Engineering Commons^™

A Functional Ultrasound Imaging (Fusi) Pipeline For Investigating Brain-Wide Hemodynamics During Torpor-Like Hypothermia, Owen J. Culver

McKelvey School of Engineering Graduate Student Theses & Dissertations

Torpor is a regulated state of reduced metabolic demand that enables animals to conserve energy under unfavorable environmental conditions. The controlled induction of a similar state, termed synthetic torpor, has potential applications in ischemic protection, organ preservation, cancer treatment, radiation protection, and long-term spaceflight. Although neuronal populations within the preoptic hypothalamus have been shown to initiate hypothermic and hypometabolic states, the distributed cerebral hemodynamic dynamics accompanying their induction and maintenance remain poorly understood. In this thesis, we developed an accessible functional ultrasound imaging (fUSI) acquisition and analysis pipeline and applied it to investigate cerebral hemodynamics during chemogenetic activation of the …

Single Fluorogens And Orientation-Localization Microscopy For Quantifying Chemical And Biomolecular Dynamics At The Nanoscale, Yiyang Chen, Yuanxin Qiu, Matthew D. Lew

Electrical & Systems Engineering Publications and Presentations

Many chemical systems look uniform only because ensemble measurements average over their most interesting molecules. Electron-transfer rates vary across electrode surfaces; lipid membranes contain nanodomains with distinct packing and fluidity; peptide aggregates exhibit local polymorphism; and biomolecular condensates contain transient networks of interactions that are blurred in ensemble images. A central challenge in chemical imaging is not simply to see smaller structures, but to measure chemical variables such as polarity, redox potential, and molecular confinement at the single-molecule level. In this Account, we describe how fluorogens, molecules whose brightness, blinking, spectral shifts, orientation, rotational mobility, and motion are directly shaped …

Laponite Nanosilicate As A Platform For Antigen–Adjuvant Co-Delivery In Vaccination, Haoyu Qi

McKelvey School of Engineering Graduate Student Theses & Dissertations

Nanosilicates are two-dimensional, charged nanomaterials with tunable surface chemistry that enable electrostatic interactions with proteins and nucleic acids. These properties make Laponite nanosilicate a promising platform for vaccine delivery, where coordinated antigen–adjuvant presentation and lymph node delivery are important for shaping immune responses. This thesis investigated nanosilicates as scaffolds for lysozyme-based antigen delivery and co-delivery with CpG.

The preparation method reduced the apparent size of the NS–Lys–CpG complex at pH 10, although neutralization to pH 7 promoted larger aggregate formation. In vivo IVIS imaging after footpad injection showed persistent Cy7-associated fluorescence at the injection site for up to three weeks …

Jme 4110: Drill-Powered Beach Umbrella Anchor, Matthew Barton, Tanin Ramnath, Marquan Bailey, Zachary Van-Horn, Kaelin Mendoza

Washington University / UMSL Mechanical Engineering Design Project JME 4110

A common and potentially hazardous situation faced by beachgoers is when standard umbrella anchors fail to hold during wind gusts, causing the umbrella to potentially go airborne and injure nearby people. Existing anchors require manual operation, leading to inconsistent grip and no resistance to different wind directions. Our project is a motorized three anchor system that drives augers into the sand to ensure a consistent grip and security against the wind.

Jme 4110: Drill Powered Pressure Washer, Kathryn Keele, Ashley Givance, Reagan Grass, Andrew Ellis, Jacob Thebeau

Washington University / UMSL Mechanical Engineering Design Project JME 4110

This project focuses on developing a drill-powered pressure washer attachment that connects to a standard cordless drill and garden hose. The device uses the drill as its only power source to pressurize water for cleaning applications. This portable design provides a convenient, low-cost alternative to traditional electric or gas-powered pressure washers.

Chatbot-Based Feedback + Revision And Reflection For Lab Reports, Janie Brennan

Generative AI Teaching Activities

Students will upload draft versions of laboratory reports to a specially designed chatbot trained on course guidelines and instructor preferences. The chatbot gives structured feedback on the submission, and then students update their work and write a reflection about the experience.

Cloud-Deployed Rna-Seq Analytics For Identifying Imaging And Therapeutic Targets In Chemotherapy-Induced Toxicities, Zhimu Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Chemotherapy has significantly improved cancer survival rates; however, many anticancer agents induce severe acute and chronic side effects that substantially reduce patient quality of life and limit therapeutic efficacy. Despite their clinical importance, the molecular mechanisms underlying chemotherapy-induced toxicities across different organs remain incompletely understood, in part due to the lack of integrated, scalable, and accessible analytical platforms capable of synthesizing large transcriptomic datasets across tissues and experimental models.

