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Undergraduate Programs

2021 Senior Design Presentations Schedule



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EncIDE: Encellin Implant Delivery System
2:15 – 2:50
John DePalo, James Peterman, Isabelle Vidamo
Advisors: Unyoung (Ashley) Kim, Verna Rodriguez
We set out to develop a minimally invasive subdermal implant delivery system to deposit Encellin's therapeutic device for the treatment of Type 1 diabetes. Following an initial incision in the forearm, our tool dispenses the implant at a standardized depth and orientation in an effort to reduce procedural variability and associated patient risks.

Non-Ribosomal In Vivo Protein Ligation
2:55 – 3:30
Sarah Desautel, Victorino Miguel Francisco, Kenneth Joseph
Advisor: Zhiwen (Jonathan) Zhang
Protein ligation is an integral yet inefficient process in the development of drugs and diagnostic assays. Our Senior Design project aims to improve upon current industry standards by creating a new protein ligation method that relies on a single enzyme, Sortase A, rather than tedious and error-prone in vitro techniques.

EView: High Throughput and On-Chip Characterization of Single Engineered Extracellular Vesicles
3:40 – 4:10
Brendan Johnson, Jiayi Zhang
Advisor: Bill Lu
Engineering extracellular vesicles (EVs) with transmembrane scaffolds holds great promise for targeted drug delivery, but EV heterogeneity imposes a significant challenge on fully understanding engineered EVs and engineering efficiency. This project aims to analyze individual engineered EVs for their biological and functional characteristics and reveal distinct capabilities of various scaffolds.

X-Messenger Molecule
4:20 – 4:50
Julianna Bernardo, Jiacheng Tan
Advisor: Zhiwen (Jonathan) Zhang
Knowing the fact that antibiotic-resistant Gram-positive bacteria are emerging and effective therapeutics are lacking, we will focus our engineering efforts on discovering and developing potential anti-infective therapeutics against Sortase A's messenger molecule that will not impose the risk of further antibiotic resistance and yet can effectively eliminate the pathogenic bacteria.


Artificial Lumbar Spinal Disc Implant
2:15 – 2:50
Sara Layton, Nikhil Pai, Michael Rueckert
Advisors: Bill Lu, Maryam Mobed-Miremadi
We are designing an Artificial Lumbar Spinal Disc Implant to counter degenerative disc disease within patients as well as alleviate back pain. Our goal is to create a long lasting restorative disc with an emphasis on revise-ability for patients in the case of repeat surgeries.

Flow Visualization of Bolus Microcapsule Delivery through 3D Printed Microneedles
2:55 – 3:30
Lexi Enstrom, Sophie Quisling, Leana Vestal
Advisor: Maryam Mobed-Miremadi
Microneedles enable painless delivery and withdrawal of biologicals through the dermis. Operating within the therapeutic range, flow and microcapsule trajectory through the custom 3D printed device were simulated pre-puncture. Using the validated model, multiple failure modes of the 3D printed artifacts were tested to determine their effect on flow profiles.

Skin Phantoms for Biowearable Testing
3:40 – 4:15
Brooke Fitzwilson, Ruby Karimjee, Jordan Spice
Advisors: Emre Araci, Prashanth Asuri
The biowearable device industry is in need of a model that can accurately mimic the properties of skin. Our project design includes a skin phantom and corresponding COMSOL simulation, which emulates the perspiration and impedance spectrum behavior of human skin.

G-MAP: Gastrointestinal Myoelectric Activity Phantom
4:20 – 4:55
Kei Castleberry, Sarah King, Edie O’Connor
Advisors: Prashanth Asuri, Shoba Krishnan
This project aims to develop a phantom that can accurately emulate the myoelectric activity of the stomach, small intestine, and colon. The phantom will meet the biowearable industry’s need for a synthetic platform to test devices that non-invasively measure the motility of the gastrointestinal tract.

Minimally Invasive 3D Printed Microneedles for Glucose Monitoring
5:05 – 5:40
Daniel Bermudez, Josephine Semaan, Amanda Yaung
Advisor: Unyoung (Ashley) Kim
With the purpose of making patient care for diabetics more affordable, accessible, and reliable, our project aims to create a minimally invasive glucose monitoring system through the use of 3D printed microneedles. This system would have extensive applications in helping improve patient care for diabetics.


