Digital Commons Network^™

The Pebble In The Shoe, Marcos Fernandez Tous

The Cicadian

This piece offers an introspective reflection by an educator at the University of North Dakota, blending phenomenological perspectives on the nature of education with the embodied experience of participating in a sweat lodge. Framed by a meandering walk across campus, the narrative interweaves several thematic threads: the tension between clarification and explanation, the values that should guide technology education, and the role of nature with its inherent, chaotic vitality. Although the text adopts a stream‑of‑consciousness approach, it does so without leaning on the established stylistic traditions of Proust, Joyce, or Faulkner. The work is also poetic in tone, suggesting that …

Testing And Qualification Of Low-Voltage Power Supplies For The Atlas Tile Hadronic Calorimeter Phase-Ii Upgrade, Justice A. Jones

2026 Spring Honors Capstones Projects

The High Luminosity upgrade of the Large Hadron Collider (HL-LHC) places increased thermal and operational demands on detector electronics, requiring highly reliable power systems. The ATLAS Tile Hadronic Calorimeter (TileCal) uses low-voltage power supply (LVPS) bricks to power front-end electronics, but these units operate in inaccessible regions, making failures difficult to repair. Therefore, rigorous qualification procedures are essential. This work focuses on improving LVPS reliability through a structured burn-in process. Each unit undergoes pre-burn-in electrical verification using a Single Test Stand (STS), followed by sustained operation under load and elevated temperature, and post-burn-in requalification. Standard cooling conditions limit temperatures to …

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 …

Riki&Dolphin: Real Time Data Transmission From The Bottom Of A Cave To A Website, Luca Tringali, Giacomo Canciani Dr., Tecla Tripari, Alexander Debenjak, Caterina Bearzotti

International Journal of Speleology

Coming from over 10 years of experience in cave monitoring in northeast Italy, Gruppo Speleologico Talpe del Carso, has designed Riki and Dolphin: customizable, low cost, and easy to assemble tools for getting real time data transmission from the bottom of a cave, even underwater, to a webserver. Their use has been tested to monitor air temperature inside the Abisso Bonetti Cave (Classical Karst, Italy), proving for the first time that a cave in Gorizian Karst can systematically be colder than the outdoor temperature even in winter, recording an internal temperature even lower than 0°C. The Dolphin device can be …

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 …

Engagement Modeling And Inference For Risk-Aware Path Planning Under Adversarial Uncertainty, Grant Stagg

Theses and Dissertations

This dissertation develops methods for planning safe and efficient trajectories for autonomous vehicles operating in environments containing adversarial and environmental threats with uncertain parameters. The central objective is to quantify and control the risk of adverse events--such as interception or detection--when threat characteristics are imperfectly known. To address this challenge, probabilistic weapon engagement zone (PEZ) models are introduced to estimate the likelihood of violating adversarial engagement constraints under uncertainty in pursuer state and capabilities. Multiple computational strategies are developed for PEZ evaluation, including first-order sensitivity-based approximations, Monte Carlo estimation, and neural-network surrogate models. These approaches enable rapid engagement-probability assessment and …

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. …

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 …

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 …

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 …

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 …

Rgfc: Registry Grounded Function Calling With Stage-Decomposed Evaluation, Ritvik Garimella, Vedant Khandelwal, Anvi Kohli, Amit Sheth

Publications

Tool-calling evaluations often report whether the final call matches a reference answer, but this single outcome merges different failures: choosing a function outside the available registry, violating the selected schema, or filling arguments with values not supported by the user request. These failures matter more when models must choose from larger tool registries. We introduce RFCD, a registry-scaled function-calling benchmark built from BFCL, Glaive Function Calling v2, and Tool-Call-Data, with standardized JSON-schema registries ranging from 5 to 3,000 functions. We also introduce TAAG, a deterministic stage-decomposed evaluator for registry conformance, structural completeness, and argument grounding. Across six locally served sub-4B …

