Schedagent: Dynamic Cpu Scheduler Selection Via Reward-Driven Behavioral Cloning,
2026
Santa Clara University
Schedagent: Dynamic Cpu Scheduler Selection Via Reward-Driven Behavioral Cloning, Rawan Bekheet
Computer Science and Engineering Master's Theses
Modern Linux systems ship with a single default CPU scheduler that remains active regardless of how workloads change over time. Although the sched ext framework permits loading alternative scheduling policies at runtime, existing approaches to selecting among them rely on manual configuration rather than automatic adaptation to workload characteristics. We present an automated scheduler selection system that monitors workload behavior and dynamically switches between scheduling policies. Using discrete-event simulations of four Linux scheduling policies, we formulate scheduler selection as a sequential decision problem with a composite reward signal covering latency, fairness, throughput, and CPU utilization, and apply a two-phase behavioral …
Reasoning In The Network: Large Language Models For Congestion Control And Agent-Defined Networking,
2026
Santa Clara University
Reasoning In The Network: Large Language Models For Congestion Control And Agent-Defined Networking, Shanaya Anna Varkey
Computer Science and Engineering Master's Theses
Despite decades of progress in network protocols and control algorithms, many network-control mechanisms continue to rely on fixed heuristics, manually written rules, or static controller logic. This thesis explores the use of large language models as reasoning-based decision-making components within networked systems.
The thesis presents two case studies. The first, RLVR-CC, investigates whether a large language model can be trained to make congestion-control decisions using reinforcement learning with verifiable rewards. In this system, the model observes network state, reasons about current conditions, and selects a rate-control action. The second, Agent-Defined Networking, studies whether a large language model can participate in …
Fisheye Camera Object Detection For Traffic Surveillance,
2026
Santa Clara University
Fisheye Camera Object Detection For Traffic Surveillance, Hugo Yang, Robert Luo
Computer Science and Engineering Senior Theses
Effective traffic management is hampered by the physical limitations of traditional pinhole cameras, whose narrow fields of view create blind spots that require costly multi-camera infrastructure to overcome. Fisheye cameras offer a wide-angle alternative capable of single-camera intersection coverage, but the radial distortion inherent in their optics renders standard object detection algorithms unreliable, limiting their practical deployment in traffic surveillance.
This thesis investigates specialized object detection pipelines for fisheye traffic imagery by reproducing and building upon two top-ranked submissions from the 2025 AI City Challenge Track 4: the VNPT and SKKU-AutoLab pipelines. Both were successfully reconstructed outside their original containerized …
Ml Models For Child-Parent Speech Diarization,
2026
Santa Clara University
Ml Models For Child-Parent Speech Diarization, Kenneth Kang
Computer Science and Engineering Senior Theses
This senior design thesis presents a machine learning research pipeline for child-parent and child-directed speech diarization. Speech diarization is the task of determining who spoke and when in an audio recording. Although this problem is well studied in adult meeting, broadcast, and conversational speech, child-parent audio is a more uneven setting. Children may speak in short turns, change pitch quickly, vocalize without producing clear words, interrupt adults, overlap with adult speech, cry, laugh, or code switch. These behaviors are normal in real family interaction, but they can confuse diarization systems that were mostly designed and evaluated on adult speech.
