Computer Engineering Commons^™

Examining Iot-Enhanced For Current Developments In Face Image Authentication (Fia) Methods And Their Drawbacks, Marwa Jamal Hadi, Emaan Ouudha Oraby

Al-Esraa University College Journal for Engineering Sciences

The quick development of IoT and facial image manipulation (FIM) algorithms, as well as the growth of their user-friendly applications, highlight the pressing need for manipulation detection methods. These techniques need to demonstrate how face photos have been altered and validate their legitimacy. The scientific community has recently taken notice of the phrase “DeepFakes” and methods for detecting them. Take note of the latest methods for identifying watermark-based face image modification as well. The important thing to remember is that every one of these methods has its own set of drawbacks. This study provides a brief introduction to face image …

Foundations For Multi-Bit-Per-Cell Phase Change Memory Modeling Gst Crossbar Arrays, Sashah Wilson-Thompson

Holster Scholar Projects

This project builds a simulation foundation for selective cell heating in a phase-change memory (PCM) crossbar using Ge2Sb2Te5 (GST) as the active material. Using COMSOL Multiphysics® a 3D modeling software, couples Electric Currents, Electric Circuits, Heat Transfer in Solids, and Electromagnetic Heating for the simulation. A parameterized Tungsten (W)/GST-Amorphous/GST-Crystalline(phases) /W embedded in Silica Dioxide (SiO2) and surrounded in Silica Nitride (Si3N4) is validated at the single-cell level and scaled to small GST crossbars A terminal voltage (V_active/V_inactive, or 0 V if unselected) is applied through MOSFET and diode selector elements at the ends of each word line and bit line. …

Freer Arrows And Why You Need Them In Haskell, Grant Vandomelen, Gan Shen, Lindsey Kupur, Yao Li

Computer Science Faculty Publications and Presentations

Freer monads are a useful structure commonly used in various domains due to their expressiveness. However, a known issue with freer monads is that they are not amenable to static analysis. This paper explores freer arrows, a relatively expressive structure that is amenable to static analysis. We propose several variants of freer arrows. We conduct a case study on choreographic programming to demonstrate the usefulness of freer arrows in Haskell.

Ai-Powered Accessibility Tracker For Inclusive Public Spaces, Yenny Ma, Kevin Beltran

College of Engineering Summer Undergraduate Research Program

This research project will develop and evaluate a smartphone-based, AI-powered system to crowdsource and analyze accessibility features and barriers in public spaces. Using computer vision and geospatial mapping, the system will identify and categorize issues such as uneven sidewalks, missing or inadequate curb ramps, damaged tactile paving, obstructive overhangs, and the absence of visual or auditory wayfinding cues. The overarching goal is to generate a dynamic, real-time accessibility map that empowers individuals with diverse mobility, sensory, and cognitive needs to navigate public spaces more safely and confidently. The project will integrate technologies and methods from applied machine learning, mobile computer …

Advancing Mobileclip Through Hybrid Quantization: A Cpu-Focused Approach, Atiqur Rahman

2025 Fall Honors Capstones Projects - Archive

MobileCLIP is a compact model that connects images and text, enabling it to perform tasks like image identification and question answering without needing to be retrained for each new task. Although it’s designed to be lightweight, it still runs slowly on regular computers without a powerful graphics card (GPU). This research focuses on making MobileCLIP run faster and smaller by using post-training quantization, which reduces the model’s precision after training without hurting performance. We combined several strategies: analyzing which parts of the model are more sensitive to changes, applying targeted adjustments to its structure, and running everything using CPU-only tools. …

Improved Context For Llm Queries On Knowledge Graphs Using The Model Context Protocol, Talha Tahmid

2025 Fall Honors Capstones Projects - Archive

Large Language Models (LLMs) struggle on factual, relation-heavy questions without structured external knowledge. This thesis implements a standards-based pipeline that connects LLMs to Resource Description Framework (RDF) knowledge graphs through the Model Context Protocol (MCP). The system comprises an MCP tool that executes SPARQL against approved endpoints, an Natural Language (NL) to SPARQL step in which the LLM (ChatGPT) generates the SPARQL query using prompt-based templates, followed by a generation stage conditioned on the retrieved graph facts. Final experiments focus on the Rhea knowledge graph. We evaluated the same base model with and without MCP on a 50-question benchmark spanning …

