turns our
relationship to clothing into an embodied practice of awareness and care. The work
examines overproduction, waste, and accumulation—cultural and psychological conditions
shaped by fashion consumerism—through slow, durational movement, task-based actions
(sorting, layering, removing), and a live clothing exchange/donation embedded within
the performance. Audience members sit in the round and are invited to bring garments
that shape both the material environment and the choreography. The event concludes
with a brief facilitated conversation to support reflection and identify next steps
(e.g., linking donations to a coat drive).
The project began as a commissioned six-minute solo for Ten Tiny Dances® at the Wichita
Art Museum (in collaboration with Harvester Arts) and now expands to an ensemble format
appropriate for community venues. By pairing contemplative attention with a tangible
redistribution of goods, Fabricated Need moves from metaphor to practice—asking what
we carry, what we can release, and how shared responsibility can transform excess
into care. Goals for the proposed ARCS grant period include: (1) research, development,
and rehearsal of ensemble scores, that transition the work from a solo to ensemble
performance in collaboration with two additional dancers; (2) open rehearsals with
workshop-audiences to develop performative clothing-exchange logistics within the
work and receive post-sharing feedback; (3) travel to present our first-draft of the
expanded work at the Built-On-Stilts Festival in Matha’s Vineyard where I have received
a special invitation to present at the 30th year anniversary of this festival; and
(4) creating clear documentation and materials for external funding and future presentations.
Dr. Mohamed Nasser
Assistant Professor of Mathematics Statistics and Physics
College of Mathematics, Statistics and Physics/LAS
Mohamed Nasser is an Assistant Professor of Applied and Computational Complex Analysis
in the Department of Mathematics, Statistics & Physics at Wichita State University.
He earned his PhD from Universiti Teknologi Malaysia in 2005. Before joining WSU in
2022, he held several academic positions at Ibb University (Yemen), King Khalid University
(Saudi Arabia), and Qatar University. His research interests include boundary integral
equations, numerical conformal mappings, Riemann-Hilbert boundary value problem, ideal
fluid mechanics, and potential theory.
Project Abstract
The area of boundary value problems for analytic functions is one of the active research areas in complex analysis in particular and mathematics in general. An important class of boundary value problems for analytic functions is the nonlinear Riemann-Hilbert problem (RH problems for short) which consists of the determination of all analytic functions in a domain in the complex plane that satisfy a prescribed nonlinear boundary condition on the boundary. The RH problem has applications to problems in applied mathematics, mathematical physics, and engineering. The nonlinear RH problem generalizes two fundamental problems in complex analysis: the linear RH problem and the conformal mapping problem. Since analytic solutions of these two special case problems are known for only a few special domains, numerical methods are needed for both problems. In the past two decades, the PI (Mohamed Nasser) and his co-authors developed a fast and accurate numerical method for solving the linear RH problem and for the computation of conformal mappings for simply and multiply connected domains. The method builds upon the use of the boundary integral equation with the generalized Neumann kernel. The aim of this project is to use this integral equation to develop a numerical method for solving the nonlinear RH problem in simply and doubly connected circular domains. By means of conformal mappings, the RH problem in other simply and doubly connected domains can be reduced to the case of circular domains.
Project Abstract
Current MURPA Awards
Currently, Dr. Davood Askari is an Associate Professor of Mechanical Engineering at Wichita State University (WSU) and the founding director of Multifunctional Nanocomposite Lab (MNL). He has served as a graduate coordinator for Master of Science in Materials Engineering at WSU and he has worked in industry and academia as a mechanical design engineer, research assistant, post-doctoral research associate, and university professor. Davood has been actively involved in research, teaching, scholarly, and professional service activities and his areas of research interest include: (1) design, modeling, analysis, fabrication, testing, of solids, composites, nanocomposites, thin films, and hydrophobic/super-hydrophobic surfaces, (2) synthesis, functionalization, characterization, and applications of carbon nanostructures, metallic Nanoneedles, 3D nano-structured materials, devices, and systems for various high-performance engineering applications. His research and educational efforts have been supported by federal and state agencies and industry collaborators such as NSF and Spirit AeroSystems. He has served as referee, session chair, symposium organizer, and technical committee member for several technical conferences and scientific journals and served as grant reviewer for funding agencies such as NSF.
Project Abstract
Unmanned aerial vehicles (UAVs) are increasingly important for applications ranging from disaster response to national defense. However, today's UAVs rely heavily on radio frequency (RF) communications, which can be jammed, intercepted, or disrupted in contested environments. This project will investigate a new method of communication between UAVs using free-space optical (FSO) links, including both laser and visible-light technologies. Unlike RF signals, optical beams are highly directional and difficult to jam, offering secure and high-bandwidth data transfer. The research will develop and evaluate a dual-mode optical system that can switch between laser and heliograph-styl e visible-light signaling, ensuring resilient communications even under interference. The work will generate pilot data to support larger federal proposals and provide opportunities for student research training in optics, communications, and aerospace systems.
