Engineering Commons^™

Deep Learning For Wireless Communications, Swarada Ajit Kulkarni

Electrical Engineering Dissertations

The rapid evolution of wireless communication imposes stringent requirements for ultra-reliable, low-latency transmission in dynamic, interference-prone environments. Traditional model-driven signal processing struggles to adapt to nonlinear hardware effects, time-varying channels, and complex interference patterns. Deep learning (DL) offers a transformative, data-driven alternative, enabling end-to-end optimization and robust adaptation under uncertain propagation conditions.

This dissertation investigates deep learning architectures for intelligent and resilient wireless communication through three complementary contributions. The first introduces a Vision Transformer (ViT)-based modulation classification framework that leverages self-attention to capture local and global dependencies in spectrogram representations of Quadrature Amplitude Modulation (QAM) signals. The ViT achieves superior …

A Transdisciplinary Approach To Advancing Water Security And Public Health: The “Nurse + Engineer” Model For Achieving Sustainability In Wash Systems Using Community-Based Participatory Research, Daniel B. Oerther, Sarah Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

Human health is linked to the health of the environment, a concept referred to as planetary health. As environmental challenges become increasingly complex, single-disciplinary approaches are insufficient to achieve sustainable solutions. This article presents a transdisciplinary framework, termed the "Nurse + Engineer" model, as a novel methodology for addressing complex problems at the nexus of environmental engineering and public health. The model integrates the technical design and systems-level thinking of environmental engineering with the community-based, patient-centered care of nursing. This work details the key lessons learned from the retrospective application of this framework to a series of multi-year, community-based participatory …

Environmental Engineers Develop Solutions To Problems Of Planetary Health: The Legacy Of Professor P. Aarne Vesilind, Daniel B. Oerther

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The principal ethical obligation of the engineering profession, to "hold paramount the health, safety, and welfare of the public," has been challenged for decades. Professor P. Aarne Vesilind identified two primary deficiencies: an anthropocentric bias that values nature only instrumentally and the use of non-mandatory, aspirational language for environmental protection, which resulted in the exclusion of enforceable environmental canons. This paper argues that two recent developments provide a comprehensive response to Vesilind's recommendations for engineering ethics. First, the United States Bureau of Labor Statistics has redefined environmental engineering as "developing solutions to problems of planetary health." Second, Oerther proposed a …

Sainik Vol 1 Issue 2, Sastra Deemed To Be University

SAINIK

No abstract provided.

Training A Cellpose Model For T-Cell Cytoplasm And Nucleus Segmentation, William Laws, Matthew Lindley, Irene Georgakoudi

Wetterhahn Science Symposium Posters

Accurate single-cell segmentation of cytoplasm from nucleus in autofluorescence images is critical for quantifying cellular metabolism using the optical redox ratio (FAD / FAD+NAD(P)H). However, automated cytoplasmic segmentation of T cell two-photon excitation fluorescence images remains challenging due to low signal-to-noise ratio, small cell size, and variability in cell brightness across imaging conditions. Here, we present a pipeline combining a custom-trained Cellpose-SAM model with an adapted cytoplasmic post-processing algorithm (CPPA) for automated single-cell metabolic analysis of T cell NAD(P)H autofluorescence images. Raw 2048×2048 pixel images were spatially binned 4×4 in MATLAB to improve signal-to-noise ratio and reduce processing time. A …

Powering The Machine, Draining The Planet: Whether U.S. Environmental Law Is Equipped To Regulate The Energy And Water Demands Of Ai Data Centers, Michael Marcu

Journal of Earth and Life Science

Artificial intelligence (AI) data centers have become one of the United States' fastest-growing and least-regulated sources of environmental stress. In 2024 alone, U.S. data centers consumed 183 terawatt-hours (TWh) of electricity more than the entire nation of Pakistan and consumed an estimated 17 billion gallons of water (IEA, 2025; Berkeley Lab, 2024). By 2030, electricity demand from these facilities is projected to reach 426 TWh, a 133% increase in six years (Pew Research Center, 2025). This paper examines whether the existing U.S. environmental regulatory framework put by the National Environmental Policy Act (NEPA), the Clean Water Act (CWA), and the …

Fiber-Reinforced Composites For Vaginal Tissue Engineering Applications, Samyuktha S. Kolluru, Abir Hamdaoui, Annabella M. Mascot, Siobhan S. Sutcliffe, Jerry L. Lowder, Michelle L. Oyen, Samantha G. Zambuto