Microfluidic Barcode Device for Human Movement Data Storage
2:15 – 2:50
Justin Culpepper, Gianna Gathman, Katie Neighbors
Advisor: Emre Araci
We have developed a computer model of a novel wearable microfluidic strain sensor to support human physical therapy. Our microfluidic pump design uses the skin strain produced by movement to create a fluidic pattern that resembles a barcode. This device will provide patients and clinicians information to bridge inter-appointment gaps.

Classification of Breast Cancer Using Deep Learning and Mammogram Images
2:55– 3:30
Travis Kay, Derrick Nguyen, Lashan Wijayawickrama
Advisor: Yuling Yan
Using an open-source mammography dataset, we examined several pre-trained convolutional neural network (CNN) models to find the best model for classifying breast masses and cysts. This CNN model can be used to assist radiologists in rapid screening of breast cancer and improving the diagnostic accuracy.

MilkGuard: Predictive Modeling and Mobile App Development
3:40 – 4:10
Beau Hsia, Emma McCurry
Advisors: Unyoung (Ashley) Kim, Maryam Mobed-Miremadi
MilkGuard aims to produce a sensitive, low-cost, and environmentally friendly biosensor that can detect the presence of E. Coli in donated human breast milk. This year, we focus on building 1) a dynamic CAD model of our colorimetric assay and 2) a user-friendly mobile app that interfaces with our sensor.

Classifying Brainwaves for Brain-Computer Interface Technology
4:20 – 4:50
Brendan Lawler, Derrick Wang
Advisor: Yuling Yan
This project's aim is to utilize pre-trained image classification networks to develop a deep learning (DL) model for signals recorded via electroencephalography (EEG). We focused on the classification of motor imagery tasks, which is useful for the development of brain-computer interfaces (BCIs).

Predictive Model for Design of a 3D Developmental Neurotoxicity Platform
5:05 – 5:40
Emma Barrett-Catton, Cameron Read, Murial Ross
Advisors: Prashanth Asuri, Maryam Mobed-Miremadi
We worked on developing a predictive model, based on literature review and statistical analysis, to test developmental toxicity on early neuronal differentiation in three-dimensional cell culture. Such models may be useful for clinical and pharmaceutical research.


Modular Steel Frame for Residential Use
2:15 – 2:50
Kevin Cheng, Derek Eggertson, Noah Rapadas
Advisor: Reynaud Serrette
Our senior design project is a modular frame structure designed with cold formed steel. There are a variety of potential applications for this structure, however for our project we focused on designing a durable and resilient single-family residence that can be placed in a wide range of locations.

Suburban Tiny Home Development
2:55 – 3:30
Paul Carr, Chris Wang, Colin Wood
Advisors: Laura Doyle, Edwin Maurer, Tonya Nilsson
To capitalize on increased workplace flexibility brought by COVID-19, we designed a tiny home development to give stay at home workers more sustainable living options. Using a plot of land outside Seattle, we engineered a model home structure, outlined water resource and drainage systems, and created a municipal layout.

Warehouse Design for Automotive Parts Manufacturers in Bekasi, Indonesia
3:40 – 4:10
Marco Ardiya, Stanley Lemena
Advisor: Reynaud Serrette
This project involves designing the superstructure of a warehouse/office building in partnership with PT Cipta Mulia Aditama, located in Bekasi, Indonesia. The project focuses on commercial and community needs, more on commercial as the goal is to allow access for international companies to provide resources the neighboring industries need.


East Orosi Clean Water Initiative
2:15 – 2:50
Julia Carroll, Peter Naughton, Trey Novara
Advisor: Aria Amirbahman
East Orosi, California, has been devastated by nitrate contaminated groundwater as local legislation fails to act. This project analyzes multiple designs that provide potable water solutions for the 800 low-income residents. The objective is to determine the optimal design while bringing awareness to the idiosyncrasies of the California water crisis.

Water Treatment Solutions for Wildfire Impacted Watersheds
2:55 – 3:30
Michael Reyes, Jackson Shank, Mai Sinada, David Villani
Advisor: Aria Amirbahman
In watersheds affected by wildfires, contaminants are delivered to water treatment plants or supply reservoirs at extreme and unmanageable concentrations. Focusing on the City of St. Helena, our proposed solutions target the removal of sediments, increased nitrates, and fire retardant chemicals from runoff in order to assist treatment plants.