2. Background
Secure communication is the backbone of UAV operations in both civilian and defense settings. Traditional RF-based methods are vulnerable to interference, interception, and spectrum congestion. This limits UAV effectiveness in environments where adversaries deliberately attempt to disrupt communications.
Optical wireless communication offers an attractive alternative. Free-space optical (FSO) systems transmit data using light beams rather than radio waves, making them inherently more resistant to jamming and interception. FSO links also support much higher bandwidth compared to RF, enabling rapid transfer of images, sensor data, and control signals.
Despite these advantages, FSO for UAVs is underexplored [1-8]. Most prior work has focused only on active laser systems, which can be blocked by obstacles or degraded by atmospheric conditions. Our project introduces a dual-mode design that combines laser-based links with heliograph-style signaling using modulated visible light. This hybrid approach ensures that UAV swarms can maintain reliable connectivity even when one channel is degraded.
This research aligns with growing national interest in resilient aerospace communication systems and directly supports the mission of funding agencies such as the Department of Defense (DoD) and the National Science Foundation (NSF). Wichita State University is uniquely positioned to pursue this work due to its strengths in aerospace engineering, optics, and applied research.
This project investigates how Large Language Models (LLMs) can support individuals navigating local food systems by automating data collection and enabling personalized food-access recommendations. A central challenge in this setting is maintaining an up-to-date, comprehensive database of food opportunities—such as food pantries, community fridges, and soup kitchens—which often operate with limited resources and inconsistent online information. To address this, we will use state-of-the-art LLMs and retrieval-augmented generation (RAG) methods to periodically extract, summarize, and update data from web sources suggested by organizations such as the Kansas Food Bank, United Way of the Plains, and the Health and Wellness Coalition. The resulting structured dataset will include operational hours, locations, documentation requirements, and food availability, forming the foundation for downstream decision-support models.
The dataset will be used help individuals minimize travel distance to obtain food subject to life constraints by exploring two complementary solution strategies. First, we will reformulate the problem as a traveling-salesman problem with time windows to generate optimized schedules. Second, we will develop an LLM-driven prompting system capable of producing flexible, real-time recommendations based on user context and updated data. These dynamic outputs may include ranked lists, alternatives, or tailored suggestions that adapt to individual needs.
Finally, we will conduct a preliminary usability assessment of recommendation formats with members of the Community Health Improvement Plan (CHIP) group focused on food access. Outcomes of this work include an automated data-updating algorithm, improved formulations for food navigation, and community-informed guidance for future large-scale studies
received his Ph.D. degree in Electrical and Computer Engineering from the University of Massachusetts Amherst in 2013. He was a Postdoctoral Research Fellow at Texas A&M University, College Station, TX, USA, from March 2013 to April 2015. From August 2014 to June 2015, he also served as a Visiting Research Scholar as part of the Information Initiative at Duke (iiD). He is currently an Associate Professor in the Department of Electrical and Computer Engineering at Wichita State University, Wichita, KS, USA. His current research interests include developing robust and resilient networks, such as infrastructure networks and communication networks. In 2017, he received Wichita State University’s Young Faculty Risk Taker Award. He has served as a Session Chair for several IEEE conferences and workshops, and as a reviewer for numerous IEEE journals. He has also served on multiple NSF review panels.
Project Abstract
Unmanned aerial vehicles (UAVs) are increasingly important for applications ranging from disaster response to national defense. However, today's UAVs rely heavily on radio frequency (RF) communications, which can be jammed, intercepted, or disrupted in contested environments. This project will investigate a new method of communication between UAVs using free-space optical (FSO) links, including both laser and visible-light technologies. Unlike RF signals, optical beams are highly directional and difficult to jam, offering secure and high-bandwidth data transfer. The research will develop and evaluate a dual-mode optical system that can switch between laser and heliograph-styl e visible-light signaling, ensuring resilient communications even under interference. The work will generate pilot data to support larger federal proposals and provide opportunities for student research training in optics, communications, and aerospace systems.
2. Background
Secure communication is the backbone of UAV operations in both civilian and defense settings. Traditional RF-based methods are vulnerable to interference, interception, and spectrum congestion. This limits UAV effectiveness in environments where adversaries deliberately attempt to disrupt communications.
Optical wireless communication offers an attractive alternative. Free-space optical (FSO) systems transmit data using light beams rather than radio waves, making them inherently more resistant to jamming and interception. FSO links also support much higher bandwidth compared to RF, enabling rapid transfer of images, sensor data, and control signals.
Despite these advantages, FSO for UAVs is underexplored [1-8]. Most prior work has focused only on active laser systems, which can be blocked by obstacles or degraded by atmospheric conditions. Our project introduces a dual-mode design that combines laser-based links with heliograph-style signaling using modulated visible light. This hybrid approach ensures that UAV swarms can maintain reliable connectivity even when one channel is degraded.
This research aligns with growing national interest in resilient aerospace communication systems and directly supports the mission of funding agencies such as the Department of Defense (DoD) and the National Science Foundation (NSF). Wichita State University is uniquely positioned to pursue this work due to its strengths in aerospace engineering, optics, and applied research.