Learn To Fly: Enabling Deep Learning Based Perception And Control In Aerial Robotics, Krishna Muvva

School of Computing: Dissertations, Theses, and Student Research

Uncrewed Aerial Vehicles (UAVs) are increasingly deployed in dynamic, GPS degraded, and cluttered environments, yet their autonomy remains fundamentally constrained by limitations in onboard perception and real-time control. This dissertation addresses these challenges by proposing a unified framework that co-designs deep learning-based perception and model-based control, organized around three core thrusts: Learn to Track, Learn to Localize, and Learn to Evade.

Learn to Track develops dynamic and adaptive perception control mechanisms that optimize CNN inference for target tracking. A control-aware CNN framework dynamically adjusts inference frequency based on UAV motion, reducing latency while maintaining visual lock. An adaptive CNN with …

Csc36000 - Modern Distributed Computing Assignment, Saptarashmi Bandyopadhyay

Open Educational Resources

This assignment covers standard performance metrics for Distributed Systems and the basics of Multiprocessing for CSC36000 - Modern Distributed Computing at the City College of New York CUNY. It is an interactive coding assignment intended to be executed in a Python notebook.

Deep-Learning Based Microstructure Reconstruction And Generation, Cameron J. Maloney, Lucas Taliaferro, Nina St. John

College of Engineering Summer Undergraduate Research Program

Microscopic imaging is essential to characterize multi-scale material behavior and understanding structure-property relationships. Recently our group developed a deep learning approach based on a Generative Adversarial Network (GAN) to reconstruct and artificially generate microstructures of strain-sensing nanomaterial networks based on microscope imagery. In this SURP project we would like to evaluate an alternative approach called diffusion to see if we can improve the quality of our results. Furthermore, we aim to test our approaches on a wider variety of materials, which will have different microstructures, to evaluate how versatile our models are.

Behind The Prompt: The Environmental Impact Of Llm Inference, Lucy Hegenderfer, Isaac Huang

College of Engineering Summer Undergraduate Research Program

As the size and demand for large language models (LLMs) increase, the environmental impact of computational inference often exceeds training; yet industry lacks a standardized method of calculating this expanding environmental footprint. Complexity arises with task-specific computational demands, infrastructure overhead, and various GPU architectures, making cross-model assessments burdensome. Combining environmental engineering and computer science principles by validating Jegham et al.’s meta-model, we predict the carbon emissions and water consumption during inference, providing metrics to raise user awareness of AI’s growing environmental footprint. Additional work supports integration into a multi-agent conversational system that encourages responsible scheduling and prompting, guiding the user …

Mixed Reality In Human–Robot Interaction For Collaborative Applications, Evan Reid, Caitlin Osorio

College of Engineering Summer Undergraduate Research Program

This project explores the use of Extended Reality (XR) technologies to enhance human- robot interaction in industrial contexts. Building upon prior research in affective and cognitive state recognition during human-cobot collaboration, this study investigates how natural hand and head gestures, captured through Meta Quest passthrough mode, can be used to communicate human intent to a Universal Robotics e-Series collaborative robot. The XR system provides users with an immersive, real-world visual interface while tracking motion and position in real time. The captured gestures are interpreted through a custom software pipeline that integrates machine learning models and rule-based logic to trigger adaptive …

Constructing A High-Performance Iot Pipeline For Smart Manufacturing Environments, Seth Langel