Analysis Of Approximations In Flash Thermal Diffusivity Measurements Using High‑Fidelity Simulations, Tage T. Burnett, Jakob G. Bates, Matthew R. Jones, Christopher R. Dillon, John Tencer

Faculty Publications

Thermal diffusivity is an important material property for understanding and characterizing transient behavior in many heat transfer applications. This study investigates the accuracy and approximations of inverse mathematical models for measuring thermal diffusivity of materials via the widely used Flash Method. High-fidelity simulations of the Flash Method in copper, silicon carbide, silicon, and glass were performed as numerical experiments and included physics such as in-depth absorption, radial conduction, and surface convection. Data from those numerical experiments were used to estimate material thermal diffusivity using seven traditional and new inverse models. Parker’s original model had relative errors 𝜖< 5% when the approximations it makes were enforced in numerical experiments. Newer models performed well even when experimental restrictions were relaxed. Models that include radial heat conduction were capable of accurately measuring thermal diffusivity (𝜖< 1%) when a Gaussian energy source was used. Models with radial conduction and in-depth material absorption of the laser source could calculate thermal diffusivity for semi-transparent materials such as silicon (𝜖< 1%) and even transparent materials like glass (𝜖< 10%). Convective losses from the material’s front surface had a negligible impact on measurements except for very low thermal diffusivity materials. Using temperatures from many locations of the test material’s surface increased resilience to noise, reducing the distribution of thermal diffusivity measurements by more than an order of magnitude. The models developed in this study could enable a more relaxed Flash Method experimental setup that maintains thermal diffusivity accuracy and extend the utility of the Flash Method to semitransparent materials.

Challenging Stem Learning Spaces: The Paradigm Of Contemplative Traditions As The Bedrock Of Creativity And Healing, Raaghav Pandya, Christopher Emdin

Journal of Contemplative and Holistic Education

As the post-pandemic classroom and pedagogy evolve to remedy oppressive norms, young people’s mental health and alienation has taken front stage (Rahmani & Zitouni, 2022). Traditional STEM learning spaces often teach inquiry as a linear, non-deviated approach to problems about self and nature (Hrisa & Psillos, 2022). Furthermore, because our classrooms often strip students and educators of their inherent creative abilities through constant assessments, improvement scales, and market-driven expectations, classrooms cease to become places of healing (Pandya, 2021). Eastern wisdom traditions and their associated philosophies provide a unique pedagogical lens that emphasizes a deep inquiry into self, empathy, and creativity …

Leveraging Information Theory And Ecological Network Analysis To Monitor Communication Networks In A Student Aerospace Team, Christine Sessions

Doctoral Dissertations and Master's Theses

Effective communication is a critical component of successful collaboration in group projects and team settings. However, systematically tracking and analyzing team communications can be challenging, especially in complex, multi-member teams such as those found in the aerospace industry. This paper explores an information-theoretic approach that leverages encoding techniques and graph theory to analyze communication networks within a university’s multi-year, student-led cubesat design project (Project COMET). By utilizing Shannon Entropy as a measure of information flow, encoding communication patterns, and analyzing Ecological Network Analysis parameters, this research aims to understand how an Embry-Riddle Aeronautical University student project team evolves over the …

Introduction To Computer-Aided Design Using Solidworks® : A Structured Approach To Parametric Modeling And Design Intent, Swapnil Moon

Open and Affordable Textbooks

This textbook introduces computer-aided design (CAD) using SOLIDWORKS® through a structured, design-centered approach that emphasizes parametric modeling and engineering reasoning. Rather than focusing solely on software commands, the material develops foundational skills in design intent, constraint-based modeling, and feature relationships to create robust, adaptable models.

The content is organized progressively, beginning with basic sketching and feature creation and advancing to complex part modeling, assemblies, motion studies, and engineering drawings. Each chapter builds upon prior concepts, reinforcing systematic modeling practices and promoting the development of system-level thinking required in real-world engineering design workflows.