This project investigates how Large Language Models (LLMs) can support individuals navigating local food systems by automating data collection and enabling personalized food-access recommendations. A central challenge in this setting is maintaining an up-to-date, comprehensive database of food opportunities—such as food pantries, community fridges, and soup kitchens—which often operate with limited resources and inconsistent online information. To address this, we will use state-of-the-art LLMs and retrieval-augmented generation (RAG) methods to periodically extract, summarize, and update data from web sources suggested by organizations such as the Kansas Food Bank, United Way of the Plains, and the Health and Wellness Coalition. The resulting structured dataset will include operational hours, locations, documentation requirements, and food availability, forming the foundation for downstream decision-support models.
The dataset will be used help individuals minimize travel distance to obtain food subject to life constraints by exploring two complementary solution strategies. First, we will reformulate the problem as a traveling-salesman problem with time windows to generate optimized schedules. Second, we will develop an LLM-driven prompting system capable of producing flexible, real-time recommendations based on user context and updated data. These dynamic outputs may include ranked lists, alternatives, or tailored suggestions that adapt to individual needs.
Finally, we will conduct a preliminary usability assessment of recommendation formats with members of the Community Health Improvement Plan (CHIP) group focused on food access. Outcomes of this work include an automated data-updating algorithm, improved formulations for food navigation, and community-informed guidance for future large-scale studies
Current URCA Awards
Dr. Abdulaziz Abubshait
Assistant Professor of Psychology
Fairmount College of Liberal Arts and Sciences
Dr. Abubshait is an Assistant Professor of Psychology at Wichita State University.
He received a Ph.D. in Human Factors and Applied Cognition from George Mason University
and completed a postdoctoral fellowship at the Italian Institute of Technology. Aziz
was also awarded the AAAS-STPF fellowship where he worked at the National Institute
on Aging. His research investigates human interactions with robots and artificial
agents with the goal of designing machines, robots, and AI systems that serve as better
collaboration partners.
Project Abstract
By 2030, a fifth of U.S. workers will be over 65, presenting urgent challenges for sustaining workforce productivity in an increasingly technology-driven economy. Although older workers often possess strong cognitive capabilities, they frequently lack access to effective training resources that enable them to adapt to new technologies. This gap accelerates skill obsolescence and premature retirement. Social robots offer a promising solution: As learning guides, they can capture attention, provide consistent feedback, and facilitate skill acquisition. This pilot study investigates whether social robots can effectively induce attentional shifts in the aging workforce, a critical first step toward developing robot-assisted training systems. As such, this pilot will assess (A) the acceptance of social robots among older workers, (B) their ability to direct attention during complex tasks, and (C) the relationship between robot acceptance and attentional guidance. Findings will establish preliminary evidence on whether robots can serve as effective attentional guides in learning contexts. Ultimately and beyond this work, we aim to investigate the use social robots to directly enhance training efficiency, reduce errors, and extend the productive participation of older adults in the workforce, addressing a nationally recognized priority for economic sustainability and aging policy.
Dr. JaeHwan (Jay) Byun
Associate Professor School of Education
College of Applied Studies
Jaehwan Byun, Ph.D., is an Associate Professor and the chair of the M.Ed. in Learning
and Instructional Design Program at Wichita State University, specializing in Instructional
Design and Technology. His recent research activities emphasize innovative educational
approaches, including generative AI applications, AI-assisted lesson planning, Online
learning in developing countries, and digital game-based learning designed to support
refugee students. Dr. Byun has secured significant research funding, notably from
NASA for enhancing STEM education in Kansas public schools and through Wichita State
University's President Convergence Science Initiative. Recognized for his impactful
contributions, Dr. Byun was recently named the 2025–26 Corbin Connect Emerging Technologies
Fellow. His dedication to excellence has also earned him awards such as Wichita State’s
Excellence in Online Teaching and the Technology & Innovation Award. Actively involved
in academia, Dr. Byun serves in key roles within professional associations, frequently
presents at international conferences, and mentors graduate students, driving forward
transformative advancements in educational technology.
Project Abstract
The rapid integration of Generative Artificial Intelligence (GenAI) into K-12 education has created an urgent need for research-based guidance, yet a critical gap exists in the empirical understanding of how teachers are actually using this new technology. Most current literature is conceptual, lacking real-world, classroom-based evidence of teacher adaptation. To fill that gap, this study conducts a foundational needs assessment of in-service K–12 teachers in the Wichita metropolitan area. The primary goal of the project is to investigate current teacher practices, perceived challenges, and critical support needs related to GenAI. Employing a mixed-methods sequential design, the study will begin with a quantitative survey of approximately 100 teachers to identify patterns of use, followed by in-depth qualitative focus groups to explore the nuances of teacher experiences. The findings will provide a crucial empirical snapshot of the regional landscape, moving beyond speculation to offer data-driven insights for researchers and policymakers. Significantly, this project aims to serve as essential pilot data for a future external grant proposal to formally establish The Applied GenAI in Education Lab (A^2E Lab) at Wichita State University, envisioned as a regional hub for fostering innovation and ethical integration of AI in education.