The …
Trends In Non-Profit Cybersecurity: Analyzing Three Years Of Incident Data From The Npcir,
2026
Kean University
Trends In Non-Profit Cybersecurity: Analyzing Three Years Of Incident Data From The Npcir, Stanley Mierzwa, Joanna Paliszkiewicz, Edyta Skarzyńska
Center for Cybersecurity
This study analyzes cyberattack trends targeting non-profit organizations using longitudinal data collected over a three-year period within the Non-Profit Cybersecurity Incident Repository (NPCIR). Developed through a National Security Agency Center of Academic Excellence in Cyber Defense (NSA CAE-CD) designated center, the NPCIR applies an open-source intelligence (OSINT) methodology to systematically document cybersecurity incidents affecting the global non-profit sector. This study examines attack types, threat actor characteristics, sectoral distribution, and cybersecurity impacts using the Confidentiality–Integrity–Availability (CIA) triad framework. The results indicate that availability-related incidents, particularly ransomware and distributed denial-of-service (DDoS) attacks, constitute the most prevalent threats, while confidentiality breaches remain highly …
Implementation Of A Mixed Precision Iterative Solver On An Amd Apu,
2026
Santa Clara University
Implementation Of A Mixed Precision Iterative Solver On An Amd Apu, Saeyeon Kim, Henrik Evers
Computer Science and Engineering Senior Theses
Solving systems of linear equations is a core operation in high-performance computing and many scientific and engineering applications. One of the most widely used direct methods for solving such systems is LU factorization. Mixed-precision methods accelerate these solvers by using low-precision LU factorization with iterative refinement, improving performance and energy efficiency while preserving high numerical accuracy. AMD Accelerated Processing Units (APUs), which integrate CPU and NPU resources, provide an opportunity to explore this approach on emerging heterogeneous architectures. However, effective NPU utilization remains challenging due to workload partitioning, buffer management, data-movement overhead, and software tooling limitations.
This project implements a …
Sleepfocus – The Attributes And Application,
2026
Santa Clara University
Sleepfocus – The Attributes And Application, Austin Kim, Erik Keifer, Isaac Amedie
Computer Science and Engineering Senior Theses
Insufficient sleep is a widespread public health concern, yet many consumer sleep tools still emphasize retrospective dashboards over personalized, actionable guidance. Platforms such as Apple Health, Fitbit, Whoop, and Oura collect detailed biometric and sleep data, but users are often left to interpret trends and decide what to change on their own.
SleepFocus was built to address that gap by turning wearable sleep data into clearer feedback, personalized recommendations, and healthier sleep routines. SleepFocus is a native iOS application that integrates with Apple HealthKit to collect sleep-stage data and biometric streams such as heart rate, heart rate variability, respiratory rate, …
Broncosgo: Driving Student Event Participation Via Human-Ai Collaborative Event Curation,
2026
Santa Clara University
Broncosgo: Driving Student Event Participation Via Human-Ai Collaborative Event Curation, Katherine Carter, Ethan Sychangco
Computer Science and Engineering Senior Theses
College campuses rely heavily on email communication for event advertisement. However, due to the sheer number of emails any student may receive, the individual effectiveness of each advertisement decreases. A better alternative for event promotion was needed. How could we introduce students to events they would not usually find on their own, without continuing to fill up their email inbox? And how would information on all of those events be collected and maintained without requiring organizations to jump through extra hoops? Our project, BroncosGo, solves this issue by maintaining a database of campus events which is populated with information provided …
Club Finance Management Application,
2026
Santa Clara University
Club Finance Management Application, India Bell, Lydia Martin, Sola Kawahara, Zachariah Wang
Computer Science and Engineering Senior Theses
There are over 160 Registered Student Organizations (RSOs) at SCU as of 2023 [6]. There is currently no centralized system that RSO treasurers use to track and manage club finances. As a result, many organizations rely on fragmented methods such as spreadsheets, shared documents, email chains, and manual record keeping to manage budgets, reimbursements, and financial reports. These disconnected systems often lead to inconsistent organization, communication difficulties, and challenges during leadership transitions between club officers. This project proposes the development of a web-based Club Finance Management Application, Kaikei, designed specifically for Santa Clara University student organizations. The application centralizes financial …
Stomp (The Student Organization Management Portal),
2026
Santa Clara University
Stomp (The Student Organization Management Portal), Lindsey Leong, Madeline Follosco, Noelle Evanich, Irene Chang
Computer Science and Engineering Senior Theses
At Santa Clara University, the Center for Student Involvement (CSI) leads to support hundreds of student-led organizations with different audiences and ambitions, but all aim to bring students together nonetheless. However, such development regarding student organization management proves to be much harder when administrative processes are decentralized and cumbersome, often involving numerous layers of manual work and departmental bottlenecks. Restructuring and optimizing administrative workflows would entail more energy towards the growth of student life at Santa Clara University.