Seedling Irrigation Design for Valley Verde
3:40 – 4:15
Sarah Dao, Sally Ferguson, Hope Laborin
Advisor: Laura Doyle
This project is in partnership with Valley Verde, a non-profit organization that offers edible gardens to underserved communities. With increased demands and stress on the organization due to COVID-19 and climate change, SCU civil engineers will design an automated irrigation and drainage system to optimize Valley Verde’s water usage.

Potable Water for a Volcanic Community in Rural Guatemala
4:20– 4:55
Marieli Rubio, Jichan Seo, Connor Thomas
Advisors: Aria Amirbahman, Laura Doyle, Edwin Maurer
The intent of this project is to design a water treatment and distribution system that will provide potable water for a small volcanic community in Guatemala. It will remove the high levels of heavy metals and suspended solids to alleviate water-related illnesses in the area.


2:15 – 2:45
Jeffrey Huang
Advisor: Maya Ackerman
A Co-creative Drawing Application for Personalized Digital Expression

Alzheimer’s Disease Diagnostic Support Tool
2:55 – 3:30
Chelsea Fernandes, Aiyushi Kumar, Shreya Venkatesh
Advisors: Ahmed Amer, Julia Scott
Our project aims to develop a web-based diagnostic-support tool that physicians can use in a clinical setting to increase the efficiency and accuracy of diagnosing Alzheimer’s Disease. Our solution uses a machine learning model to classify patients into one of three possible stages of Alzheimer's Disease using multiple clinical parameters.

Music For Me
3:40 – 4:10
Zak Graber, William Henrion
Advisor: Maya Ackerman
A web application that allows users to play music alongside an AI in an intuitive way.

Spend Happier
4:20 – 4:55
Jack Guillet, Kyle Moore, Cole Steere
Advisor: Maya Ackerman
Spend Happier ( is a web application that tracks the value of each purchase in addition to cost. It helps users to spend more money on the things they love and less on the things they don't.

CREATE: Creative Resources to Express Art Through Engagement
5:05 – 5:35
Katherine Sanchez, Ari Soriano
Advisor: Maya Ackerman
A platform of co-creative systems that users can engage with as a creative outlet or therapeutic resources. Systems include art, music, and dance options and are matched with users interests and evaluated based on mood assessments of the users before and after using each system.


HUSK: High-level Network Feature Utility for Security-based Kernel
2:15 – 2:45
Dillon Leigh, Shaunak Mashalkar
Advisors: Behnam Dezfouli, Yuhong Liu
Implementation of traffic feature generation within the Linux kernel's network stack, for use in userspace security applications

Enhanced Sensing Methods for UAV-based Disaster Recovery Applications
2:55 – 3:30
Connor Azzarello, Christopher Gerbino, Ruchir Mehta
Advisor: Behnam Dezfouli
Natural and human-caused disasters cripple, displace, and diminish civilian populations. This project aims to develop UAV technology that uses image analysis to identify the location of survivors. We will combine inexpensive hardware systems and novel image classification to improve the efficiency of humanitarian organizations and developing nations during disaster response.

Drone Mesh Wifi System for Disaster Scenarios
3:40 – 4:10
Cameron Burdsall, Mark Rizko
Advisor: Behnam Dezfouli
Our project is about creating a drone system that can deploy a wireless mesh network over a disaster area, allowing first responders to use internet-enabled devices and aid in the process of finding survivors by using advanced sensors and allow authorities to send out alerts to people in the area.

Seamless Container Migration Between Edge and Cloud
4:20 – 4:55
Angeline Chen, Tamir Enkhjargal, Aditya Mohan, Jonathan Yezalaleul
Advisor: Behnam Dezfouli
The purpose of this project is to evaluate the performance of running container management systems on resource-constrained machines such as Raspberry Pi. Through the experiments, our group proposed methods to reduce the overhead of management and migration depending on the workload type.


StickARs: Effortlessly Apply a Fun Overlay to the Real World
2:15 – 2:50
Théo Arrouye, Jackson Centeno, Morgan Fleshren, Vasilis Odysseos
Advisor: Ahmed Amer
StickARs is an iOS app for the customization, placing, and viewing of stickers in augmented reality. StickARs provides a library of sticker templates for users to select from. Stickers can have different audiences (private/public/custom). Users can also follow tags, join groups, and add friends to customize their experience.