Mechanical Engineering Faculty Publications

The vagina is a fibromuscular tube-shaped organ that plays critical roles in menstruation, pregnancy, and female sexual health. Vaginal tissue constituents, including cells and extracellular matrix components, contribute to tissue structure, function, and prevention of injury and pathology. However, much microstructural function remains unknown, including how the fiber-cell and cell–cell interactions influence macromechanical properties. A deeper understanding of these interactions will provide critical information needed to reduce and prevent vaginal pathologies. Our objective for this work is to design a novel tissue-mimicking biomaterial for vaginal tissue engineering, and characterize its biological and mechanical performance in the vaginal microenvironment. We successfully …

First Water-To-Ligand Substitution Dictates Co2+/Ni2+ Extraction Selectivity, Kailong Zhang, Yuxuan Zhang, Bin Ji, Rick Q. Honaker, Isabel C. Escobar, Jian Shi, Qing Shao

Mining Engineering Faculty Publications

Solvent extraction is a crucial technology for the large-scale recovery of critical metals. One key challenge is to develop ligands with high ionic selectivity, especially for ions with similar properties. Manipulating ionic solvation emerges as a viable approach to enhance the selectivity. However, such manipulation requires a thorough understanding of the thermodynamics underlying ligand-induced variation in ionic solvation. We investigated the thermodynamics governing the binding of two organophosphorus ligands (Cyanex 272 and D2EHPA) with Co²⁺ and Ni²⁺ at the aqueous-organic liquid–liquid interface using a combination of experiments and computations. UV-vis and IR spectroscopy confirmed that extraction induces solvation …

Field-Based Device To Test Possible Tbis, Colin Laidlaw, Lauren Powers

Student Research Design & Innovation Symposium

Traumatic brain injury (TBI) remains a major cause of death in the United States. In emergency field care, first responders must quickly assess neurological status and determine appropriate patient transport. The Glasgow Coma Scale (GCS), the primary neurological assessment used in the field, correctly identifies TBI only about 40 percent of the time. In Rhode Island, state protocols require all patients with suspected TBI to be transported to a Level I trauma center. This creates challenges when trauma resources are limited or when symptoms are subtle and difficult to evaluate in the field. To address this issue, a reaction time …

Story Builders, Jillian Mercer

Student Research Design & Innovation Symposium

The objective of this project was to create an engaging and educational game for children in the 1st - 3rd grade that strengthened reading comprehension skills and fostered positive associations with reading through collaboration, tactile learning, and fun. The COVID-19 pandemic forced the shutdown of schools and switched learning to online only, which caused a lasting negative impact to childhood literacy in America. Research and first-hand testimony revealed that children developed a more positive relationship to reading when it was a group activity, as opposed to solitary, screen-based learning. In the early stages of prototyping, words in colored blocks were …

Futura Type Book, Ava Nuckolls

Student Research Design & Innovation Symposium

This creative piece was the final project for GDES: 2000 Typography. The goal of the project was to create a book about a chosen font that consisted of at least 6 pages. The book would tell a brief history of the font, while showcasing weights, styles, and anatomy. Each book would have a cohesive theme throughout. The font chosen specifically for this project was Futura by Paul Renner. The theme was retro-futuristic and consisted of green text and graphics on top of a black background. The process of this piece started with choosing a font and creating thumbnail sketches. After …

One Product, One Hook, Thousands Of Views, Mackenzie Lauto

Student Research Design & Innovation Symposium

The video highlights how a single, well-positioned product, Cocokind lip balm, with a great discounted deal of running, can generate strong engagement through strategic short-form content. By combining a clear value proposition (a high-quality product at a discounted price) with a scroll-stopping hook, the video demonstrates how brands can quickly capture audience attention. This approach has urgency, relatability, and visual appeal to drive views, interaction, and potential conversions, showcasing the effectiveness of simplicity in social media marketing.

Burghi Variable Candy Land Type Book, Lily Guyon

Student Research Design & Innovation Symposium

This project showcases a comprehensive understanding of a chosen typeface by exploring its visual identity and emotional connection. The student developed a type book focused on the font's aesthetic and its creator, incorporating two artistic quotes that align with the project's overall theme. The book features a detailed analysis of both Burghi Big and Burghi Small, including a labeled breakdown of letter anatomy and a full display of the alphabet, numbers, and symbols. Concluding with a historical overview of the font and its designer, the project finishes with a formal references page containing the student's credentials and course information.