Designed for undergraduate students with little or no …

Design Of Air-Entrained Concrete For Airport Pavements Through Local Aggregate Utilization: Performance Optimization And Economic Analysis, Li Wentao, Rizwan Qadir, Arslan Mushtaq, Hilal Khan, Kamran Jillani

Journal of Sustainable Construction Materials and Technologies

Airport pavement construction in developing countries faces critical challenges balancing international performance standards with economic constraints, while limited research exists on optimizing air-entrained concrete mixes using locally sourced materials for cost-effective solutions. This study investigated the development of economical air-entrained concrete mix designs for airport pavements utilizing Pakistani aggregates and systematic cement content optimization. Comprehensive experimental evaluation included material characterization through petrographic analysis, alkali-aggregate reactivity assessment via accelerated mortar bar testing, and mechanical property development across cement contents from 360-450 kg/m3. Air entrainment was achieved through controlled admixture dosing while maintaining target slump of 50mm. Results demonstrated that locally sourced …

Ai Institute Summer Camp Academic Preview Webinar: Curriculum, Research, And Outcomes, Paul English Applied Artificial Intelligence Institute

Paul English Applied Artificial Intelligence (AI) Institute Publications

This webinar presents an academic preview of the AI Institute Summer Camp hosted by the Paul English Applied Artificial Intelligence Institute at the University of Massachusetts Boston. The session introduces the program’s curriculum, structure, and student outcomes, providing insight into a hybrid learning model that combines faculty-led lectures, hands-on labs, and guided project development. The webinar highlights the program’s five-week structure, covering topics such as machine learning, neural networks, computer vision, speech and language processing, and generative AI. Participants learn how students engage in real-world AI applications, complete portfolio-ready projects, and develop research and presentation skills. This session is designed …

Erratum For "Soil Freezing Characteristic Surface For Partially Frozen Soils", Antai Dong, Xiong Zhang, Ming Xiao

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

The following corrections should be made to "Soil Freezing Characteristic Surface for Partially Frozen Soils" by Antai Dong, Xiong Zhang, and Ming Xiao, https://doi.org/10.1061/JGGEFK.GTENG -13924: In the third sentence of the Abstract, the value for suction when completely dried is incorrect. It should be 106 kPa. The label at the end of the suction axes in Figs. 1(a) and 2 is similarly inaccurate. Corrected versions of Figs. 1 and 2 are provided herein. To preserve the published version of record, these details have been corrected only in this erratum. (Figure Presented)

A Critical Review And Methodological Recommendations For Life Cycle Assessment Of Electrochemical Co₂ Mineralization, Dennis Dadzie, Kwame Awuah-Offei

Mining Engineering Faculty Research & Creative Works

Purpose: While researchers have relied on life cycle assessments (LCAs) to make claims about the environmental benefits of electrochemical CO₂ mineralization, no systematic review literature exists that synthesizes what we know about the LCA of electrochemical mineralization. This review aims to synthesize established knowledge on the LCAs of electrochemical CO₂ mineralization studies, identify research gaps and discuss challenges, and suggest guidelines for applying the ISO 14040/14044 LCA methodology in this sector. Methods: This paper undertook a comprehensive review of LCA studies on CO₂ mineralization with emphasis on electrochemical mineralization. We utilized relevant keywords based on the theme to search in …

Selective Extraction Of Nickel And Cobalt From Limonitic Laterite Via Optimized Sulfation Roasting–Water Leaching And Solvent Extraction, Maryam Osali, Farid Ahani, Mohammad Reza Aboutalebi, Mandana Adeli, Javad Moghaddam, Saeid Karimi, Janaka Jayamini Wijenayake, Lana Alagha

