The Sensors, Energy, and Automation Lab (SEAL) aims to gamify undergraduate research by instituting a leaderboard, awarding points for tasks, assigning ranks for accomplishments and published papers, and framing research directions as Quests. Individuals receive a character sheet with a health bar, while groups compete against one another in Racetrack- a software for team challenges. Gamification in educational settings is well-studied: gamifying learning can boost students’ motivation, retention, and challenge appraisal. However, research indicates that the efficacy of gamification varies dramatically, particularly personality traits like extraversion, which correlate more positively with success in software with leaderboards. Significant gaps exist in gamification literature; existing research primarily studies gamification in classrooms, not workplaces or research environments. Further, the studies fail to incorporate modern approaches to psychology. The socio-psychological model suggests personalities and behaviors differ depending on the environment, meaning people may exhibit different personality traits in gamified environments. Moreover, gamer motivation, a personality test tailored to predicting player personality with strong correlations to the Big Five (psychological scale for key personality traits), has yet to be tested in gamification studies. By accounting for contemporary psychological theory, SEAL aims to rigorously test the hypothesis that gamification is an effective structure in lab organizations through multi-year longitudinal study on a scale never seen in gamification literature. SEAL’s large cohort and gamified structure offer a perfect platform to analyze the role of demographic and personality type in gamification outcomes. Our preliminary results explored collected qualitative and quantitative data on demographics, gamer motivation personality, and perceptions of the SEAL system by anonymously surveying 81 associates. Our longitudinal study contributes to the growing literature on gamification; a solution potentially improving productivity in research ecosystems.

The increasing concern over global warming has driven interest in clean energy solutions, with piezoelectricity emerging as a promising alternative. Piezoelectric materials generate electric voltage under external mechanical forces, offering an innovative method for energy harvesting. This work derives a system of partial differential equations (PDEs) and their accompanying boundary conditions that describe the coupled elastic-electric behavior of an Euler-Bernoulli piezoelectric beam. Under the quasi-static approximation for the electrical field, the assumptions of Euler-Bernoulli beam theory, and the constitutive relations for the 3-1 piezoelectric coupling mode (i.e., voltage is generated in a direction perpendicular to external mechanical force), we develop a Hamilton’s variational principle to derive the governing equations and boundary conditions for the piezoelectric Euler-Bernoulli beam. The obtained equations consist of Gauss’s law of electrostatics and the Euler-Bernoulli beam equation that are coupled due to the piezoelectric effect: apparent electric charges that depend on elastic deflection appear in Gauss’s law, while apparent mechanical forces and moments that depend on the electric potential appear in the Euler-Bernoulli beam equation and its boundary conditions. The derivation from first principles, as well as the study of the governing equations constitutes a fundamental framework for analyzing piezoelectric beam behavior, with implications to the improvement of design of piezoelectric energy harvesters.

The project aims to design a multi-modal sensor network with VLF antennas will be implemented to model the ionospheric D-region in real-time. In consideration of not having ground truth data, such a network will address the ill-posed problem of inverting with robust regularization techniques. High-data-rate acquisition, high-data-rate processing, and dynamically adaptable auto-tuning will be included in our design. Drawing on experience with the NeSSI, modularity and a digital bus for centrally processed, real-time processing will be part of a standardized, modular sensor network that will be designed. The D-region, an upper atmospheric dusty plasma, controls radio wave propagation via fluctuations in charge. Numerical simulations in our work simulate such occurrences as HF to UHF range radar echoes, validated through experiments in radar labs. Ionospheric instabilities in occurrences such as SAPS events generated through space weather result in GPS and Starlink communications outages. 3D electrostatic fluid and gyrokinetic equations are included in our model, which is significant for describing such instabilities. Real-time observation, predictive maintenance, and reliability in communications networks are enhanced through such studies.

Chimeric Antigen Receptor (CAR) T-cell therapy has revolutionized immunotherapy for blood cancers, achieving unprecedented outcomes for many patients. However, variability in treatment responses—ranging from complete remission to relapse or severe side effects—remains a critical challenge. Mathematical and computational models that have been calibrated to experimental data can help to predict treatment efficacy and inform personalized therapeutic strategies. Working with Dr. Konstantinos Mamis (UW Applied Mathematics) and Dr. Katherine Owens (Fred Hutchinson Cancer Center), Rohan Pandey and Ray Chen (UW ACMS Department) employ models consisting of systems of ordinary differential equations (ODEs)- to simulate tumor and CAR T-cell dynamics. Though several prior mathematical models analyzing the interactions between CAR T-cells, tumor cells, and effector cells under varying treatment conditions exist, there has not been a systematic comparison of models representing competing mechanistic hypotheses against data from patients undergoing CAR T-cell treatment and/or chemotherapy. For two existing mathematical models, we explore the practical identifiability of model parameters using synthetic data and a population approach with nonlinear mixed effects implemented in Monolix. Furthermore, we calibrate the model parameters to real data from 10 patients with B-cell acute Lymphoblastic Leukemia (B-ALL) and identify the most accurate and parsimonious of the existing models. Finally, we determine and study the effect of key variables that largely influence patient responses to therapy, including those associated with sustained remission or relapse. This computational oncology work has the potential to inform strategies for optimal CAR T-cell therapy, improve patient outcomes, and further innovation in cancer treatment.

Carbon fiber reinforced polymer (CFRP) is a composite material consisting of carbon fiber and cured resin layers. Its usage is especially prominent in Washington state, whose aerospace sector generates over 70 billion dollars in revenue each year and supports more than 250,000 jobs. Despite its relatively high material value of more than $40 per pound, around two million pounds of CFRP waste are sent to landfills in Washington each year. Assessments show that the costs of this waste and its disposal are a significant financial expense for manufacturers, potentially exceeding hundreds of thousands of dollars. Additionally, the complex and high-temperature manufacturing process required to produce CFRP is extremely energy intensive and generates high levels of greenhouse gas emissions. My research seeks to identify the current state of CFRP recycling in the Washington aerospace sector and examine its potential to address these industry-wide economic and environmental concerns. Through conducting market analysis of aerospace manufacturers in Washington, I will collect data on current levels of CFRP recycling and understand to what extent these recycling processes are effective in reducing environmental impact and improving business profitability. I aim to identify the main barriers that manufacturers face when attempting to implement recycling processes, in order to establish what developments would be necessary to expand the adoption of CFRP recycling across the industry. I anticipate that by identifying these developments and the processes required to achieve them, there will be opportunities for increased collaboration between aerospace manufacturers and CFRP recyclers. With Earth’s resources rapidly depleting and demand for CFRP steadily rising, CFRP recycling is a critical solution that will ensure that aerospace manufacturing can be sustainable, circular and economically feasible.