Dr. Amy Chesser
Professor of Public Health Sciences
College of Health Professions
Dr. Chesser is a Professor in the Department of Public Health Sciences at Wichita
State University. She holds a doctorate in health communications. Her primary research
interests are public health, women’s health, health communication, health literacy,
health disparities, and older adults. She has taught multiple communications courses
at the graduate and undergraduate levels including Health Communications, Health Communications
for Older Adults, Social Marketing, Organizational Communications, Global Public Health
Communications, and Introduction to Communications. She has twenty years of experience
working in health literacy and is a part of the Health Literacy Regional Network.
Dr. Chesser was awarded the Quality Matters National Certification: AGE 804 Aging
Programs and Policies and AGE 717: Health Communications. She has received the WSU
Gold Standard award for all other classes that she has taught. In 2016, Dr. Chesser
received the Excellence in Research Award for the College of Health Professions. She
has worked with Behavioral Risk Factor Surveillance Survey (BRFSS) data for more than
a decade. The survey includes a Diabetes Risk Assessment as well as health literacy
questions. Currently, Dr. Chesser is collaborating with Drs. Keene Woods and Drassen
Ham on activities for Interprofessional Education through National Interprofessional
Healthcare Education and Research Team (NIHEART).
Project Abstract
Dr. Francis X. Connor
Associate Professor and Chair Department of English
Fairmount College of Liberal Arts and Sciences
Dr. Francis X. Connor is Associate Professor and Chair of English and co-director
of the Robert L. Cattoi Book Technologies Lab. He is an Associate Editor for The New Oxford Shakespeare, for which his editions of Romeo and Juliet, Titus Andronicus (co-edited with Gary Taylor, Terri Bourus, Rory Loughnane, and Anna Pruitt), and
As You Like It have recently been published as part of the Oxford World's Classics series. He is
currently editing Hero and Leander for The Oxford Complete Works of Christopher Marlowe. His forthcoming book, No Choice But Action (forthcoming Fall 2026), co-authored with WSU's own Dr. Darren DeFrain, chronicles the postpunk and DIY musical
subcultures of Reagan-era Kansas. Whether researching Early Modern English or Contemporary
American writers, publishers, and musicians, his work is united by an interest in
the materiality of text technologies – such as books, manuscripts, cassettes, or zines
– and the impact these forms have on the cultures that produce them.
Project Abstract
This year the Wichita State Department of English unveiled a new humanities makerspace, the Robert L. Cattoi Book Technologies Lab, intended for use as a teaching space where students can explore the history of human communication through engagement with technologies used to make books and other texts, from wax tablets and scrolls to letterpress printing and digital publishing. To this end this URCA grant will fund a student research assistant to work in the Cattoi Lab alongside faculty to develop teaching resources that demonstrate how such labs can enrich the study of writing, printing, publishing, and digital humanities. The project has two interrelated goals: (1) to develop practical teaching resources, such as sample exercises and classroom-tested modules, that accompany those arguments; (2) to generate scholarly publications that argue for the pedagogical value of Book Labs, offering replicable teaching strategies for humanities (and humanities-adjacent) faculty who want to integrate hands-on book history into courses. We hope this work will culminate in publications that provide guidance on how instructors could incorporate Book Labs into traditional humanities instruction. This project contributes to ongoing debates about how to connect historical media to contemporary pedagogy, and provides students with active learning opportunities and professional development in research, editing, and publication. The Cattoi Book Technologies Lab is the first such space in Kansas and one of a handful currently based in American universities generally, so scholarship produced with this grant is likely to be highly impactful.
Dr. Rui Dai
Assistant Professor in Special Education
College of Education
Dr. Rui Dai is an Assistant Professor in the College of Education. His research focuses
on human motivation and the application of motivational theories to understand and
address classroom issues, such as students’ challenging and problematic behaviors.
Dr. Dai is especially interested in connecting classroom practices with contemporary
popular culture, such as digital gaming, to support student engagement and learning.
Project Abstract
Uncertainty-based rewards are powerful behavioral drivers because they can heighten curiosity, engagement, and anticipation beyond what is typically offered by certain rewards. This is evident in the growing commercial blind-box market as well as in educational settings, where mystery rewards are used to support behavior management in K–12 classrooms. However, little is known about which features of blind boxes are most salient in motivating purchasing behavior, or the extent to which these features are similar to or different from classroom mystery rewards. The overall goal of this proposed study is to fill this gap in literature. Using a mixed-methods methodology, our specific objective is to examine the key motivational features underlying commercial blind boxes and mystery rewards used by K–12 teachers as an academic or behavior management strategy. Findings from this study will support the development of a preliminary framework to guide the intentional, developmentally appropriate, and ethical use of mystery rewards in educational settings. Furthermore, these preliminary findings will inform the development of an app-based mystery reward platform aimed at enhancing student engagement and supporting behavior management in K–12 classrooms.