Real-Time Multi-Camera Traffic Analysis on a Single Intersection with IoT Devices
2:55 – 3:35
Justin Liu, Kent Ngo, Tyler Niiyama, Ethan Paek, Spencer Tsang, Jackson Tseng
Advisor: David Anastasiu
This project will attempt to solve two problems: tracking individual vehicles within an intersection, and counting vehicles based on the path they take through an intersection. By improving the efficiency of machine learning algorithms and utilization of cost-efficient IoT devices, it aims to improve and enhance real-time traffic analysis.

3:40 – 4:10
Andrea Horvath, Isabel Wu
Advisor: Dan Lewis
Siheyuan is a VR learning experience that allows the user to gain a better understanding of the Chinese written language using visual storytelling and interactive drawing of Chinese characters.

Multi-Class Multi-Intersection IoT-Based Vehicle Counting
4:20 – 5:00
Donovan Allen, Maggie Dong, Jay Ladhad, Colin Rioux, Chris Tian
Advisor: David Anastasiu
Current machine learning algorithms for vehicle counting and tracking are not designed to run on IoT devices in real time. Our team proposes a decentralized method of multi-class vehicle counting and tracking through a system of IoT devices that communicate vehicle identification information in a multi-intersection environment.

Smart Pantry
5:05 – 5:40
Audrey Hou, Sukruth Krishnakumar, Jacob Lucke
Advisor: David Anastasiu
Smart Pantry makes managing groceries more convenient by maintaining data of what is in the user's pantry. Data is obtained using a novel weight to computer vision mapping method to detect grocery usage. A collaborative filtering recommender system queries on available ingredients to suggest recipes.


IoT MarketOne
2:15 – 2:45
Michael Zarrabi

Advisor: Angela Musurlian

An e-commerce site that includes IOT products from producers.

Nicaragua Weather App
2:55 – 3:30
Alexa Grau, Justin Ling, Greta Seitz
Advisor: Angela Musurlian
A mobile weather application to be implemented in rural Nicaragua as a way to collect and distribute necessary weather information to the community which will influence agricultural practices. 

Elevate Tutoring
3:40 – 4:10
Sparsh Chauhan
Advisor: Silvia Figueira
Elevate Tutoring needed a platform for both program managers to do their daily scheduling tasks and tutors to submit data such as unavailability times. The solution is a Salesforce web application fully customized for completing tasks such as handling tutor profiles, viewing shifts in calendar layout, and other operational functions. 

MARTHA: Offline Educational Tool for Cameroonian Refugees
4:20 – 4:55
Sarah Ahmed, Marco Marenzi, Leila Scola
Advisor: Silvia Figueira
MARTHA is a mobile application that delivers educational resources offline in the form of PDF files to Cameroonian refugees. The content ranges from vocational training to hygiene care. A remote database stores the files to be accessed from the Android application when the Internet becomes available.  

OneMe: Virtual Identity Creation and Verification, as a Service
5:05 – 5:35
James Grom
Advisor: Silvia Figueira
OneMe, a third-party web service, provides virtual identity creation and verification - a virtual passport for users. OneMe issues an initial account, after a one-time stringent verification/ authentication process, that requires a government ID. Subsequently, any virtual entity that requires a OneMe account ensures that its users aren't duplicated, impersonated, or misrepresented.  


Smart Grid Security Simulator (SGSS)
2:15 – 2:45
Christopher Woo
Advisor: Xiang Li
The web application, Smart Grid Security Simulator, is designed to make it easier for people, who intend to learn about smart grid security, to better visualize the failure of lines in a network due to various attacks through modification and testing of various networks and attacks.

2:55 – 3:30
Darren Codipilly, Brandon Quant, Horatio Xiao
Advisor: Xiang Li
With TasteMate, we aim to improve current recommendation systems by utilizing a link between the nutrition facts of a dish and different flavor profiles. Our goal is to create a personalized flavor based recipe recommendation system that uses a user’s taste profile to provide the best matching food recipes.  

Improved Graph Learning Performance with Hyperparameter Tuning
3:40 – 4:10
Drew Ligman
Advisor: Zhiqiang Tao
This project thus seeks to increase the effectiveness of Graph Machine Learning performance through hyperparameter optimization. We specifically analyze Graph Convolutional Networks as the model in question and use a BOHB approach to hyperparameter tuning.

Urban Planning Optimization via “Cities: Skylines”
4:20 – 4:55
Jack Cunningham, Carter Duncan, Alexander Kennedy, Andrew Wang
Advisor: Ying Liu
Used Reinforcement Learning techniques to train a game agent to play the city simulator "Cities: Skylines". The agent will learn certain patterns of playing and thus optimal strategies. This will result in a simulated city environment that is strategically laid out and more optimally designed than a human-designed one.  