The Student Organization Management Portal, or StOMP, is a web application that aims to centralize and optimize student organization-related processes, as well …
Real-Time Corridor Counting,
2026
Santa Clara University
Real-Time Corridor Counting, Erick Sun, Jacob Lin, Jayden Malhotra, Joseph Hissen
Computer Science and Engineering Senior Theses
Identifying traffic trends is a critical step in urban planning and design for the purpose of creating safer and more efficient roads. One such problem in the field of traffic data is corridor counting, which is the process of counting the unique number of vehicles that pass through a set of predefined intersections in a given time. In this paper, we develop an automated solution to perform corridor counting in real-time using camera footage and computer vision. We build upon the architecture of a previous Senior Design project, replacing and refining key components and architectural choices to improve accuracy and …
Bilingual Math For Kindergartners (Biki),
2026
Santa Clara University
Bilingual Math For Kindergartners (Biki), Anna Aldrin, Caroline Tapia, Lillian Le
Computer Science and Engineering Senior Theses
For many children from bilingual households, kindergarten represents a critical, learning benchmark where the introduction of fundamental math concepts coincides with their first significant exposure to the English language. Traditional educational methods often fail to support English language learners, leading to a disconnect between their understanding of math in the home and its application in the classroom. This linguistic barrier frequently results in reduced engagement, diminished confidence, and an unstable educational foundation that can discourage students from pursuing STEM careers later in life. While existing platforms like Khan Academy and Duolingo address either language acquisition or mathematical proficiency independently, they …
Bridgeide,
2026
Santa Clara University
Bridgeide, Maya Srimal, Jeshwin Prince, Arnav Gupta, Will Zumbolo
Computer Science and Engineering Senior Theses
Anyone who has done a group project knows the pattern: the first meeting burns an hour on logistics—which document to use, who has access, why the formatting broke on one laptop—before real work begins. In computer science courses that gap is worse. Students must install the right compiler, runtime, and libraries on their own machines; a four-person team on four different laptops can lose the first week to setup alone. Instructors who want to review submissions often download every zip from the learning management system and run each one locally. Existing tools solve pieces of this puzzle—real-time document editing, browser-based …
Wearable Hazard Detection System For The Visually Impaired,
2026
Santa Clara University
Wearable Hazard Detection System For The Visually Impaired, Nolan Daly, Sergio Diaz, Brandon Ng
Computer Science and Engineering Senior Theses
This project presents a wearable assistive system designed to help blind or visually impaired people navigate their surroundings more safely. The system uses a Raspberry Pi 5 connected to Camera Module 3 (NoIR Wide) sensors to capture a wide field of view. Real-time object detection is performed using a lightweight YOLOv8 model, and a redundancy-based merging algorithm combines detections across cameras to improve reliability. By requiring agreement between multiple cameras, the system reduces false positives and increases confidence in identifying obstacles.
