Digital Commons Network^™

Deep Learning Compilers, Raffi Khatchadourian

Open Educational Resources

These lecture slides introduce deep learning compilers for a graduate compiler-construction course (CSc 81010). Building on the classical compiler pipeline, they show how modern machine-learning systems compile tensor programs: static tensor and type analysis (illustrated by a WALA/Ariadne-based refactoring of imperative TensorFlow code to graph mode), MLIR-based end-to-end compilation with IREE, and the PyTorch 2.x stack—TorchDynamo graph capture, AOTAutograd, PrimTorch operator decomposition, and TorchInductor lowering to Triton (GPU) and C++/OpenMP (CPU). The slides are a self-contained HTML (W3C Slidy) deck with editable Pandoc Markdown source. Part of a two-session unit on advanced compiler topics; see also "LLMs in Compiler Construction."

Uncovering The Impact Of Youtube's Hidden Algorithm On Its Users, Oscar Perez

COD Library Student Research and Award Symposium

YouTube is a well-known platform that offers users endless hours of news, entertainment, and education. This research seeks to understand how the algorithm functions and uncover the effects of allowing a system to curate content for viewers. The research combines academic sources with fieldwork to understand the impact of YouTube's algorithm.

Faculty Sponsor:  Professor Jacqueline McGrath

Virtualizing Practical Science Education: A Sociological Analysis Of Undergraduate Teaching And Learning, Sina J. Fakoyede, Femi E. Babalola, Oluwatoyin T. Obateru, Oluwayemisi D. Akomolafe, Deborah O. Alabi, Stella K. Ekundayo

Higher Learning Research Communications

Objectives: The study aims to investigate the perspectives of university teachers and students on integrating practical science teaching with virtual learning in a multicultural and diverse society, specifically within the context of southwestern Nigeria.

Methods: A mixed-methods approach was employed, involving data collection from 100 university lecturers and 400 undergraduate students across 10 universities. Qualitative data were gathered through semi-structured interviews with lecturers and focus group discussions with students. Quantitative data were obtained via structured questionnaires, allowing for triangulation and comprehensive analysis.

Results: Findings revealed that certain lecturers showed preferential support influenced by students’ cultural backgrounds or academic behavior during …

The Role Of Gender And Salient Social Identities In Producing Vulnerability And Maladptation To Flooding In Koraso, Berekum, Ghana, Kingsley Damoah Oppong

Geography ETDs

This paper highlights how social identities like polygamy, illiteracy, and ethnicity hinder rural women farmers in Ghana from adapting to climate change. It advocates for an intersectional approach to address these challenges, moving beyond simplistic gender binaries. Using qualitative interviews (n=49) in a flood-prone village in Berekum, Ghana, the study reveals how these identities intersect with gender roles and colonial legacies, exacerbating vulnerability. It bridges Black feminist thought with climate change, an underexplored area, offering insights into climate change and environmental studies, as well as Black feminist scholarship. This research urges a reevaluation of how we understand climate change in …

The Influence Of Prosthetic Obturators On Quality Of Life In Individuals With Maxillectomy Defects, Minseok Kim

Oral Health

Abstract

Introduction: In recent years, there has been a growing focus on understanding the impact of oral cancer on patients' quality of life. Prosthetic rehabilitation techniques, such as maxillary obturators, often in conjunction with reconstructive surgery, have emerged as interventions to address the challenges posed by post-maxillectomy abnormalities.

Objective: This study aims to systematically review and evaluate the effectiveness of maxillofacial prosthetic rehabilitation using obturators in enhancing the quality of life of patients following maxillectomy.

Methodology: Systematic review of identified literature spanning the timeframe from 2000 to 2020 was used. The comprehensive search encompassed widely recognized databases including PubMed, …

Teacher Shortages In Arkansas Rural School Districts: Employed Teacher’S Perceptions Of The Impact On Their Effectiveness, Carloss Guess

ATU Theses and Dissertations 2021 - Present

ABSTRACT

TEACHER SHORTAGES IN ARKANSAS RURAL SCHOOL DISTRICTS: EMPLOYED TEACHERS’ PERCEPTIONS OF THE IMPACT

ON THEIR EFFECTIVENESS

Carloss Guess

Teacher shortages in rural school districts remain a persistent challenge that affects instructional quality, teacher workload, and professional sustainability. The purpose of this qualitative phenomenological study was to explore how teachers in rural Arkansas perceive the impact of staffing shortages on their instructional roles, workload, and professional well-being. Data were collected through semi-structured interviews with 10 K–12 teachers representing elementary, middle, and high schools and across varying career stages. Interview transcripts were analyzed using an inductive qualitative approach and the constant …