College of Engineering Summer Undergraduate Research Program

The Fourth Industrial Revolution, or Industry 4.0, integrates a range of advanced technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Cloud Computing, and Data Analytics to improve the efficiency, productivity, scalability, and security of modern manufacturing systems. Smart manufacturing leverages these technologies across various domains to enhance data-driven decision-making and quality control in production processes. In a smart manufacturing environment, heterogeneous IoT sensors interact with each other and control systems to automate real-time monitoring, analysis, and decision-making. This integration enables manufacturers to optimize production, quickly detect and address anomalies, reduce environmental impact, and adapt rapidly to changing …

Ai-Driven Embedded Camera System For Real-Time Traffic Anomaly Detection, Isaac Pruett

College of Engineering Summer Undergraduate Research Program

In this project, we will collaborate with Caltrans District 5 (covering San Luis Obispo County and surrounding regions) to develop a small, battery-powered, camera-based embedded system utilizing an NVIDIA Jetson board and neural networks to detect highway traffic anomalies. The device will analyze real-time traffic flow patterns and send alerts regarding detected anomalies. Unlike the stationary commercial camera systems currently in use, the proposed system offers increased mobility, affordability, and will give Caltrans engineers improved access over system outputs.

Ai Agents For Search And Rescue (Ai4sar), Nathan Huang, Lakshana Viswa

College of Engineering Summer Undergraduate Research Program

The goal of this summer research activity is to expand the capabilities of a system developed in the larger AI in Search and Rescue project. This project supports volunteer organizations participating in the search for missing persons by providing a basic framework for the collection and organization of relevant information, augmented with specific components that utilize a variety of AI methods. The focus of the summer research will be on the development of agent components for selected roles and tasks in a search and rescue mission. The agents utilize generative AI methods such as Large Language Models (LLMs) to provide …

How Does User Control Reduce Irritation Of Mid-Roll Ads, Elijah Villanueva

College of Engineering Summer Undergraduate Research Program

Large video platforms like YouTube and Twitch rely extensively on advertising for revenue. Often, they deploy mid-roll advertising: ads that play in the middle of video content, interrupting it. Such interruptions can irritate consumers significantly. This project primarily involves conducting user testing of an already-developed YouTube browser extension that that gives users some control over when mid-roll ads play. We hope to ascertain how effectively the design mitigates user irritation from mid-roll ads. Tasks will involve recruiting people into a laboratory setting where they will use the browser extension, interviewing them about their experience, and manually extracting themes from the …

Approximating The Maximum Weighted Independent Set Problem Empirically, Sue Sue

College of Engineering Summer Undergraduate Research Program

In this project we investigate approximation algorithms for the maximum weighted independent set (MWIS) problem in random graphs that approximate real-world graphs, such as social networks. The problem involves finding a large collection of nodes in a network (vertices in a graph) such that no two nodes are directly connected to one another. Applications of the MWIS problem are broad and include clique-finding algorithms as well as the use of large independent sets in distributed algorithms. We build on prior work by the mentor with a SURP 2024 and senior project, in which preliminary findings suggested that a standard greedy …

Building Pathways To Computer Science Careers For Latinx Students Through Multilingual Collaborative Block-Based Programming, Valerie Ponce, Priscilla Garcia

College of Engineering Summer Undergraduate Research Program

The underrepresentation of Latinx students in computer science highlights the need for innovative and inclusive educational approaches. This project addresses challenges such as limited access to educational resources and the demand for multilingual learning tools by developing a co-located, collaborative, game-based programming environment. Designed for use on phones, tablets, and laptops, this tool supports English, Spanish, and Mixtec, facilitating broader engagement. By promoting peer collaboration and interactive learning, our approach challenges traditional notions of solitary programming and reinforces the idea that expertise is shared, fostering an inclusive and equitable learning environment.