This thesis describes the development of a cloud-deployed RNA-seq analytics platform designed to identify candidate imaging biomarkers and therapeutic targets associated with chemotherapy induced toxicities. The platform integrates large-scale transcriptomic datasets …

Toward Vehicle-Agnostic Driving Signatures For Cognitive Impairment Prediction From Naturalistic Driving Data, Aadarsha Gopala Reddy

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis studies whether naturalistic driving data can help predict binary Clinical Dementia Rating (CDR) status while accounting for differences across vehicles. The final analytic dataset comprised 26,968 participant-weeks from 304 participants. Weekly driving features were derived from real-world telematics data and combined with four demographic covariates. Primary model comparisons used leave-one-participant-out (LOGO) cross-validation, with one individual held out at a time and pooled participant-level metrics used as the main reporting surface.

The main comparison includes six model families evaluated on the same dataset under a shared LOGO framework. Performance remained modest overall. GRU-DANN had the highest participant-level ROC AUC …

Largest 2-Regular Subgraphs In Complete S-Partite Graphs, Yiyang Jiang

McKelvey School of Engineering Graduate Student Theses & Dissertations

In this thesis, we focus on the class of complete $S$-partite graphs, for $S$ an undirected graph possibly with self-loops, and address the problem of finding largest $2$-regular subgraphs of these graphs, which can be formulated as an integer linear program. Roughly speaking, a complete $S$-partite graph is obtained by replacing every single node of $S$ with a number of nodes, preserving the edge/non-edge relations of $S$. Our motivation in studying largest $2$-regular subgraphs is rooted in the structural systems theory, particularly in the problem of finding largest subnetworks that can sustain controllability or asymptotic stability of the corresponding subsystems. …

Interaction-Aware Safe Planning For Human-Robot And Multi-Robot Systems, Haoyi Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Robots operating in shared environments must interact safely not only with static obstacles but also with other decision-making agents, including humans and other robots. In such settings, both safety and task completion depend on the ability to reason about interaction. Two major challenges arise. In human-robot interaction, future human behavior depends on latent internal factors, such as attentiveness and behavioral style, that are not directly observable to the robot. In multi-robot systems, decentralized reactive navigation can fail in cluttered environments when reciprocal interactions create deadlocks that prevent progress through narrow passages or bottlenecks. This thesis investigates these two challenges from …

Temperature And Environmental Implications On Ti3c2cl2 Mxene Degradation Process, Yang Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

MXenes, a rapidly emerging class of two-dimensional transition metal carbides and nitrides, have attracted considerable attention owing to their exceptional electrical, mechanical, and chemical properties. However, the inherent thinness of their atomic structure and the reactivity of their functional groups render MXenes susceptible to environmental degradation, whereby the lattice integrity is compromised and desirable material functionalities are dimin- ished. In this work, ex situ electron microscopy characterisation is performed on Ti₃C₂Cl₂ MXene specimens subjected to controlled gas environments — nitrogen gas (N₂) and air — at annealing temperatures of 200°C and 600°C, with …

Optimization Of Refolding, Purification, And Analytical Characterization Of Proinsulin(F25d) Soluble Antigen Array Immunotherapy, Abigail Richardson

McKelvey School of Engineering Graduate Student Theses & Dissertations

Type 1 Diabetes (T1D) is characterized by autoreactive immune responses to insulin and its precursor, proinsulin. Soluble antigen arrays (SAgAs) displaying the metabolically inactive proinsulin variant, proinsulin(F25D), represent a promising antigen‑specific immunotherapy candidate for T1D. However, the production of these platforms is hindered by substantial practical challenges, including protein aggregation, inefficient refolding, and the lack of sensitive analytical tools to verify quality and dosage. This work establishes an integrated, scalable pipeline for the purification, conjugation, and quantification of a proinsulin(F25D) SAgA. First, we optimized the refolding of recombinant methionine-proinsulin(F25D) (M-PI(F25D)) from inclusion bodies using controlled buffer systems and created a …

Improving Semantic Precision In Text-To-Image Diffusion Models Via Latent-Space Optimization And Semantically-Parsed Evaluation, Mohammad Rouie Miab

McKelvey School of Engineering Graduate Student Theses & Dissertations

Text-to-image diffusion models can produce visually impressive images from natural-language prompts, but they often fail to satisfy the detailed semantic constraints expressed in compositional prompts. Typical failure modes include omitted objects, merged entities, incorrect quantities, incorrect attribute binding, and leakage of one entity's attributes onto another. This thesis studies the problem of semantic precision in text-to-image generation: how faithfully a generated image satisfies the structured meaning of its prompt.   The thesis makes two linked contributions. First, it presents a training-free inference-time refinement method for diffusion-based image generation. The method operates directly in latent space during denoising and uses noun-phrase-aware cross-attention …