Standard Issue, Tyler Miles

Student Research Design & Innovation Symposium

Created for GDES 2000, STANDARD ISSUE explored the font Helvetica and rigid masculinity using archival military testing imagery. The project deconstructed the typeface's neutrality, personifying Helvetica as a clinical figure of, "structured, pervasive, and subverted" nature. By juxtaposing 1950s Swiss design with the physical vulnerability of military experimentation, the work examined the "bureaucracy of language," ultimately framing the "standard" as a form of armor that humans wear as much as it wears them.

Paraná Fiz, Cloey Dias

Student Research Design & Innovation Symposium

This project focused on the conceptualization and design of a beverage brand inspired by the Paraná River located in Argentina. The river, the second longest in South America, was used as both a cultural and visual reference, symbolizing movement, energy, and natural vitality. These characteristics guided the overall concept and aesthetic direction of " Paraná Fiz", a yerba mate-infused soda water brand. The product aimed to merge traditional Argentine influences with a modern beverage format through flavors inspired by popular Argentine fruits. The project involved extensive visual branding development, including the creation of a custom logo, four distinct flavor identities, …

6 Degrees Of Freedom Robotic Arm, Vansh Garg , ‘26, Eric Chen , ‘26, Kaw Moo , ‘26

Senior Theses, Projects, and Awards

This project involved the design, fabrication, and testing of a 6 degree of freedom robotic arm. The goal was to demonstrate that a low-cost, 3D-printed system could achieve useful strength, modularity, and basic manipulation for simple pick-and-place tasks. Potential applications include education, prototyping, hobbyist robotics, and low-precision automation.

The mechanical system uses 3D-printed arm links, cycloidal gearboxes, belt-driven transmission, bearings, and a modular end effector. These components were selected to balance cost, manufacturability, and performance, with gear reduction used to increase available joint torque. The electrical system provides motor actuation, power distribution, and controller integration, while the software enables command-based …

Cell-To-Pack Modeling Of Lithium-Ion Batteries: From Bayesian Parameterization To Pack-Level Optimization, Derek Slack

Graduate Theses, Dissertations, and Problem Reports (ETD)

One of the major hurdles for electric or hybrid aviation is the comparative energy density between lithium-ion batteries and jet fuel. To help obtain maximal power-to-weight ratio in electric or hybrid powertrains the battery pack design should be optimized to be as light as possible while meeting thermal safety and power requirements. The proposed solution is an optimization routine beginning with a cell-level parameter estimation of lithium-ion battery cells, where data driven Bayesian Gaussian Processes replace empirically or analytically derived parameters in a first principles electrochemical model in PyBaMM, as functions of the transient state of the cell. The resulting …

Fairness Without Demographic Attributes In Medical Vision–Language Models, Ahsan Habib Akash

Graduate Theses, Dissertations, and Problem Reports (ETD)

Vision–language models (VLMs) and the embedding models that underlie them have become the default representation layer for multimodal artificial intelligence. Trained by contrastive alignment over enormous, loosely curated image–text corpora, they inherit the demographic skew of that data, and they encode it in the geometry of the shared embedding space itself. The consequence is a model that performs unevenly across demographic groups even when no protected attribute is ever supplied as an input. In consumer applications this is an equity problem; in medicine it is a safety problem, because an embedding that is systematically less discriminative for one subpopulation translates …

Dielectrophoretic Biomarkers For Cancer Detection And Cell Analysis: Integrating Microfluidics And Ai, Raphael Olumide Oladokun

Graduate Theses, Dissertations, and Problem Reports (ETD)

Pancreatic ductal adenocarcinoma (PDAC) carries a five-year survival rate of 13%, driven largely by late-stage diagnosis and the absence of sensitive noninvasive screening tools. Current diagnostic methods lack the sensitivity to detect disease-associated systemic changes at early and precancerous stages, representing a critical clinical gap. This dissertation addresses the central hypothesis that PDAC and its pathological subtypes induce measurable, disease-associated electrophysiological changes in circulating PBMCs that can serve as correlative liquid-biopsy biomarkers. To test this hypothesis, this work asks: can dielectrophoresis (DEP), impedance and zeta potential analysis with AI-assisted classification distinguish benign pancreatic conditions (non-malignant control), precancerous lesions (primarily IPMNs), …

Application Of Passive Samplers For Exploring Remedial Progress In The Torch Lake Aoc And Interlake Variability Of Pcbs, Cailin B. Bishop