Dr. Yanwu Ding
Associate Professor of Electrical and Computer Engineering
College of Engineering
Yanwu Ding is a faculty member with the Department of Electrical and Computer Engineering
at Wichita State University. Her research portfolio spans advanced signal processing
algorithms for communication systems. Specific interests include robust fetal electrocardiogram
(ECG) signal extraction using time-frequency techniques, geolocation, Doppler frequency
estimation, and blind receivers. She also applies machine learning to jamming analysis
and develops precoding techniques to save transmitting power while maintaining Quality
of Service (QoS) in communication systems. Dr. Ding's work has been supported by a
US Air Force SBIR grant, and she was selected for the prestigious Summer Faculty Fellowship
Program (SFFP) at the Air Force Research Laboratory (AFRL).
Project Abstract
The non-invasive fetal electrocardiogram (fECG) is crucial for monitoring fetal health, but its clinical adoption is limited by a low signal-to-noise ratio (SNR). The weak fECG is often obscured by the dominant maternal ECG (mECG) and noise in abdominal recordings. To address this, we introduce a novel framework based on the Synchrosqueezing Transform (SST), which produces a high-resolution time-frequency representation to disentangle the overlapping fetal and maternal components. Our goal is to develop and validate a robust, open-source algorithm for accurate fECG extraction from a single-channel recording, enabling reliable heartbeat detection and morphological analysis. This work aims to pave the way for simpler, more accessible, and accurate fetal monitoring solutions.
Dr. Ahmad Esmaeili
Assistant Professor in School of Computing
Fairmount College of Liberal Arts and Sciences
Dr. Ahmad Esmaeili is an Assistant Professor of Computer Science in the School of Computing
at Wichita State University, where he leads the Multiagent Systems Lab. His research
interests lie at the intersection of artificial intelligence and distributed systems,
with a particular focus on multi-agent systems, hierarchical and holonic agent architectures,
distributed machine learning frameworks, and collaborative learning methodologies.
Dr. Esmaeili received his Ph.D. from the Department of Computer and Information Technology
at Purdue University, where his research explored the design and development of decentralized
agent-based machine learning frameworks. His work has been published in reputable
peer-reviewed venues, including ACM Transactions on Internet Technology, ACM Transactions
on Adaptive and Autonomous Systems, and International Conference on Autonomous Agents
and Multiagent Systems. Dr. Esmaeili is an active member of the IEEE, ACM, and AAAI
societies and has served on the program committees and review boards of numerous conferences
and journals in the domain of artificial intelligence.
Project Abstract
Decentralized multi-agent systems (MAS) offer scalable, robust, and adaptive decision-making without the need for centralized control. These systems are particularly valuable in distributed environments where flexibility, redundancy, and parallelism are essential. However, the effectiveness of collective learning within such systems critically depends on how—and with whom—agents communicate. The structure and quality of these interactions directly impact how well information propagates, how quickly agents align on shared goals, and how efficiently they adapt to new data, much like in human societies—where communication networks shape cooperation, innovation, and learning.
While prior research acknowledges the importance of network topology in influencing MAS performance, it often imposes simplifying assumptions. Common approaches treat communication structures as fixed, assume agents operate on independently and identically distributed data, or rely on predefined adaptation rules. These assumptions limit our understanding of how variations in communication architecture influence learning outcomes, particularly in systems where interactions are central to coordination and knowledge diffusion.
This study investigates how different peer-to-peer interaction structures—specifically, variations in network density and topology—affect learning efficiency, convergence behavior, and computational cost in MAS. Using computational experiments, we will evaluate a range of network configurations to identify key trade-offs between system connectivity, performance, and resource consumption. The insights gained will clarify these trade-offs, informing the design of more efficient MAS architectures. This has implications for real-world domains such as autonomous vehicles, robotic swarms, and IoT systems, where understanding these structural impacts is crucial for optimizing performance under practical communication and resource constraints.
Dr. Fu Yang
Assistant Professor of Elementary Education
College of Applied Studies
Yang Fu is an Assistant Professor in the School of Education at Wichita State University.
She earned her Ph.D. in Special Education from the University of Maryland, College
Park in 2025, where her work centered on improving instructional opportunities for
diverse learners. As a researcher, educator, and teacher educator, her scholarship
focuses on fostering equity and expanding access to high-quality, effective instruction
for underrepresented student populations, including students with disabilities and
English Learners. She is particularly committed to addressing the systemic challenges
that limit students with disabilities from receiving rigorous and meaningful instruction
across content areas. Through her work, Dr. Fu aims to bridge research and practice
by partnering with schools, supporting teacher preparation, and advancing evidence-based
approaches that promote equitable learning outcomes for all students.