Mastering Undergraduate Algorithms: Improving Problem-Solving Skills And Fluency Through Scaffolding Learning Modules, Anissa Soungpanya

College of Engineering Summer Undergraduate Research Program

The primary objective of the undergraduate algorithms course is to equip students with the ability to design and analyze algorithms, prove theorems about computation, and effectively communicate these algorithms and proofs to a human audience. In addition, the course aims to help students foster their fluency in the process of formulating and solving computational problems. Scaffolding exercises and activities that focus on these aspects could serve as useful learning tools in providing targeted feedback and helping students develop their confidence and fluency. To address the challenges that students encounter when solving algorithmic problems -- particularly in regard to problem decomposition …

Reinforcement Learning For Autonomous Parking, Ravi Panchal

College of Engineering Summer Undergraduate Research Program

This research project proposes the development of an adaptive reinforcement learning (RL)-based parking system designed to handle complex parking maneuvers that are often unaddressed in existing research. Unlike previous works that focus on isolated maneuvers such as reverse parking or parallel parking, this work presents a flexible framework where multiple parking types (reverse, parallel, diagonal) are addressed through independent agents and then integrated into a cohesive system. The primary gap addressed by this work is the integration of diverse parking maneuvers into a unified RL framework with adaptability to dynamic and varied parking environments. Additionally, this project introduces curriculum learning …

Augmented Reality Application For Real-Time Coastal Data Visualization, Nithyasri Palanisamy

College of Engineering Summer Undergraduate Research Program

This project aims to develop an Augmented Reality (AR) application that overlays real-time coastal environmental data onto physical landscapes when viewed through AR devices such as smartphones and mixed reality headsets. By integrating data from machine learning models, computer vision-based event detection, coastal sensors, and geospatial mapping technologies, the application will provide users with an immersive and interactive experience, enhancing their understanding of coastal dynamics and environmental changes. The application will focus on observing coastal phenomena such as rip currents, tracking endangered coastal species and marine mammals, monitoring crowd levels on beaches, etc. Data sources will include NOAA's National Data …

Machine Unlearning: The Right To Be Forgotten, Colin Ngo

College of Engineering Summer Undergraduate Research Program

The objective of this SURP proposal is to investigate machine unlearning as a viable approach to support the right to be forgotten in artificial intelligence (AI) systems, many of which rely heavily on personal data. The capability to selectively remove user-specific information upon request—without necessitating full model retraining—is critical for safeguarding individual privacy and enhancing computational and energy efficiency. This project will undertake a systematic review of state-of-the-art unlearning techniques, evaluate their performance using standard benchmark datasets, and assess their feasibility in real-world applications. In addition, the project will provide participating students with practical experience in implementing and analyzing machine …

Deep Learning In Eye-Tracking Biomarkers For Anomaly Detection, Jay Rajesh

College of Engineering Summer Undergraduate Research Program

This research project proposes the development of a novel, data-driven framework for detecting concussions using machine learning (ML) and deep learning (DL) models applied to high-resolution eye-tracking data. Unlike traditional concussion assessments that rely on subjective evaluations, this work seeks to identify objective, quantifiable biomarkers derived from ocular dynamics—such as saccadic velocity, smooth pursuit accuracy, and pupillary response—captured through advanced eye-tracking technology. The project will explore state-of-the-art feature extraction techniques and predictive modeling approaches to uncover subtle neuro-ocular signatures associated with mild traumatic brain injury. By combining principles from biomedical signal processing, artificial intelligence, and neurophysiology, this work advances current …

Relational Algebra Interpreter, Sydney Lynch

College of Engineering Summer Undergraduate Research Program

We would like to build a compiler for relational algebra that converts it to SQL. This compiler will be used in database labs to give the students hands-on experience to write relational algebra code. Current relational algebra compilers that are open source are not very good and are hard for the students to use.

Hpc Configuration And Automated System Administration, Matty Witt, Deep Singh, Christopher Imirian

College of Engineering Summer Undergraduate Research Program

With the exponential growth in the use of computing, there is a growing need for undergraduate students to enter the workforce with experience with more complicated computing architectures. The CFD research group in the Aerospace Engineering Department received an HPC system and related computing hardware through the Air Force Research Lab. This system consists of three components: (1) a cluster compute engine with 256 CPU cores, 3.2 TB of RAM, 4 Tesla A100 GPUs, and 200 Gbps InfiniBand network backplane; (2) a high performance storage platform with 540 TB of raw storage, 200 Gbps InfiniBand network, and BeeGFS parallel cluster …