Voltage-Sensor–Targeting Modulators Of Iks: Identifying Critical Functional Groups Of C28 Via Electrophysiology And Sar Modeling, Jiacheng Huang

McKelvey School of Engineering Graduate Student Theses & Dissertations

I_Ks (KCNQ1/KCNE1) channels are essential for cardiac repolarization, and their dysfunction contributes to arrhythmogenic disorders such as Long QT Syndrome type 1 (LQT1). Pharmacological activation of I_Ks has therefore emerged as a promising therapeutic strategy. C28, a recently identified voltage-sensor–targeting activator, has been shown to markedly shift KCNQ1/KCNE1 voltage dependence and enhance current amplitude, validating the voltage-sensing domain (VSD) as a druggable site. However, the structural determinants that underlie C28’s activity remain incompletely understood. In this study, we aimed to identify critical functional groups of C28 by screening a structurally diverse set of C28-like analogs and evaluating their …

Multiscale Architecture Governs Stability In Suction-Actuated Variable Stiffness Catheters, Sheridan Lee

McKelvey School of Engineering Graduate Student Theses & Dissertations

Endovascular procedures require devices with widely varying mechanical properties: flexibility for navigating tortuous vessels and rigidity for stable therapeutic delivery. Suction-actuated variable stiffness sheaths address this challenge by incorporating axial wire string arrays that mechanically couple under suction to increase flexural rigidity. However, prototype devices achieve stiffening ratios below theoretical predictions, suggesting that interlayer mechanics and string positioning play a critical role. This study investigates whether interweaving polytetrafluoroethylene (PTFE) tape within the string array enhances flexural rigidity modulation and curvature stability. Prototype devices with varying wrap configurations were fabricated and evaluated using flexural testing, curvature stability testing, and mathematical modeling. …

Establishing Caenorhabditis Elegans As A Platform For Bioaccumulation And Selectivity Screening Of Anthelmintic Compounds, Jiarui Li

McKelvey School of Engineering Graduate Student Theses & Dissertations

To address the cuticular barrier in anthelmintic discovery, this study establishes a bifurcated framework in Caenorhabditis elegans. First, HPLC-based quantification of 14 PIM inhibitors revealed that cuticular penetrance is primarily dictated by phylogenetic lineage (Clade V) rather than ecological niche. Specifically, C. elegans demonstrated a significant pharmacokinetic correlation with the hookworm Ancylostoma ceylanicum (Clade V) but not the whipworm Trichuris muris (Clade I), validating it as a superior surrogate model for hookworm bioaccumulation. Within this small molecule inhibitor library, SGI-12was identified as a lead candidate with superior potency against C. elegans and bioaccumulation. Second, target validation using a C. …

Computational Fluid Dynamics (Cfd)-Based Performance Prediction Of Transcatheter Microvascular Plugs In Single-Ventricle Patients, Zhuhuan Zou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Transcatheter palliation using fenestrated Modified Micro Vascular Plugs (MVP) has emerged as a promising, minimally invasive alternative to surgical pulmonary artery banding (PAB) for high-risk neonates with single-ventricle physiology. However, clinical applications are currently limited by the difficulty in predicting the resulting pulmonary-to-systemic flow ratio () and the lack of a standardized approach for selecting the optimal fenestration size. This study utilizes patient-specific computational fluid dynamics (CFD) to quantitatively evaluate the impact of varying fenestration diameters on circulatory balance. Patient-specific 3D models of the pulmonary artery (PA) were reconstructed from imaging data for two clinical cases using SimVascular. Transient CFD …

Temporal Logic Planning In Semantic Maps Of Unknown Environments Using Tl-Rrt, Dongrui Yang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Autonomous mobile robots are increasingly expected to perform complex missions in unstructured environments. Traditional path planning approaches handle simple point-to-point navigation, but struggle with complex tasks that involve temporal and logical orderings of objectives. Linear Temporal Logic (LTL) provides a method for complex missions (e.g., sequential visits to multiple targets or surveillance tasks) in a strict way. This thesis presents an integrated planning framework that enables a robot to satisfy LTL-based task specifications in an unknown environment by combining a Temporal Logic RRT* (TL-RRT*) planner with semantic mapping. The robot builds a semantic map of its environment online using simultaneous …