Extracting Creative Procedural Knowledge from Web Design Tutorials
5:05 – 5:35
Federico Madden
Advisor: Zhiqiang Tao
A web app that uses a deep neural network to extract specific procedural steps (such as File > New or Layer > New Layer) from the plain text content of tutorials for graphic design software such as Photoshop.  


Efficient Feature Collection for IoT Devices Using DPDK
2:15 – 2:45
Kade Harmon, Jordan Murtiff
Advisor: Behnam Dezfouli, Yuhong Liu
Older packet sniffing tools often use a large number of CPU cycles and energy in order to conduct real time traffic analysis. Our project utilizes the Data Plane Development Kit in order to bypass the kernel for more efficient network feature collection and analysis for a multitude of purposes.

Correlating Diversity and Resistance to Misinformation in Social Media Groups
2:55 – 3:30
Jasper Ahn, I Chang, Orion Sun
Advisor: Yuhong Liu
This project's purpose is to measure different diversity metrics for Facebook groups and correlate the results with the amount of misinformation spread within the groups. Our results could give insight into how different aspects of group diversity influence the spread of misinformation and how to better combat false information. 

Security of Android Bluetooth with Respect to Colocated Apps
3:40 – 4:10
Omar Garcia, Sean Kelker
Advisor: Yuhong Liu
We created a malicious application targeting the connection between smartphones running the Android operating system and popular Bluetooth devices to steal the data those devices generate, and show the above vulnerability has practical applications. We also change the source code of the Android OS creating a defense against this attack.  

Infodemic: Understanding COVID-19 Public Sentiment Using Social Media Data
4:20 – 4:55
Christine Chye, Olivia Figueira, Yuka Hatori, Liying Liang
Advisor: Yuhong Liu
With the outbreak of the COVID-19 pandemic, an overabundance of information related to the virus was released through social media. To understand the public’s response to public health messaging, we analyze the sentiment of social media data and whether it parallels the spread of COVID-19.  

Lightweight Speed Protocol
5:05 – 5:35
Zachary Hardy
Advisor: Yuhong Liu
A network protocol that aims to be lightweight, fast, and secure. Written in C with IOT devices in mind. 


Machine Learning-Based Side-Channel Analysis on the Advanced Encryption Standard
2:15 – 2:45
Jack Edmonds, Tyler Moon
Advisor: Fatemeh (Sara) Tehranipoor
Information security is of utmost importance in our digital age. Because of this, awareness of any vulnerabilities that may exist in data encryption methods is vital. Our project’s focus is on examining the potential security threat of machine learning-based side-channel attacks on the Advanced Encryption Standard implemented on a microcontroller.  

Telehealth Sensor Authentication Through Memory Chip Variability
2:55 – 3:30
Holden Gordon, Calvin Kimbro, Thomas Lyp
Advisor: Fatemeh (Sara) Tehranipoor
As the world of remote patient monitoring grows, so too does the threat of malicious third parties abusing remote sensor security vulnerabilities. Our project extracts hardware security primitives based on MLC Flash NAND memory chip’s manufacturing process variations to build a unique identifier for telehealth sensor applications.  

Attacking Logic Locked Circuits Using Reinforcement Learning
3:40 – 4:10
Jake Mellor, Allen Shelton
Advisor: Fatemeh (Sara) Tehranipoor
Evaluating reinforcement learning as a method to defeat modern logic locking techniques. 


Portable Radio Frequency Direction Finding Package
2:15 – 2:45
Austin Colon, Jacob Taub
Advisor: Kurt Schab
Design a compact, portable, multi-platform radio frequency (RF) direction finding (DF) system. The system will provide options for both real-time readouts and aggregated measurements for post-processing analytics by geotagging a line of bearing (LOB) and received signal strength (RSS) of target signals. 

Powering IoT Sensors with RF Energy Harvesting
2:55 – 3:25
Kristi Nguyen, Austin Rothschild
Advisor: Kurt Schab
This project aims to design a radio-frequency (RF) energy harvesting system to wirelessly power IoT sensors in an urban environment. An antenna and rectifier system interfaced with a power management circuit will effectively convert incoming RF energy into a form able to power a wireless sensor

Wafer Handling Automation for Aligned CNTs (WHAAC)
Eric Bressinger, Steven Pretlove
Advisor: Shoba Krishnan
Design a system for a carbon nanotube furnace that automates part of the process for inserting and removing the wafer. The project is made of two phases: automatically shutting the opening to the furnace and sliding the wafer plate into and out of the furnace.

