Digital Commons Network^™

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 …

Technology Demonstration, University Of North Dakota. Energy And Environmental Research Center

EERC Brochures and Fact Sheets

Fact sheet about the Energy & Environmental Research Center’s technology demonstration abilities. Includes information on combustion systems, gasification and gas cleanup systems, and chemical and liquid processing.

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.

Unhsc Performance Curve Calculator, Daniel Macadam

UNH Stormwater Center

No abstract provided.

Integration Of Sco2 Brayton Cycles With Carbon Capture Systems, Nathan C. Stearns, Rajarshi Roy, Brian Schooff, Andrew Chiodo, Andrew R. Fry, Brian D. Iverson

Faculty Publications

Increasing global energy consumption and greater market penetration of intermittent energy sources require a baseline power source to enable renewable energies. Here, a case is made for pairing supercritical CO₂ Brayton cycles with carbon capture to create low-emission, high-efficiency, combustion-based power generation systems. Pairing carbon capture and storage (CCS) systems with supercritical carbon dioxide (sCO₂) Brayton cycles enables the reduction of greenhouse gas emissions in combustion systems, but with an associated energy cost. Three different representative models of CCS systems (oxyfuel combustion, amine scrubbing, and cryogenic carbon capture) are considered for pairing with an sCO2 Brayton cycle, …

Chemistry Of Inclusions By Size In Three Primary Copper Anodes, Charles Campbell, Michael Moats

Materials Science and Engineering Faculty Research & Creative Works

Three copper anodes from different commercial electro refineries were characterized to measure inclusion chemistry, size (diameter), and morphology. An automated scanning electron microscope (SEM) paired with energy-dispersive X-ray spectroscopy (EDS) was used to examine hundreds of inclusions near the mold and set sides of each anode. The investigation revealed that in the two anodes with less impurities (99.65% Cu and 99.75% Cu), many of the inclusions were Cu2O with an average diameter of 2 microns. The greater impurity anode (99.05% Cu, 4076 ppm Pb, 1939 ppm As, 635 ppm Bi) contained significant numbers of complex oxide inclusions, averaging 4.6 microns …

Selective Nickel Leaching And Preparation Of Battery-Grade Nickel Carbonate From Copper-Rich Industrial Intermediate, Janaka Jayamini Wijenayake, Michael S. Moats, Lloyd Masuzyo Mseteka, Lana Alagha

Materials Science and Engineering Faculty Research & Creative Works

The rising demand for electric vehicles (EVs) has driven a significant increase in nickel consumption, a critical element in EV battery production. An industrially viable hydrometallurgical process was developed for the selective recovery of nickel from a copper-rich industrial intermediate, containing approximately 70 wt.% Cu and 6 wt.% Ni, predominantly as sulfides alongside minor impurities. Approximately 90% of nickel was selectively extracted via single-stage atmospheric pressure leaching using HCl and H2O2 at 95 °C for 12 h, with the majority of copper retained in the leach residue, which can be utilized as a valuable feedstock for copper smelters. The selectivity …

Data Center Developments For Flexible Generation Dispatch, Advanced Infrastructure, And Ultra-Fast Digital Twins, Grant M. Fischer, Rosemary E. Alden, Donovin D. Lewis, Aron Patrick, Dan M. Ionel

Electrical and Computer Engineering Graduate Research

The rapid advancement and widespread integration of artificial intelligence (AI) is driving demand for unprecedented deployment of power-intensive computational infrastructure, including multi-megawatt data centers with the potential for facilities with gigawatt-scale capacity in the near future. In this paper, load growth projections for the US are reviewed, and an example energy dispatch solution considering a mixed energy portfolio with flexible, renewable, distributed, and load-based generation is employed. The brief technology review included in the paper covers aspects of electric power, cooling, and computational infrastructures. The concept of a data center digital twin for transient load, grid interaction, and hybrid energy …

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.