Project Abstract
Students with disabilities continue to face persistent challenges in mathematics learning, underscoring the critical role of teachers in shaping equitable learning opportunities. However, many educators report barriers to effectively addressing diverse student needs, while teacher candidates often feel underprepared to teach mathematics to students with disabilities. This study investigates these challenges from both practitioner and preparation perspectives by examining the experiences of teachers in Wichita Public Schools and teacher candidates enrolled in Wichita State University’s College of Applied Studies. The study explores instructional practices, preparation experiences, and systemic supports and constraints that influence mathematics instruction for students with disabilities. The analysis will identify key factors shaping teacher preparedness, including access to targeted training, professional learning opportunities, and program-level collaboration. Findings will inform professional development design, strengthen district–university partnerships, and provide actionable insights for enhancing teacher preparation programs. Ultimately, this study aims to bridge research and practice by identifying strategies to improve equitable mathematics instruction for students with disabilities and by fostering a shared understanding among teacher educators, candidates, and practicing teachers about the supports needed to ensure all learners—particularly those with disabilities—have access to meaningful and high-quality mathematics learning experiences.
Dr. Michael Jorgensen
Professor of Industrial, Systems, and Manufacturing Engineering
College of Engineering
Michael Jorgensen, PhD, has been at Wichita State University (WSU) since 2001, he
is a Professor in the Industrial, Systems and Manufacturing Engineering (ISME) Department,
and served as the founding Chair of the Biomedical Engineering Department at WSU.
Dr. Jorgensen is responsible for the Industrial Ergonomics curriculum and research
within the ISME Department. His research activities have included assessment of intervention
strategies for prevention of work-related injuries, including passive shoulder exoskeletons
in the aircraft and construction industries, job rotation in manufacturing, interventions
to reduce the risk of low back injury during manual materials handling, and assessment
of segmental vibration from rivet guns and bucking bars to reduce vibration exposure
and risk of musculoskeletal injury to aircraft manufacturing workers. Prior to joining
WSU Dr. Jorgensen was an Industrial Engineer and Ergonomist with the U.S. Occupational
Safety and Health Administration, in the Office of Ergonomic Support in Washington,
DC, where he provided ergonomics support for OSHA ergonomics regulatory and enforcement
activities. He also worked as a consultant for an ergonomics consulting firm and
has consulted with companies within Wichita and nation-wide on evaluation and development
of processes to reduce work-related injuries in manufacturing and office settings.
Project Abstract
Shoulder musculoskeletal disorders (MSDs) impose a disproportionate burden in the construction industry, with fewer cases than back injuries but substantially longer disability durations and higher claim costs. Passive arm-support exoskeletons (ASEs) have shown promising reductions in shoulder muscle demand during elevated-arm tasks in laboratory settings, yet field evidence on trade- and task-specific suitability remains limited. This project aims to generate a Trade/Task-to-ASE Suitability Map and a ranked shortlist of construction tasks where ASEs can provide maximal benefit with minimal workflow interference. We will use a mixed-methods design integrating literature review, jobsite observations, structured worker/manager interviews, and ergonomic screening. First, we will synthesize existing literature and O-NET data to build an initial database of potentially ASE-suitable tasks by trade and identify knowledge gaps. Partnering with multiple construction companies across trades, workers will trial a commercial shoulder ASE for up to three days while performing their usual tasks. They will then rate ASE suitability for each task on a 1–5 Likert scale, comment on perceived benefits and constraints (e.g., confined spaces, harness/toolbelt compatibility), and provide subjective feedback on discomfort and perceived exertion. Tasks rated suitable will undergo ergonomic analysis and, when permitted, video-based documentation of shoulder postures. Survey ratings, qualitative feedback, and observational data will be integrated to develop the Trade/Task-to-ASE Suitability Map and ranked shortlist. The resulting evidence will offer field-grounded guidance to contractors, safety professionals, and technology developers regarding where and how to deploy ASEs, reduce trial-and-error implementation, and ultimately help lower the burden of shoulder MSDs in construction.
Dr. Yeil Kwon
Assistant Professor of Mathematics and Statistics
Fairmount College of Liberal Arts and Sciences
Dr. Kwon is an Assistant Professor in the Department of Mathematics, Statistics, and
Physics at Wichita State University. His research centers on empirical Bayes estimation
methods for high-dimensional data, with broader interests in parameter estimation,
statistical modeling for social sciences, and data science education. He earned his
Ph.D. in Statistics from the Fox School of Business at Temple University, an M.S.
in Operations Research with a concentration in Financial Engineering from Columbia
University, and an M.S. in Statistics from Korea University. Dr. Kwon brings extensive
industry experience to his academic work. He previously served as a quantitative analyst
at a hedge fund, where he developed options trading strategies using stochastic models.
As a principal portfolio manager at an insurance company, he managed $12 billion in
assets, applying advanced analytics to assess credit risk and customer behavior. Additionally,
he worked as a credit risk analyst at leading credit bureaus, designing predictive
models for credit risk, bankruptcy, and fraud detection. His expertise contributed
to major projects with Fair Isaac Corporation (FICO) and Experian, where he played
a key role in developing advanced credit risk systems for financial institutions.
Project Abstract
Bayesian statistics, first introduced by Thomas Bayes in the 18th century, remained
largely unused for over two centuries due to computational complexity. With advances
in computing and algorithms, Bayesian methods have become integral to modern data
science, statistics, and machine learning, including applications in artificial intelligence.