Debriefing In Emergency Departments And Intensive Care Units To Combat Compassion Fatigue, Madison N. Chiolino

ATU Theses and Dissertations 2021 - Present

Compassion fatigue can be associated with nurses working in increased stressful environments such as the Intensive Care Unit (ICU) and Emergency Room (ER).  There is a gap in healthcare facilities, where structured interventions like debriefing tools are not implemented to address compassion fatigue. The purpose of this study was to determine if implementing a debriefing tool in areas where nurses are placed in high stress scenarios such as the intensive care unit and emergency department can aid in combating compassion fatigue. A piloted quantitative pre-and post-survey intervention design was used. Data was collected using the ProQOL 5 and PEARLS debriefing …

Nutrilog: Design And Development Of A Full-Stack Web Application For Holistic Health Tracking, Jaromir J. Saloni

Honors Theses

NutriLog is a web-based fitness and nutrition tracking application designed to help users record, organize, and interpret personal health data in one centralized platform. Many existing applications focus primarily on either nutrition tracking or exercise performance, which can make it difficult for users to understand how food intake and physical activity interact. NutriLog addresses this gap by combining food logging, exercise logging, calorie adjustment, nutrition summaries, and historical tracking into a single dashboard-based interface.

The application was developed using React and TypeScript for the frontend and Supabase for authentication, database storage, and user-specific data management. Nutrition data is supported through …

Explicit Hydration Of The Beryllium Trifluoride Anion With One To Three Water Molecules: Bef3–(H2o)N=1–3, Kayleigh R. Autry, Gregory S. Tschumper

Chemistry Faculty Research & Creative Works

This work investigates the micro hydration of the beryllium trifluoride anion (BeF₃^–) with up to three water molecules (BeF₃^–(H₂O)_n where n = 1–3). Full geometry optimizations and harmonic vibrational frequencies were computed on various BeF₃^–(H₂O)_n stationary points using density functional theory methods (B3LYP-D3BJ, B3LYP, ωB97XD, and M06-2X) as well as the CCSD(T) and MP2 ab initio methods with a triple-ζ correlation-consistent basis set augmented with diffuse functions on all non-hydrogen atoms (haTZ). One BeF₃^–(H₂O)₁, five BeF₃^{– …}

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 …

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 …

Developing A Comprehensive Resource Guide For Caregivers Within The Area Agency On Aging, Aiden R. Murphy

Public Health Capstone Projects

This project developed a new universal caregiver resource guide for caregivers within the Area Agency on Aging, in order to improve resource navigation and workflow efficiency. Resources were collected, verified, and organized into a new, streamlined guide via the ARIA chatbot, covering multiple needs. Caregiver resources were collected and verified by the capstone student and mentor, Michael Kroeker, and organized into a centralized knowledge base within the ARIA chatbot. A mixed methods evaluation was conducted utilizing a 5-point Likert scale with three quantitative questions and one open-ended qualitative question. The data was given to the SeniorLine staff, who wanted to …

What History Shows: A Structural Account Of Fixed-Point Theory Formation, Griselda Poe

Publications and Research

Theory generation has long been subsumed under categories such as creativity, genius, and innovation. These categories do not distinguish assembly-based conceptual synthesis from fixed-point theory generation.

This paper makes that distinction explicit. The termination condition of assembly is external: data, citation, endorsement, usability. The termination condition of fixed-point theory generation is internal: consistency with internally held constraints, resolution of structural contradiction. The two operate under different processing conditions.