Mining Engineering Faculty Research & Creative Works

Limonitic laterites typically contain low Ni and Co contents and significant impurities, making the development of technical and economically feasible processes challenging. To address this challenge, this study investigates and evaluates an integrated hydrometallurgical process comprising sulfation roasting, water leaching, and solvent extraction (SX) for the selective recovery of Ni and Co from limonite-type laterite. Response Surface Methodology coupled with a Central Composite Design (RSM-CCD) was employed as a statistical experimental design tool to efficiently optimize the sulfation roasting conditions. Under the optimal sulfation roasting conditions (temperature 703 °C), selective leaching efficiencies of 87.2% for Ni and 96.6% for Co …

Transformation Efficiency And Gfp Expression In E. Coli, Jessica H. Hobbs

Honors Theses

Genetic transformation of bacteria is a foundational technique in molecular biology and biotechnology, enabling the introduction and expression of foreign genes for research, industrial, and educational applications. This thesis investigates the transformation efficiency and green fluorescent protein (GFP) expression in Escherichia coli using the pGLO plasmid system, with the primary objective of supporting the development of a graduate-level laboratory course focused on bioprocess engineering and molecular biotechnology. The pGLO plasmid contains a GFP reporter gene regulated by an arabinose-inducible promoter and an ampicillin resistance gene that allows for selective growth of transformed cells. Competent E. coli HB101 K-12 cells were …

Salt-Dependent Purification Of Green Fluorescent Protein Via Hydrophobic Interaction Chromatography, Katie L. Collins

Honors Theses

Green fluorescent protein, GFP, is a widely used fluorescent reporter, and its purification provides a clear model for studying downstream bioprocessing. This thesis investigates how binding-buffer salt strength affects GFP retention and elution during hydrophobic interaction chromatography, HIC, by comparing three conditions (1.0×, 0.8×, and 0.6×). GFP-expressing E. coli were lysed and clarified, and the lysate was purified on HIC columns; collected fractions were evaluated qualitatively under UV illumination to track fluorescence distribution. Results showed a salt-dependent trend in which higher salt improved retention and shifted fluorescence toward later elution fractions, while reduced salt weakened hydrophobic interactions and increased earlier …

Using Machine-Learning-Based Process Map To Guide Evaluation Of Inconel 625 Mechanical Properties In Laser Foil Printing, Yu Hsiang Wang, Sung Heng Wu, Hung Chu Chiang, Pen Ning Yu, Chia Hung Hung, Ming C. Leu

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Inconel 625 is widely studied in powder-based additive manufacturing, but its processing characteristics and mechanical performance in foil-feedstock laser foil printing (LFP) remain largely unexplored. In this study, a gradient boosting regression (GBR)-based process map was developed for LFP of Inconel 625 using 32 single-track experiments. The GBR model achieved R² values of 0.859 and 0.793 and mean absolute errors of 22.25 μm and 19.83 μm for melt-pool depth and width, respectively, outperforming second- and third-order polynomial regressions in capturing nonlinear melt-pool responses and distinguishing lack-of-fusion, conduction, and keyhole regimes. Three conduction-mode conditions with target depth-to-foil thickness ratios (D/T) …

Effect Of Environmental Conditions On Fracture Of Composite Materials And Thin Films, Victor Birman

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Environmental conditions, i.e., temperature and moisture, affect mechanical properties of materials, including composites. In this paper, we concentrate on one of the aspects of the effect of environment on fracture in a composite lamina. The paper demonstrates an analytical approach to account for the effect of the changes in environment on the strain energy release rate of composite materials and thin films. These analytically determined strain energy release rates should be compared to fracture toughness to predict the susceptibility of the material to fracture. Numerical examples are presented for several polymeric and metal matrix composites using available experimental data for …

Atom Probe Tomography Investigation Of Gas And Solid Fission Product Superlattice In Neutron Irradiated U-10 Wt.% Mo Fuel, Maalavan Arivu, Andrew Hoffman, Anish Ranjan, Assel Aitkaliyeva, Yaqiao Wu, Brandon Miller, Mukesh Bachhav, Dennis Keiser, Jian Gan, Haiming Wen