Hand-Tracking And Extended Reality Interfa, Alexander Bloomer, Alberto Cornejo

College of Engineering Summer Undergraduate Research Program

This project explores the use of Extended Reality (XR) technologies to enhance human- robot interaction in industrial contexts. Building upon prior research in affective and cognitive state recognition during human-cobot collaboration, this study investigates how natural hand and head gestures, captured through Meta Quest passthrough mode, can be used to communicate human intent to a Universal Robotics e-Series collaborative robot. The XR system provides users with an immersive, real-world visual interface while tracking motion and position in real time. The captured gestures are interpreted through a custom software pipeline that integrates machine learning models and rule-based logic to trigger adaptive …

Romance In Games, Camila Yermin

College of Engineering Summer Undergraduate Research Program

“Romance” is a common genre of books, especially among women, but in games it has a complex reputation: often relegated to visual novels or side mechanics in life simulations or role-playing games. These games rely on heavily scripted interactions, pre-written scenes, or represent relationships as a simple binary in code. This project aims to use cutting-edge embodied agent research and drama management research to build more inclusive, robust, satisfying, and interactive romance game mechanics. The project will likely be in 2D and use the Godot game engine, though the students involved will have the freedom to influence the design decisions …

Ai Fact-Checking Claims In Videos, Jake Altieri

College of Engineering Summer Undergraduate Research Program

This project investigates the use of acoustic signals captured during Fused Deposition Modeling (FDM) 3D printing to predict part quality and detect process anomalies. Traditional quality monitoring in FDM often relies on visual inspection or post-process evaluation, which can be slow and inconsistent. This research explores a low-cost, non-contact alternative using microphones and accelerometers to capture real-time audio and vibration signatures of the printing process. By applying signal processing and machine learning techniques to these acoustic signals, the project aims to classify part quality and identify defects such as under-extrusion, layer misalignment, or nozzle clogging. The outcomes have potential applications …

Computational Investigation Of The Role Of 3d Genome Architecture In The Lifecycle Of The Malaria Parasite, Srish Maulik

College of Engineering Summer Undergraduate Research Program

Malaria, a mosquito-borne infectious disease caused by the Plasmodium parasite, is responsible for more than a half a million deaths per year, the vast majority of which occur in central Africa. The parasite undergoes an incredibly complex cell molecular transformation as it transitions from living in mosquitoes to living in humans with different sets of genes being activated or silenced in order to evade the immune system of the host. Understanding how its genome guides this transition is critical for developing adequate treatments. In this project, we aim to develop a computational framework for investigating the role of the three …

Deterministic Motion Planning For Highly Articulated Multi-Link Robots, Matthew Flynn

College of Engineering Summer Undergraduate Research Program

Slender, multi-link, highly articulated, and extensible robots designed for minimally invasive surgeries have the potential to significantly transform the performance of common medical procedures. These advanced robots can reduce uncertainties and risks associated with surgeries, leading to shorter patient recovery times, accelerated healing, and minimized scarring. Made possible by their numerous mechanical linkages and concentric mechanisms, these multi-link articulated robots can navigate along non-linear paths, a capability that traditional straight probes lack. This flexibility allows surgeons to perform minimally invasive procedures on clinically significant targets that were previously difficult or impossible to access while avoiding vital anatomical structures. Beyond their …

Math+Cs Integrated Curriculum For K-12 Computer Science Education, Amogh Arora

College of Engineering Summer Undergraduate Research Program

This is a proposal for an activity to initiate an effort to create a series of X+CS integrated curricula for learning Computer Science (CS) in K-12. As a start, we examine Mathematics and CS standards, to find the cross-cutting concepts between the two fields. By leveraging these concepts, we bring to the foreground the ways CS can be used in the mathematical context. The goal for this research is to create a 15-week teacher training curriculum that will expose teachers to the CS concepts of Abstraction, Data Representation, Problem Comprehension and Decomposition, Control Structures, Functions and Generalization. Historically, Mathematics and …