The historical record confirms this distinction. What Darwin, Einstein, Spinoza, and Kant produced was not assembly. Their processes involved unresolved branch retention and decomposition necessity, arriving at internally constrained fixed-point termination. Freud …

Genetic Analysis Of Triplicated Genes Affecting Sex-Specific Skeletal Deficits In Down Syndrome Model Mice, Kourtney Sloan, Kristina M. Piner, Pathum Randunu Nawarathna Kandedura Arachchige, Charles R. Goodlett, Yann Herault, Gayla R. Olbricht, Joseph M. Wallace, Randall J. Roper

Mathematics and Statistics Faculty Research & Creative Works

Down syndrome (DS) is caused by the triplication of human chromosome 21 (Hsa21), resulting in skeletal insufficiency (low bone mineral density) and altered bone development. DS mouse models recapitulate these deficits, including sexual dimorphism in long bone alterations. Historically, Ts65Dn mice provided much of the insight behind DS-related skeletal deficits with ∼100 trisomic orthologous genes, but there are concerns about the genetic fidelity in this model due to the included triplication of genes not homologous to Hsa21. A new DS model, Ts66Yah, subtracted the non-Hsa21 homologous trisomic genes from Ts65Dn but has not been evaluated for long bone deficits. Comparing …

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. …

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 …

Propasafe-Hybrid: A Text-Based Hybrid Propaganda Detection Tool, Thomas Kimmeth, Avijit Roy, Vivek Sharma

Publications and Research

Propagandistic content increasingly circulates through online news and social media, where readers often encounter it with limited scrutiny, highlighting the need for reliable and fine-grained detection. This paper introduces Propasafe-Hybrid, a sentence-level system that integrates a fine-tuned transformer classifier with LLM-based technique classification to identify, label, and explain specific propaganda strategies. The pipeline generates actionable outputs, including highlighted sentences, technique assignments, and concise rationales, so users can immediately understand why a sentence was flagged and how each label was determined. To control inference cost, Propasafe-Hybrid employs a cost-aware pre-filtering stage that forwards only high-likelihood sentences to LLMs, reducing token usage …

Radar Spoofing Attacks And Their Impact On Sensor Fusion-Based Perception For Autonomous Vehicles, Ahmad Mohammed Bara

Student Theses

Safe autonomous vehicle (AV) operation depends on robust perception of the surrounding environment. While multimodal sensing—integrating cameras, LiDAR, and radar—provides comprehensive environmental awareness, radar’s robustness under adverse conditions has made it a critical component of modern perception pipelines. However, the security vulnerabilities of radar within these fusion architectures remain largely unexplored. This work presents an end-to-end analysis of radar spoofing attacks on learning-based radar–camera fusion systems. Using a simulation framework grounded in reflect-array attack models, we inject physically plausible perturbations into radar measurements by altering depth by and velocity, while maintaining crossmodal consistency. Evaluation on the nuScenes dataset shows that …

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 …

Phenological Overlap In Obligate Plant-Pollinator Mutualism, Austin J. Carlson

2026 Spring Honors Capstones Projects

Plant-pollinator mutualisms require temporal overlap between flowering and pollinator activity, so climate-driven timing shifts can weaken the interaction and, in severe cases, destabilize the system. This work investigates how reduced overlap affects persistence in an obligate plant-pollinator pair using a coupled differential equation model in which a phenological overlap factor scales the saturating mutualistic benefit. Simplification with a constant overlap enables closed-form equilibrium and stability analysis, revealing that below a critical overlap threshold, coexistence is no longer maintained. Rescaling reduces the parameter space from ten quantities to seven dimensionless groups, and sensitivity analysis identifies the degree of species dependence and …

Should I Stay Or Should I Go?: Evaluating The Role Of Climate And Weather Stressors On Moving Decisions In Southeast Florida, Arielle Perry

Electronic Theses and Dissertations 2020 - Present

As climate and weather hazards intensify, Southeast Florida communities face mounting pressures that increasingly influence patterns of migration and immobility. This research examines evidence of climate migration in high flood-risk neighborhoods in Fort Lauderdale by exploring why some populations choose to stay, while others leave, in the context of a changing climate. Using focus group discussions, I investigate how climate and non-climate related factors shape mobility outcomes among residents in the city. Migration outcomes were primarily influenced by negative climate and weather hazard experiences, discontent with existing public in-situ adaptations, and non-climate disamenities, which eroded participants’ sense of place. Voluntary …

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 …

Propasafe-Hybrid: A Text-Based Hybrid Propaganda Detection Tool (Ila 2026 Presentation), Thomas Kimmeth, Avijit Roy, Vivek Sharma

Publications and Research

This presentation introduces Propasafe-Hybrid, a hybrid system for sentence-level propaganda detection that combines offline transformer-based classification with selective large language model (LLM) explainability. The system employs a two-stage pipeline in which a local BERT-based classifier evaluates all input text and filters non-propagandistic content, while only high-confidence candidates are forwarded to an LLM for rhetorical technique labeling and explanation. This design enables cost-aware, privacy-conscious, and scalable analysis by reducing unnecessary reliance on external models.