Dissertations, Master's Theses and Master's Reports

This study evaluates changes in dissolved polychlorinated biphenyl (PCB) concentrations in Torch Lake, Michigan, an Area of Concern shaped by decades of legacy contamination and evolving restoration policy. Passive samplers deployed across sites and seasons (2024–2025) show total PCB concentrations ranging from below detection to 110 pg/L (mean = 16.8 pg/L), representing an approximate 90% decline since 2005. Comparisons with regional reference lakes indicate no statistically significant difference (p = 0.84), suggesting concentrations may approach background atmospheric levels despite continued variability. Congener profiles indicate a shift toward lower-chlorinated PCBs, though interpretation of higher-chlorinated congeners is limited by slow sorption kinetics. …

Performance Comparison Of A Low Mass Vibratory Lunar Surface Compactor In Vacuum Versus Atmosphere, Robin D. Austerberry

Dissertations, Master's Theses and Master's Reports

As space agencies prepare to return to the moon, an emphasis is being placed on establishing a sustained human presence that requires permanent structures and supporting infrastructure, making site preparation a critical factor. Michigan Technological University’s Planetary Surface Technology Development Lab has developed a novel low-mass surface compaction tool for use on a site preparation vehicle in collaboration with Colorado School of Mines. Testing in vacuum is necessary to simulate a relevant environment, which is required to increase the technology readiness level of this tool to TRL 5. Testing concluded significant interactions between the presence of atmosphere and other factors. …

Microgravity-Induced Alterations In Left Atrial Hemodynamics And Thrombogenic Risk: Insights From Healthy And Atrial Fibrillation Models, Grace M. Hoeppner

Dissertations, Master's Theses and Master's Reports

Background: Microgravity exposure alters cardiovascular loading, yet its impact on left atrial flow dynamics and thrombotic risk remains poorly understood. This study investigates how spaceflight-relevant microgravity-induced changes in cardiac outflow affect left atrial hemodynamics in healthy individuals and patients with atrial fibrillation.

Methods: Patient-specific left atrial models were generated for three healthy individuals and three AF patients. Computational fluid dynamics (CFD) simulations were performed using each patient’s baseline mitral outflow waveform and two modified waveforms representing short- and long-duration post-flight cardiac loading changes derived from echocardiographic observations. Hemodynamic metrics included left atrial velocity, time averaged wall shear stress, oscillatory shear …

System-Level Assessment Of Non-Ideal Phase Change Material Behavior In Low Earth Orbit Spacecraft Thermal Control Models, Nathan S. Bruursema

Dissertations, Master's Theses and Master's Reports

Phase change materials (PCMs) are of interest in spacecraft thermal control because their latent heat capacity can provide passive thermal buffering during transient or cyclic heat loads. PCM behavior is often treated using idealized assumptions such as repeatable phase transition temperatures, consistent thermal accessibility across cycles, and full latent recovery. However, practical PCM behavior may be affected by non-ideal phenomena such as supercooling, interfacial resistance, and degradation of internal transport accessibility. This thesis examines the system-level relevance of these effects for low Earth orbit (LEO) spacecraft thermal control and identifies the operating conditions under which non-ideal PCM behavior becomes design-relevant. …

Development And Calibration Of A 2-D Diesel Oxidation Catalyst Filter (Docf) Model With Spatially Varying Washcoats Using Spacims And Engine Loading Data, Thomas K. Price

Dissertations, Master's Theses and Master's Reports

Diesel engine exhaust contains regulated species, including carbon monoxide, hydrocarbons, nitrogen oxides, and particulate matter (PM). Meeting increasingly stringent emission standards typically requires multiple aftertreatment components, motivating the development of multifunctional devices that reduce system size, cost, and catalyst usage. Computational models are essential for guiding this design process; however, existing models primarily focus on single-function devices and rarely capture the behavior of multifunctional systems with multiple catalyst washcoats. This work presents a physics-based model of a wall-flow diesel oxidation catalyst filter (DOCF), a multifunctional device that integrates the roles of a diesel oxidation catalyst and a diesel particulate filter …

On The Vibrational Dynamics Of Wind Turbine Blades: The Oscillatory Response To Gust Pulses, And The Physical Mechanisms Behind Them, North A. Yates

Dissertations, Master's Theses and Master's Reports

An easily noticed trend in the utility-scale wind turbine industry is that the size of the machines has continued to increase over time. While this may have benefits in terms of increasing the power generation for a single turbine, a major drawback is the rate with which the weight of the turbine blades grow. To ensure these larger machines can be utilized, efforts are being put forth to create lighter blades. This may fix the weight issue, but brings on a new one; these lighter blades can also be more flexible than previously studied ones. It is, therefore, vitally important …