A particularly promising area for Bayesian approaches is high-dimensional data analysis,
where the number of variables far exceeds the number of observations—a common scenario
in fields such as genomics and molecular biology. For example, a well-known leukemia
study measured over 7,000 genes from only 72 patients. In such cases, traditional
methods fail to provide reliable
estimates of variability or correlation.This project proposes a novel empirical Bayes
estimator designed for high-dimensional settings. The method leverages information
across the entire dataset to improve estimation accuracy for individual variables,
especially when sample sizes are small. Unlike previous approaches, it offers greater
flexibility by avoiding restrictive assumptions about underlying probability distributions
while retaining the theoretical rigor and adaptability of Bayesian methods. We will
evaluate the proposed estimator using both simulated and real-world datasets, including
genomics, proteomics, and medical imaging. The anticipated outcome is a robust tool
for analyzing complex, high-dimensional data, with direct implications for precision
medicine, genetics, and other domains where reliable inference from limited samples
is critical
Dr. Raj Logan
Assistant Professor of Biological Sciences
Fairmount College of Liberal Arts and Sciences
Raj is an Assistant Professor of Biological Sciences and directs the WSU DAISY Lab.
His lab uses the fruit fly, Drosophila, as a model system to investigate the cellular and molecular mechanisms of organ
formation during embryogenesis. Raj attended the Madras Medical College, India, for
undergraduate training and the University of Kansas Medical Center for graduate school.
He performed postdoctoral research at the Johns Hopkins University School of Medicine
prior to starting his research group at WSU.
Project Abstract
Iron is a critical element for cell survival and maintenance. Recent reports suggest a requirement for iron, particularly in neural stem cells, during critical stages of brain development. Without adequate iron supply, neural stem cells lose the ability to produce ATP (the cellular energy source) due to the dysfunction of iron-dependent proteins essential for ATP production. ATP scarcity results in the cessation of neural stem cell division—an energy intensive process—compromising normal brain development. Iron-deficient stem cells fail to maintain their cornerstone characteristic, i.e., stemness, consequently activating premature cell differentiation programs. Ultimately, neural stem cell dysfunction, triggered by iron deficiency, results in stunted brain growth. The WSU Developmental and Integrative Systems Biology laboratory (DAISY Lab) will investigate the biological mechanism of iron transport into the neural stem cell using the Drosophila melanogaster (fruit fly) larval brain as the model system. Our findings are expected to reveal the mechanism that mediates iron transport in neural stem cells during a critical stage of brain development.
Dr. M. Patty Hernandez-Nuhfer
Assistant Professor of School Phycology/ISLE/COE
College of Liberal Arts and Sciences
Dr. Hernandez-Nuhfer is an Assistant Professor of School Psychology and Coordinator
of the Applied Behavior Analysis Program in the Department of Counseling, Educational
Leadership, Educational and School Psychology (CLES) at Wichita State University.
She is a licensed psychologist, Board Certified Behavior Analyst–Doctoral (BCBA-D),
and Nationally Certified School Psychologist whose research and clinical work focus
on expanding equitable access to school-based mental and behavioral health services
through multi-tiered systems of support (MTSS), applied behavior analysis, data-based
decision making, and technology-enhanced training models. Her scholarship emphasizes
rural and underserved school communities, implementation of evidence-based behavioral
and academic interventions, graduate workforce preparation, and innovative approaches
to competency-based training, including telehealth, immersive simulation, and digital
intervention systems. Dr. Hernandez-Nuhfer serves as Clinical Supervisor and Co-Principal
Investigator for the federally funded School Psychology Partnerships to Increase Rural School-Based Services (SPIRSS) project, which supports school-university partnerships designed to strengthen
mental health infrastructure and workforce development in rural schools. Her work
integrates research, service delivery, and interdisciplinary collaboration to improve
outcomes for children, families, and schools.
Project Abstract
This project aims to develop and pilot a digital immersive training platform designed to enhance graduate training in school psychology and applied behavior analysis (ABA). The project will create interactive, simulation-based K-12 student scenarios that allow trainees to practice assessment, data-based decision-making, and intervention planning in a controlled, virtual environment. The overall goal is to improve trainee competency in applied skills that are traditionally difficult to teach through lecture-based methods alone. Using a one-year subscription to a digital immersive platform, the project will design, implement, and pilot test a series of training modules aligned with evidence-based practices in school-based assessment and intervention.
Dr. Erin O'Bryan
Assistant Professor of Communication Sciences
College of Health Professions
Dr. Erin O’Bryan, PhD, CCC-SLP, is an Assistant Professor in the WSU Department of
Communication Sciences and Disorders, Director of the Wichita Adult Language Lab,
and a member of the Institute for Rehabilitation Medicine and Assistive Technology
(IRMAT). Before coming to WSU in 2019, she completed a Ph.D. in Linguistics and a
master’s degree in speech-language pathology at the University of Arizona. Her clinical
research projects advance the use of music and person-centered storytelling in speech
therapy for people with aphasia, a loss of language and communication abilities that frequently results from a stroke.