Aquaponic Biofuel Nanogrid
4:20 – 4:50
Martin London
Advisors: Maryam Khanbaghi, Maryam Mobed-Miremadi
Self-sufficient aquaponic system viability is limited by inadequate power-balance associated with synergetic biofuel production and wastewater remediation. This project highlights control, net carbon-neutral flue-gas utilization; and minimized aquaponic power-use associated with growth of microalgae biofilm on novel materials with a unique airlift mixotrophic mechanism.


Automated Mixed-Dose Pill Dispenser with Image Verification
2:15 – 2:45
Rohan Bhatt, Nairu Garcia-Acevedo

Advisor: Andrew Wolfe

This project aims to reduce the human error in the dispersion of medication pills by automating the process in a cost effective manner with a robotic arm while improving mixed-dose verification with image classification.

Adaptive Deposition of Difficult Materials
2:55 – 3:30
Abel Daniel, Emily Holden, Gabriela Sanches de Carvalho Silva
Advisor: Andrew Wolfe
Our project uses images of a unique object (a cupcake) to adapt designs in a predetermined library in order to extrude those designs most accurately for that specific object's shape. 

IoT Blinds Controller
3:40 – 4:10
Ryan Claggett, Sayuru Ranamukhaarachchi
Advisor: Andrew Wolfe
Since temperature maintenance is the largest consumer of energy in a household, our project identifies the temperature of the room and uses two different types of blinds systems to assist with maintaining a more stable temperature so that the need for heating and cooling will be reduced.

Sensor Pods
4:20 – 4:50
Stephi Boyer, Vivian Tu
Advisor: Andrew Wolfe
The project aims to develop a solar-powered sensor network using Bluetooth mesh for Aver Winery that would analyze water uniformity throughout the field. This would allow the owner to quickly and efficiently tend to the crops' needs.


Mobile Nanogrid
2:15 – 2:50
Michael Batshon, Charles Ju, Benjamin Mahony, Daniel Mendoza
Advisors: Maryam Khanbaghi, Gaetano (Tony) Restivo
The Mobile Nanogrid is a vehicle-mounted power solution that uses solar PV and battery storage to meet camping and recreational power needs. This project is a proof-of-concept system that displays a working and viable mobile solar power solution.

Adaptive Robotic Chassis (ARC): RoboCrop, A Smart Agricultural Robotic Toolset
2:55 – 3:35
Steven Bucher, Brooke Broszus, Alejandro Gutierrez, Krissy Ikeda, Ariana Low
Advisor: Christopher Kitts
Addressing critical labor shortages in the agriculture industry, RoboCrop is a payload device that supports a variety of agricultural tasks, specifically the pruning of strawberry flowers. This system is integrated with an agricultural rover led by a research team in the Robotics Systems Lab and will service local strawberry growers.

Marine Robot Deployment and Control System
3:40 – 4:15
Nicky Castillo, Nick Ellis, Trent Kelsall, Matthew Kiyama
Advisor: Christopher Kitts T
he goal of this project is to develop a complete marine research operations package by rebuilding a fully-functional remotely-operated underwater robot with closed-loop heading and depth controls, implementing a top-side graphical user interface, and designing a dedicated launch and recovery system.

4:20 – 5:00
Duncan Clark, Justin Cole, Zachary Karat, Aidan Nickels, Cole Wolfe
Advisors: Vlad Ivashyn, Christopher Kitts
A UAV that utilizes ground effect for the purpose of marine research. The craft's experimental airframe allows it to be used as an aerial vehicle, land on water and perform tasks underwater, the submersible operations aspect is not part of our project's scope. Our team focused on aerial performance including ground effect operations.

Modular Oceanic Autonomous Underwater Vehicle (AUV) for Novel Actuation (MOANA)
5:05 – 5:50
John Elstad, Sean Even, Bryan Gilbertson, Matthew Holmes, Andrew Kambe, Gregor Limstrom, Robert Percell
Advisors: Christopher Kitts, Godfrey Mungal
An Autonomous Underwater Vehicle (AUV) to demonstrate low-drag design, internal actuation, and distributed computing for low power operation. This test vehicle will demonstrate the capabilities of long-range and long-endurance remote aquatic sensing and will provide the Robotics Systems Laboratory (RSL) with proofs of concept for future Long Range AUV research.