Data-Driven Multimodal Mri Representation Learning For Subtype Discovery And Disease Progression Modeling In Parkinson’S Disease, Zihan Zhou

McKelvey School of Engineering Graduate Student Theses & Dissertations

Parkinson’s disease (PD) exhibits substantial clinical and neuroanatomical heterogeneity, limiting robust patient stratification and clinically meaningful progression modeling from MRI. We propose a unified multimodal 3D generative representation-learning framework that learns an interpretable latent space from co-registered baseline T1/T2 MRI with an edge-aware channel. Confound-corrected latent embeddings support unsupervised subtype discovery, while disease duration provides weak supervision to orient a continuous progression axis. On an independent external cohort (PPMI, N=171), the discovery-trained subtype structure shows significant partial replication (ARI=0.35; permutation test p=0.001) and enables longitudinal clinical stratification: mixed-effects modeling reveals subtype-dependent MDS-UPDRS III progression, with the strongest effect in subtype …

Analysis Of Oscillating Flow Over A 2-D Airfoil With Flow Reversal, Colter Couillard-Rodak

McKelvey School of Engineering Graduate Student Theses & Dissertations

Finite-state models are useful tools in modeling the aerodynamics of rotorcraft in flight simulators. 2-D and 3-D finite-state models have been developed and compared to closed form solutions, however these models are currently unable to handle situations where the freestream changes directions and the rotor re-enters its own wake. A 2-D finite state model was previously developed that includes a parameter that accounts for the change in free stream. This model, however, contains an inherent stability issue at the instant that the velocity changes direction.

The effects of this instability can be mitigated in certain flow conditions. A purely oscillatory …

Side-To-Side Differences In Three-Dimensional Femoral Head Coverage Associated With Initial Symptom Development In Patients With Bilateral Developmental Dysplasia Of The Hip, Jiayi Sun

McKelvey School of Engineering Graduate Student Theses & Dissertations

Developmental dysplasia of the hip (DDH) is characterized by insufficient acetabular coverage of the femoral head and is a recognized cause of hip pain, instability, and early osteoarthritis. Although bilateral deformity is common, symptoms often first develop in only one hip. The purposes of this study were: (1) to determine whether, in patients with bilateral DDH, side-to-side differences in three-dimensional (3D) femoral head coverage vary according to radiographic symmetry defined by the lateral center-edge angle (LCEA); and (2) to determine whether hips that appear radiographically symmetric still demonstrate focal 3D asymmetry.

This retrospective imaging-based study included patients with bilateral DDH …

Board-Level Operating System Infrastructure In Rust, Lydia Klaus

McKelvey School of Engineering Graduate Student Theses & Dissertations

Memory and multi-threading problems are the cause of many exploits and security vulnerabilities, and errors of this nature are easy to cause in programming languages such as C and C++. Despite this, these languages are still heavily used for systems programming and underpin the majority of operating system kernels. This is partially due to a lack of suitable replacements; however, Rust is becoming more prominent as an option for systems programming. This language features a much more stringent approach to memory and multi-threading safety. It also aims to support a wide range of hardware targets, including microcontrollers, which have long …

Conditioning Hierarchical Diffusion Transformers On Rf Circuit Parameters, Ethan Morton

McKelvey School of Engineering Graduate Student Theses & Dissertations

As modern ML techniques have become increasingly advanced, they have begun to be integrated into wireless RF systems for classification, identification, and spectrum management. Deep Neural Networks (DNNs) enable RF system operators and designers to design more flexible systems with greater robustness to errors and attacks. However, neural networks require significant amounts of properly annotated data to train. Current data labeling methods lack the ability to obtain reliable true labels for circuit properties such as carrier frequency offset (CFO), power amplifier (PA) non-linearity, and in-phase/quadrature (IQ) imbalance. This thesis investigates the efficacy of a novel architecture, RF-Diffusion, for generating high-quality …

Design Of An Extensible And Scalable Data Acquisition System For Pulse Shape Discrimination, Prince John

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis presents the design and development of a highly scalable, end-to-end data acquisition (DAQ) system for nuclear physics experiments that can be deployed in configurations ranging from a few to thousands of detector channels. The system is built as an extensible platform composed of modular 16-channel chipboards that support a wide range of scintillator and detector types and perform real-time, on-board data sparsification and pulse-shape processing. Three versions of the chipboard have been fabricated to date.