The device is designed to operate in real time and provide reliable feedback about nearby hazards, helping users make …
Iajes Website Redesign,
2026
Santa Clara University
Iajes Website Redesign, Justin Fan, Nicolas Gibson, Isabelle Hu, Anisha Malani
Computer Science and Engineering Senior Theses
The International Association of Jesuit Engineering and Science Schools (IAJES) connects more than sixty Jesuit institutions worldwide to promote collaboration and shared learning in STEM research. Santa Clara University is one of more than sixty member universities whose faculty and staff participate in conferences and task forces to address priority issues identified by the Society of Jesus. IAJES’ existing website, built on a static no-code platform, limited the organization’s ability to manage content, support member interaction, and scale with its growing global network. Users faced unclear navigation options, a basic design, and no effective tools for managing roles, resources, or …
Maya Roots,
2026
Santa Clara University
Maya Roots, Erin Schmidt, Megu Kanzawa
Computer Science and Engineering Senior Theses
This project focused on the continued development of Maya Roots, a mobile and web-based platform designed for farmers in Tahcabo: a rural agricultural community located in Yucatán, Mexico. Yucatán faces unique agricultural challenges due to its karst limestone terrain and highly variable land conditions that can significantly impact farming outcomes. At the same time, traditional agricultural knowledge such as Milpa farming practices is increasingly at risk of being lost across generations. These environmental and cultural challenges highlighted the need for a portable, accessible system that could preserve agricultural knowledge, improve access to geospatial information, and strengthen communication between farmers and …
6tisch Based Sensing Network For Smart Agriculture,
2026
Santa Clara University
6tisch Based Sensing Network For Smart Agriculture, Riley Heike, Griffin Jones, Justin Odo, Jalen Paige, Rosalie Wessels
Computer Science and Engineering Senior Theses
This project investigates 6TiSCH (IPv6 over Time-Slotted Channel Hopping), a relatively recent IETF networking standard introduced in 2013 that combines deterministic TSCH scheduling, 6LoWPAN header compression, and RPL mesh routing to enable low-power, reliable, multi-hop wireless communication for IoT deployments. Despite its strong theoretical properties, 6TiSCH remains underexplored in practice, and real-world questions around configuration, scalability, power behavior, and end-to-end integration are not well documented. Our primary goal was to build and operate a working 6TiSCH network, characterize its performance through iterative testing, and understand what it takes to go from raw packet delivery to a complete data pipeline.
To …
Hyperdimensional Computing For Edge And Mobile Devices,
2026
University of Louisiana at Lafayette
Hyperdimensional Computing For Edge And Mobile Devices, Colin Eddy Dupuis
Masters Theses
This thesis presents a set of four Hyperdimensional Computing (HDC) frameworks and their Android application implementations to evaluate efficiency and feasibility on resource-constrained devices. These proposed methods target a range of application domains, including wearable health monitoring, mobile malware detection, and activity recognition utilizing both computer vision and multiple sensor streams as input. The proposed frameworks utilize HDC’s simple, lightweight arithmetic operations to convert raw data into high-dimensional representations for use in both binary and multi-class classification schemes. Each method utilizes unique encoding techniques tailored for each use case, demonstrating the flexible nature and specialization HDC offers as an emerging …
Jsd: Novel Methodology For Synthetic Data Evaluation,
2026
Santa Clara University
Jsd: Novel Methodology For Synthetic Data Evaluation, Jeffrey Lane, Scott Wang, Vincent Chang, Bojun Zhang
Computer Science and Engineering Senior Theses
The proliferation of sensitive Personally Identifiable Information (PII) on dark web marketplaces has created an urgent need for robust data protection systems, especially for vulnerable populations such as minors. Traditional PII redaction often fails to identify implicit privacy risks—such as author gender indicators or non-fictional child-related context—hidden within large-scale e-commerce datasets. This paper presents JSD, a dual-stage framework for the detection and protection of sensitive text data. The Detection phase utilizes Transformer and CNN-based architectures and Human-in-the-Loop AI to surpass the "semantic ceiling" of traditional NER approaches, enabling context-aware identification of implicit PII. The Protection phase introduces GASE (Genetic Algorithm …
Hemlock,
2026
Santa Clara University
Hemlock, Ephraim Esson, Ambrose Vellequette, Geno Meschi
Computer Science and Engineering Senior Theses
Hemlock is a tool designed to protect musicians from having their work used to train generative AI models without their consent. It works by adding carefully crafted inaudible noise to audio files that disrupts the ability of AI models to learn from them — a technique known as adversarial perturbation. Our system targets three different types of AI model simultaneously: a Music Information Retrieval (MIR) classifier, a sequential audio generation model (Mel-LSTM), and Meta’s AudioCraft, a transformer-based music generator. Testing in twenty songs showed an average 15% reduction in the MIR model’s classification confidence, a 59% increase in Mel- LSTM …