Typology And Spatiotemporal Patterns Of Illegal Fishing Activities In The Philippines: Implications For Fisheries Management, Marlowe O. Acevedo, Tzu-Yun Ching, Chih-Shin Chen

Journal of Marine Science and Technology–Taiwan

Illegal, unreported, and unregulated (IUU) fishing activity is a global threat and continues to undermine the effectiveness of fisheries regulations and management measures. However, the extent of illegal fishing in Philippine waters remains unclear. This study aims to identify the types of illegal fishing in Philippine waters and analyzed their temporal and spatial patterns. Data were obtained from the records of the Philippine Coast Guards (PCG) and Maritime Law Enforcement Agencies from 2015 to 2020. A total of 602 apprehensions were recorded, resulting in 813 violations, of which 630 cases were fishery violations. Most of the watercrafts involved in the …

Delay-Doppler Integrated Sensing And Communications (Dd-Isac) With Predictive Beamforming, Mohammad Abdul Mobin, Yanjun Pan, Jingxian Wu

Electrical Engineering and Computer Science Faculty Publications and Presentations

A new delay-Doppler (DD) integrated sensing and communications (ISAC) framework is proposed for unmanned aerial vehicle (UAV) systems. In the DD-ISAC framework, both sensing and communications are performed by using the orthogonal delay Doppler division multiplexing (ODDM) waveforms, which unify sensing and communication designs through the unique ODDM waveform properties, such as local DD-domain bi-orthogonality and dual-resolution. Specifically, the dual-resolution property enables the generation of a range-Doppler map for accurate and low complexity sensing, and the bi-orthogonality minimizes interference for both sensing and communications. The ODDM waveforms are used in combination with the phase comparison monopulse technique and a scaled …

Cats 2.0: Leveraging Large Language Models And Graph Databases For Robust Arabic Sms E-Commerce Systems, M. Samir Abou El-Seoud, Daoud M. Daoud 2

Computer Science

Arabic SMS-based e-commerce platforms pose unique challenges due to the spontaneous and noisy nature of user-generated text (e.g., abbreviations, dialectal Arabic, or “Arabizi” transliterations). In this paper, we present Classified Ads Text Service (CATS) 2.0, an improved classified ads system that combines probabilistic large language models (LLMs) with deterministic graph-based knowledge representations to achieve robust understanding and matching of Arabic SMS content. Building on earlier work that emphasized the importance of integrating sublanguage analysis with content-oriented methods, our approach uses a hybrid pipeline: an LLM interprets free-text messages and extracts structured information, which is then inserted into a Neo4j graph …

Machine-Learning- And Iot-Based Approach For Predicting Water Quality Using Data Classification And Explainable Ai Technique, M. Samir Abou El-Seoud, Omar H. Karam 2, Hosam El-Sofany 3

Computer Science

Maintaining water quality is crucial for both public health and environmental sustainability. This study proposes a machine-learning- (ML-) and Internet-of-Things- (IoT-) based approach to water quality prediction that utilizes explainable artificial intelligence (XAI) and data classification techniques. The proposed approach integrates IoT devices to enhance real-time data collection, facilitating continuous monitoring and early anomaly detection. Ten different ML classifiers—Decision Trees, K-Nearest Neighbors, XGBoost, Naïve Bayes, Logistic Regression, AdaBoost, Random Forests, Support Vector Machines, Voting, and Multi-Layer Perceptron—were evaluated to find out which one works best for predicting water quality. We used three distinct approaches for feature selection: analysis of variance …

Eeg And Imu Gait Signal Processing: A Comparative Assessment Of The "Reza" Exponential Filter And Classic Filters, Reza Pousti, Daniel M. Russell, Derek C. Monroe, Christopher K. Rhea

Rehabilitation Sciences Faculty Publications

Noise degrades both EEG and gait signals, and classical IIR filters (Butterworth, Chebyshev, elliptic) involve trade-offs between passband flatness, ripple, and roll-off. This study compared a novel exponential "Reza" filter with these designs for neural and locomotor data. We analyzed an open-source mobile brain-body imaging dataset with EEG and gait data from 49 healthy adults (EEG: 256-channel, 512 Hz; IMUs: six APDM Opals, 128 Hz). EEG channels were grand-averaged and band-pass filtered at 0.5-50 Hz, while IMU axes were averaged and band-pass filtered at 0.5-5 Hz. The outcomes were signal-to-noise ratio SNR (dB) and band-integrated Welch PSD (EEG:0.5-50 Hz; IMU:0.5-5 …