Building Bridges, Bridging The Gap: Measuring Engineering Confidence Across Ses, Amori Waller

College of Engineering Summer Undergraduate Research Program

Learning from failure is an essential component of both learning and practicing engineering. However, failure is often stigmatized and avoided in engineering education. This project aims to better understand how to support students throughout their engineering education to help them learn from their failures, rather than become frustrated or discouraged by them. The project will build on prior research in students’ responses to failure experiences to specifically analyze students who respond to failure in different ways and build on these experiences to help students in similar situations. During the SURP project, the student will use qualitative methods to analyze interview …

Safety-Critical Formation Control Of Non-Holonomic Multi-Robot Systems In Communication-Limited Environments, Logan Beard

College of Engineering Summer Undergraduate Research Program

This project explores advanced methodologies for distributed planning, formation control, and coordination in heterogenous multi-agent robotic systems consisting of small mobile robots and nano unmanned aerial vehicles (UAVs). Leveraging decentralized control theories and optimization techniques, the research aims to develop robust algorithms for real-time collaborative task execution, efficient formation maintenance, and adaptive coordination strategies. Python and ROS will be used extensively to simulate, validate, and experimentally deploy distributed robotics algorithms. The student researcher significantly contributes to the theoretical and practical advancement of multi-agent system technologies.

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 …

Eggbeater Antenna Design 915 Mhz, Anshul Deshmukh

College of Engineering Summer Undergraduate Research Program

The Sal-E cube sat mission that is planned for launch in 2026 includes a 902-928 MHz receiving module called the Space Quacker Advanced Development (SQUAD) module. The SQUAD module uses the LoRa modulation format for unlicensed uplink to the satellite using the 902-928 MHz Industrial, Scientific, and Medical (ISM) band. The goal of the SQUAD module is to demonstrate the link robustness of the LoRa communication standard to a low earth orbit (LEO) satellite using this ISM band. To demonstrate this communication link, a 902-928 MHz uplink ground station needs to be established at Cal Poly. The goal of this …

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.

Analysis And Evaluation Of Backtracking Settings For Energy Yield Optimization At The Cal Poly Solar Farm, Kayla Go-Oco

College of Engineering Summer Undergraduate Research Program

The Cal Poly Solar farm has been built as a single axis tracking facility with two different types of panels. Both conventional single cell solar panels and twin cell solar cells have been used in its construction. Twin Cell panels typically perform better than their conventional counterparts when shaded by other panels in the row in front of them in a fixed tilt system. However neither module performs well when even a small portion is shaded. This project will access the system API to access data for the field and process to determine the energy yield improvements that can be …

Exploring Impact Of Student’S Proximity To Summer Camp And Demographics On Their Interests In Engineering, Yamil Balcells

College of Engineering Summer Undergraduate Research Program

EPIC is a one-week Cal Poly program where middle-and high-school students explore engineering through hands-on projects in a university setting. In partnership with the Migrant Education Program (MEP), EPIC reserves spots for migratory students and provides bilingual counseling and support. These services ensure equitable access and a welcoming environment for students developing English proficiency.

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 …

Stretchable Mechanoluminescent Devices For Energy Harvesting And Real-Time Force Sensing, Lucas Taliaferro, Phoebe Ong

College of Engineering Summer Undergraduate Research Program

Our group has been developing a novel manufacturing technique to fabricate flexible sensing devices using electrostatic force. Previously, we focused on utilizing nanomaterials as the sensing materials to measure strains. Building on our experience with the manufacturing technique, we will move forward to incorporate other smart materials in the flexible device to achieve self-powered sensors. Besides, to better understand the fabricated material properties, we are interested in characterizing the microstructural behavior of the material networks via microscopic imaging and finite element simulations. The students will have the opportunity to closely work with Dr. Wang’s interdisciplinary research group.