Propasafe-Hybrid identifies propagandistic techniques such as loaded language, obfuscation, and appeal to fear, and generates concise natural language rationales that make these techniques interpretable to users. By …

Sequential Robustness In Adversarial Reinforcement Learning, Roman Lok-Ming Belaire

Dissertations and Theses Collection (Open Access)

My goal is to build autonomous systems that expand the reach of human capability in challenging domains such as undersea and space exploration, disaster response, and large-scale infrastructure. In everyday settings, these systems will increasingly appear in safety-critical applications such as autonomous driving, robotics, and industrial manufacturing. A central requirement for these systems is the ability to operate reliably under uncertainty, particularly when the environment behaves in unanticipated ways.

The robust handling of unforeseen environment dynamics is therefore a technical cornerstone of autonomous decision-making; Adversarial attacks provide a useful and principled lens through which to study this problem. Adversarial \textit{robustness}, …

Perspectives On Interpretability For Neural Text Representations, Jia Peng Lim

Dissertations and Theses Collection (Open Access)

In this dissertation, we investigate interpretability in the three elements of learning neural text representations: inputs, passed into models, to produce probabilistic outputs. We emphasise perspectives as we present alternative novel methods to mine and organise meaning in this work.

Models. We initiate our investigation by examining Neural Topic Models (NTM), proposing an alternate angle of interpreting its word-topic distribution, producing better topic representations for interpretation. Our method maps the problem of finding these better interpretations to classical NP-hard graph problems, enabling examination of topic distributions in a composite manner. Next, we apply our previous findings to extract interpretations from …

Software Integration In Personal Healthcare Devices And The Patient User Experience, Yassine Chahid, Patrick Slattery

Publications and Research

This study examines the current landscape and future direction of medical device hardware and software integration, focusing on how each contributes to patient care. It begins by analyzing hardware focused medical devices, such as implantable tools patients may rely on to assist with their condition, alongside diagnostic and monitoring equipment used to treat conditions in a variety of medical areas (e.g. cardiovascular conditions). It then evaluates how software is currently integrated through embedded systems, data processing, and user interfaces that support real time monitoring and clinical decision making, and how this impacts quality of care for the patient whilst minimizing …

Course Insight Portfolio: Math 1080, A Gentle Introduction To Infinite Series, Igor Luis Aureliano, Leyanis Falcon Hernandez, Ross George, Fnu Monika

Publications

This lesson aims to introduce the concept of an infinite series through geometric representations and partial sums to help students develop an intuitive understanding of convergence. A common misconception students may have when first encountering infinite series is the belief that “a sum of infinitely many things must be infinite”. Through the study of a convergent geometric series, students will investigate how the limit of partial sums can produce a finite value, thereby addressing this misconception and developing a more accurate understanding of infinite series.

Multi-Population Sufficient Dimension Reduction, Xuerong Meggie Wen, Yuexiao Dong, Li Xing Zhu

Mathematics and Statistics Faculty Research & Creative Works

A novel dimension-reduction method is introduced for multi-population data. The approach conducts a joint analysis that exploits information shared across populations while accommodating population-specific effects. Unlike partial dimension reduction methods, which identify related directions across all populations, or conditional analyses conducted independently within each population, the proposed two-step procedure leverages cross-population information to enhance estimation accuracy. The methodology is demonstrated through simulations and two real-data applications.

A Low-Rank Solver For The Stokes–Darcy Model With Random Hydraulic Conductivity And Beavers–Joseph Condition, Yujun Zhu, Yulan Ning, Zhipeng Yang, Xiaoming He, Ju Ming

Mathematics and Statistics Faculty Research & Creative Works

This paper proposes, analyzes, and demonstrates an efficient low-rank solver for the stochastic Stokes-Darcy interface model with a random hydraulic conductivity both in the porous media domain and on the interface. We consider three interface conditions with randomness, including the Beavers–Joseph interface condition with the random hydraulic conductivity, on the interface between the free flow and the porous media flow. Our solver employs a novel generalized low-rank approximation of the large-scale stiffness matrices, which can significantly cut down the computational costs and memory requirements associated with matrix inversion without losing accuracy. Therefore, by adopting a suitable data compression ratio, the …