The DAQ architecture is based on a family of analog pulse-shape-processing application- specific integrated circuits (ASICs) developed by the IC Design Laboratory at …

Study Of Complex Biological Systems Through Ai-Empowered Metabolomic Analysis And Modeling, Runyu Zhao

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation establishes an integrated framework that leverages artificial intelligence (AI) and advanced metabolomics to overcome the "complexity bottleneck" in microbial engineering, specifically addressing the global crises of plastic waste and carbon emissions. By framing the research within the complex biosystems for effective bioproduction and bioremediation, this work develops novel strategies to engineer and analyze biological systems for a circular bioeconomy. In the "Build" phase (Chapter 2), the study addresses the instability of synthetic microbial consortia. By utilizing calcium-alginate hydrogel compartmentalization, the research successfully decouples the growth of the phototroph Synechococcus elongatus from its heterotrophic partners (P. putida and Y. …

Inference-Time Scaling For Robust And Adaptive Computational Imaging, Yuyang Hu

McKelvey School of Engineering Graduate Student Theses & Dissertations

Computational imaging has transformed fields such as medical imaging, computational photography, and remote sensing by combining physical measurement models with advanced image reconstruction algorithms. Two major paradigms have driven significant progress: model-based deep learning (MBDL), which integrates learned priors with physics-based data consistency, and generative models, especially diffusion models, which capture complex image distributions and enable posterior sampling for uncertainty quantification. Despite their success, most existing methods still operate under static inference: they rely on fixed pretrained priors, predetermined sampling procedures, and a fixed forward model during reconstruction. This rigidity limits their robustness in the presence of distribution shift, complex …

Individualized Models For Perception And Cognition, Dominic Marticorena

McKelvey School of Engineering Graduate Student Theses & Dissertations

This dissertation develops individualized models of perceptual and cognitive behavior, inferring latent capacities from limited data with sufficient efficiency, precision, and generality for person-level prediction. In perception, a nonparametric Bayesian framework for adaptive psychophysics is extended from audition to vision, producing an estimator that recovers dense individualized contrast sensitivity profiles through variational inference, a generalized kernel, and information-guided stimulus selection. A multitask extension enables simultaneous estimation of multiple psychometric fields by exploiting shared latent structure. Transferring this inferential logic to cognition, where relevant dimensions must be supplied by task design rather than physics, requires new measurement infrastructure. A Minecraft-based platform …

Opportunistic Breast Cancer Detection With Photon-Counting Ct: A Quantitative Pilot Study Of Reconstruction-Dependent Image Quality, Graham Hannon

McKelvey School of Engineering Graduate Student Theses & Dissertations

Photon-counting computed tomography (PCCT) has emerged as a promising imaging modality with improved spatial resolution and contrast capabilities compared to conventional energy-integrating detector systems. These advantages present an opportunity for opportunistic detection of breast cancer in routine thoracic CT scans that include breast tissue. In this pilot study, we evaluated the feasibility of opportunistic breast cancer detection using clinical PCCT data through quantitative image analysis. Two patients with confirmed breast malignancies and corresponding thoracic PCCT scans were retrospectively analyzed. Dedicated reconstructions were performed with varying convolution kernels, field-of-view sizes, and virtual monoenergetic spectra. Image quality was assessed using signal-to-noise ratio …

​ Planning, Control, And State Estimation For Chain-Style Modular Robots​, Sebastian Theiler, Yucheng Nie, Joshua P. Kevil

Electrical and Systems Engineering Capstone Design Projects

Traditional robots have fixed shapes, limiting their ability to adapt to complex or dynamic environments. Modular robotic systems are composed of identical robot modules that can connect and disconnect to form different structures. This allows the robots to form bridges to cross voids and split apart to fit into tight corridors. However, while previous modular robotics research heavily emphasizes reconfiguration planning, comprehensive motion planning remains underexplored. We introduce a novel, end-to-end framework for the planning, state estimation, and control of chain-style modular robot swarms. Our system includes a custom network flow planner that maps polygonal environments into a Reeb graph …

Exploring Hemodynamic Signatures Using Event Camera, Zaid Ahmed

McKelvey School of Engineering Graduate Student Theses & Dissertations

This thesis investigates event-based sensing for hemodynamic measurements in transmission mode through the human finger. Conventional frame-based imagers are limited by exposure time, frame rate, and motion blur, which reduce sensitivity to fast optical transients. To address these bottlenecks, this thesis introduces a novel transmission-mode sensing framework using a Prophesee EVK4 HD neuromorphic sensor. By capturing asynchronous ON/OFF events generated by local intensity changes, this work presents a new approach to three tasks: intra-finger pulse transit time (PTT) and pulse wave velocity (PWV) estimation, event-based transmission mode laser speckle contrast imaging (LSCI), and Flicker Spike Arrival Time (FSAT) Delay Mapping, …