She also conducts research measuring the benefits of training current and future healthcare
professionals on how to communicate effectively, respectfully, and compassionately
with patients with communication disorders. She has published eight peer-reviewed
journal articles and led or co-led numerous grant-funded research projects.
Project Abstract
Every year, more than 795,000 people in the United States have a stroke, and approximately one third of stroke survivors have aphasia, a loss of their language and communication abilities. Research has shown that most health care professionals do not know what aphasia is and do not know how to communicate with people with aphasia. Our project will train future health care professionals about aphasia and communication strategies using Supported Conversation for Adults with Aphasia (SCATM). We will target the following specific objectives: 1) the PI (Dr. O’Bryan) will complete SCATM core training and “train the trainer” programs, 2) Dr. O’Bryan and a graduate student research assistant will use the training to develop a program for health professions students to be presented at WSU’s annual Aphasia Awareness Day in June 2026, 3) the attendees’ learning will be measured using a pretest and posttest, 4) the graduate research assistant will analyze the data, and 5) Dr. O’Bryan will use the research findings to submit a manuscript to a peer-reviewed journal and to submit an external grant proposal to further advance the research.
Dr. Tetsuya Sato
Assistant Professor of Human Factors Psychology
Fairmount College of Liberal Arts and Sciences
Dr. Tetsuya Sato is an Assistant Professor in the Department of Psychology at Wichita
State University and the director of the Simulation, Automation Trust, and Oculomotor
Laboratory (SATO LAB). He received his PhD in Human Factors Psychology from Old Dominion
University in 2024. His research program aims to examine how humans interact with
emerging advanced automated technologies and translate research outcomes to innovative
solutions for improving human-automation/autonomy interaction. Specifically, he explores
different factors that influence human performance, trust in automation/autonomy,
and visual attention allocation in various domains including but not limited to aviation
and surface transportation.
Project Abstract
Technological advancement in automation has enabled researchers to explore the use of robots in single pilot operation. Such technologies have anthropomorphic features that resemble a human pilot. To operate an aircraft safely, human pilots will be required to trust a well-developed and reliable agent to receive its benefit. This raises two key questions: Will human pilots develop trust in an automated agent with anthropomorphic features in flight operation? How will human pilots develop trust in high-risk environments? The objective of this proposed project is to conduct a preliminary study to investigate these research questions. Specifically, the proposed study will utilize a modified flight simulation task supported by an automated agent with varying voice and appearance. Participants will complete this modified flight simulation task across varying levels of risk. Findings from this proposed study will provide guidance for devising future research studies on trust in anthropomorphic agents in flight operations. Ultimately, the proposed research project will provide design insights to help pilots work more effectively with robotic teammates in flight operations.
Dr. Melissa A. Scruggs
Assistant Professor of Geology
Fairmount College of Liberal Arts and Sciences
Dr. Melissa A. Scruggs is an Assistant Professor of Geology at Wichita State University.
She earned her B.S. in Geology from the University of Missouri–Kansas City, her M.S.
in Earth Science from California State University, Fresno, and her Ph.D. in Earth
Science from the University of California, Santa Barbara. Her research examines magma
storage conditions and eruption-triggering mechanisms at active volcanoes, including
Chaos Crags, Kīlauea, and most recently Newberry Volcano. She teaches courses in Mineralogy,
Petrology, Geochemistry, and Introductory Earth and Environmental Science. Dr. Scruggs
has received two university-sponsored grants to support her ongoing work at Newberry
Volcano and is a member of GSA, AGU, and IAVCEI. An advocate for accessible science
education, Dr. Scruggs actively engages in public outreach by livestreaming science
discussions and topics on Twitch and has delivered invited talks at Science on Tap
and Missouri State University. She is currently mentoring graduate and undergraduate
researchers and believes that everyone deserves the opportunity to learn, regardless
of background or life circumstances.
Project Abstract
The 1300-year-old Big Obsidian Flow (BOF) is the youngest lava flow in Oregon, situated inside the active Newberry caldera. Although the United States ranks Newberry as its 13th most hazardous volcano, the location and condition of the magma body beneath Newberry caldera is not well-known. A set of newly collected samples from BOF show great promise for recording deeper parts of a magma system not typically preserved by high-silica lavas. Mafic enclaves preserve evidence of mafic recharge—hotter magma that travels from deep below to replenish shallow systems, often triggering volcanic eruptions. This study examines rare mafic enclaves collected from the vent of BOF—the last lavas erupted within Newberry caldera—to get a better understanding of the most recent state of the magma body (or bodies) beneath it. Two-pyroxene and mineral-melt equilibria will be used to estimate pressures (i.e., depths) of crystallization for enclave magmas, providing the first such estimate derived from mineral data. Finally, whole rock geochemical data, including never-before-measured Nd-isotopes, will be used to evaluate the relationship between mafic enclaves and their host BOF lavas, to better understand how the rhyolitic melts which have driven explosive volcanism at Newberry for the last ~5,000 years are formed.