Analyzing Wearable Sensor Data From Individuals Undergoing Motor And Neurological Rehabilitation, Nolan William Turk

College of Engineering Summer Undergraduate Research Program

An ongoing study funded by the National Science Foundation (NSF) is focused on developing computational models of rehabilitation for people post-stroke. Stroke affects around 800,000 people per year in the US, and often leaves people with limited motor (movement) and neurological (brain-based) capability. Wearable sensors may allow clinicians to better understand how these individuals recover, and to better design therapies and interventions. We are seeking students who can use existing software, and perhaps adapt the software to extract, analyze, and visualize detail from study participants. This project will involve with the Cal Poly PI, and collaborators from physical therapy. This …

Analyzing Wearable Sensor Data From Individuals Undergoing Motor And Neurological Rehabilitation, Carly Smith

College of Engineering Summer Undergraduate Research Program

An ongoing study funded by the National Science Foundation (NSF) is focused on developing computational models of rehabilitation for people post-stroke. Stroke affects around 800,000 people per year in the US, and often leaves people with limited motor (movement) and neurological (brain-based) capability. Wearable sensors may allow clinicians to better understand how these individuals recover, and to better design therapies and interventions. We are seeking students who can use existing software, and perhaps adapt the software to extract, analyze, and visualize detail from study participants. This project will involve with the Cal Poly PI, and collaborators from physical therapy. This …

Radiative Heat Transfer Using Spectrometers, Metztli Singha

College of Engineering Summer Undergraduate Research Program

Radiative heat transfer and the fundamental understanding of the electromagnetic spectrum, ranging from infrared to ultraviolet, are crucial topics for space environments and aerodynamic re-entry systems. The advancement of the aerospace curriculum in these areas will lay the cornerstone for undergraduate students focusing on experiential learning. A specific laboratory experiment involving black body radiation and modes of heat transfer, with a particular emphasis on radiation, will be scoped, designed, and fabricated during the SURP performance period. The outcomes of this work will standardize the introductory courses on heat transfer specific to aeronautics and astronautics concentrations, which is mainly lacking outside …

Experimental Study Of Flexible Wing Design For Low Subsonic Flow, Blake Shaffer, Timothy Barry

College of Engineering Summer Undergraduate Research Program

The aim of this project is to study experimentally the structural stability of highly flexible wings under low subsonic flow conditions. The experiments will be carried out at the low-speed wind tunnel in the Aerospace Engineering department. As part of this project, the student will design and build a variety of different flexible wing structures and test their performance in the wind tunnel--the experiments will involve pressure, deflection, and strain measurements. Both additively manufactured and built-up structures will be explored as part of this project. The project will also require the student to perform finite element simulations for the wing …

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 …

Propeller Characterization Lab, Stefanos Rosenbaum

College of Engineering Summer Undergraduate Research Program

This research focuses on creating an experiment to measure performance of an aircraft propeller on a specially designed stand. Results from the wind tunnel experiments measuring thrust, rotation speed and torque will enable students to create a database of propeller characteristics for use in aircraft design projects. Students in aerospace engineering are regularly assigned design projects powered by turboprop or propeller driven engines. There is not an easy way to verify design performance other than simplistic calculations or extrapolation of open-source wind tunnel data, and not a lot of data is available. Being able to correlate actual test data from …

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 …

15cm Gridded Ion Thruster, Arjan Reyes

College of Engineering Summer Undergraduate Research Program

This research focuses on optimizing the configuration of a 13cm ion thruster for long term efficiency. Ion thrusters produce thrust for spacecraft when they are in orbit. The thruster needs to be efficient enough to last for the lifetime of the spacecraft as well as through its deorbit procedure. Thruster efficiency is achieved through optimizing the distribution of the high velocity beam of charged particles at the exit that impacts fatigue patterns on voltage grids. The shape of the beam is determined by the placement of magnets on the thruster walls. An experiment to test configurations for increasing efficiency through …

Spacecraft Reaction Wheel Simulation Testbed, Shiva Pulmamidi, Daniel Kim

College of Engineering Summer Undergraduate Research Program

There are three typical methods used to control the attitude (or orientation) of spacecraft in orbit. They are momentum exchange devices (reaction wheels and control moment gyroscopes), magnetic torquers, and thrusters (both cold and hot gas). The PolySim research group is currently developing a spacecraft attitude dynamics simulator utilizing reaction wheels. The simulator floats on a spherical air bearing and is balanced to accurately simulate the rotational motion of a spacecraft in orbit (not including the orbital motion). As a continuation of that project, we have completed the development of spacecraft attitude simulator using cold gas thrusters to control the …

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.