Materials Science and Engineering Faculty Research & Creative Works

Body-centered cubic structured γ U-Mo fuels have been developed for high performance research reactors. The formation of Xe gas bubble superlattice (GBS) in irradiated U-Mo fuels reduces the volumetric swelling of the fuels. In this study, atom probe tomography (APT) was used to measure the characteristics of the Xe GBS, including chemical composition, number density, and volume fraction of the gas bubbles, as well as the characteristics of the solid fission products, in neutron irradiated U-10 wt.% Mo fuel. It was found that in the bubbles (∼2 nm in diameter) that form the GBS are enriched with Xe with depletion …

Effect Of Composition On Grain-Boundary Chemistry And Fracture Behavior In High-Entropy Carbides, Caleb Schenck, Marium Mostafiz Mou, Elizabeth Pritchett, Fu Yun Tsai, Josephine Hartmann, Michael Lastovich, Sam Daigle, Kayla Yano, Matthew J. Olszta, Sanjit Bhowick, Elizabeth Kautz, Gregory E. Hilmas, William G. Fahrenholtz, Donald W. Brenner

Materials Science and Engineering Faculty Research & Creative Works

High-entropy carbides (HECs) are often treated as a single material class defined by configurational entropy; however, their properties are governed by composition-specific defects and grain-boundary chemistry. This study demonstrates that substituting a single element can qualitatively change grain-boundary structure and fracture behavior in HEC ceramics. Two HECs, (Cr,Hf,Ta,Ti,Zr)C (HEC-Cr) and (Hf,Ta,Ti,W,Zr)C (HEC-W), were examined via electron microscopy, atom probe tomography, and molecular dynamics simulations. Simulations predict preferential segregation of Cr, W, and Zr to grain boundaries. Experiments confirmed Cr enrichment at grain boundaries and the formation of W-rich nanograins along boundary networks. Mechanical testing revealed that these compositional differences translated …

Evaluating The Integration Of Bio-Based Waste Into Cement Production: A Pathway To Sustainable Building, Anja Terzić, Suzana Filipović, Adriana Peleš Tadić, Jelena Živojinović, Ivana N. Jelić, Nina Obradović, William G. Fahrenholtz

Materials Science and Engineering Faculty Research & Creative Works

Rapid urbanization has increased the demand for building materials, depleting natural resources used in cement production and prompting the use of alternative and waste materials. This research verifies that eggshell powder waste can fully replace limestone in clinker synthesis. Five clinkers were produced using eggshell powder, aluminum sources (bentonite, zeolite, fly ash, and kaolinitic–illitic clay), Fe-slag, and quartz sand, with mechanical preprocessing (10–30 min) before sintering at 1300 °C. Experimental tests assessed the effects of mix design and mechanical activation on clinkerization, phase formation, temperature, and mechanical properties. XRD, FTIR, and SEM/EDS confirmed consistent phase compositions and primary cement minerals. …

Computer Vision And Machine Learning Approaches For Defect Detection In 3d-Printed Cementitious Materials: A Systematic Review, Muhammad Ali Musarat, Ruben Paul Borg, Jingjie Wei, Carl James Debono, Kamal Khayat

Civil, Architectural and Environmental Engineering Faculty Research & Creative Works

3D printing is evolving at a fast pace in both the manufacturing and construction sectors. These advancements can greatly benefit these industries. However, the 3D printing of concrete structures presents some challenges due to defects in the 3D concrete printed elements. Hence, this study systematically reviews Artificial Intelligence (AI)-driven techniques, such as Computer Vision and Machine Learning, to identify surface defects that can occur in 3D-printed cementitious material structures. The adopted methodology was the PRISMA statement with the aim of reporting the systematic review and meta-analysis. Two well-known databases, Web of Science and Scopus, were utilised for data extraction of …