Machine Learning Based Model for the Detection of Brain Aneurysms from MR Angiography
2:15 – 2:50
Katherine Becknell, Claire Bushnell, Rachel Fitzsimmons, Emily Sumner
Advisors: David Anastasiu, Yuling Yan
This project aims to process MRA images to detect the presence of brain aneurysms through the use of a convolutional neural network based machine learning algorithm.

Santa Clara Community Garden Composting Device
2:55 – 3:30
Nicholas Buccino, Kyle Uyehara, Jay Weber
Advisor: Jessica Kuczenski
In order to improve the efficiency and volume of organic waste being composted at the Santa Clara Community Garden, our team has developed an effective and sustainable solution to simplify the garden's current composting problems. Furthermore, we would like to use this device to promote the benefits of environmental sustainability.

Jamming Attack Workaround Study
3:40 – 4:10
Soren Madsen, Jack Schoen
Advisors: Behnam Dezfouli, Andrew Wolfe
JAWS is a detection and recovery system designed to prevent against deauthentication attacks in real-time by monitoring WiFi network traffic.

Dynamic Solar Shading System
4:20 – 4:55
Walker Battey, Alexander Kravstov
Advisor: Jessica Kuczenski
Dynamic solar shading mechanism is implemented on a newly built pergola, located on Kids on Campus playground, in order to reduce the exposure of dangerous UV-light radiation on children’s skin and maximize the use of space during daylight hours.

Crossroad – Avoid Crowd Intelligence
5:05 – 5:40
Yuzheng Wu, Haochen Zhang, Xukun Zhang
Advisors: Ying Liu, Andrew Wolfe
Crossroad targets to solve the problem of long waiting times due to the overflow of the crowd. The project combines pre-installed facilities’ cameras with programmed sensors to monitor the engagement of crowds while using machine learning algorithms to analyze the data. The system provides live information about consumer capacity.


Hydrofoil Propulsion Optimization
2:15 – 2:50
Zachary Flood, Nicholas Potter, Wesley Sava, Trentan Walker
Advisor: Godfrey Mungal
Taking a motorized Hydrofoil Board's propulsion system and optimizing and redesigning the propeller and duct design to increase hydrodynamic efficiency and battery life.

Wildfire Prevention and Suppression System
2:55 – 3:30
Johnny Dimas-Flores, Ansh Jetly, Antonio Lorenzo
Advisor: Godfrey Mungal
Our project aims to solve the design problem of creating a marketable product with the capability of protecting the property of an individual from the threat of a wildfire assuming no external power or water.

Frugal Urban Greenhouse
3:40 – 4:15
Connor Pearson, Alexandra Rivera, Emma Rosicky
Advisor: Godrey Mungal
Our project partners with local nonprofit Valley Verde to improve their backyard greenhouse design based on weight, manufacturability, user experience, and cost. The relationship with our client was a priority and led to the creation of instructional guides and materials. Other considerations included efficiency in thermal regulation and water usage.

Portable Bicycle-Powered Refrigeration
4:20 – 5:00
David Gilbert, Zach Gotvald, Kerri-Ann Kamei, Lindsay McConville, Brooke Watson, Brian Woo-Shem
Advisor: Hohyun Lee
Our human-powered refrigeration system enables the transport of vaccines on a bicycle to regions with unreliable electricity and minimal infrastructure. The system uses thermoelectric cooling and pedal-powered electric generation for travel in off-grid, rugged terrain and it is adaptable to different bicycles.
The Drier Dryer
5:05 – 5:40
Daniel Anderson, Justin Lee, Thomas Morey, Josh Sunada
Advisor: Hohyun Lee
Increase the efficiency of a dryer by removing moisture from the incoming air. This should minimize the air’s relative humidity and maximize the amount of water it can remove from clothes, thereby reducing the dryer’s operating time and increasing its efficiency.


Elastic Tail Propulsion at Low Re
2:15 – 2:50
Rafaela Barros-Barreto, Jennifer Miranti, Yoel Park, Elijah Vidal
Advisor: On Shun Pak
Swimming at the microscopic scale (a low Reynolds number environment) encounters stringent constraints due to the dominance of viscous over inertial forces. We design and develop a dynamically similar, macroscopic low Re swimmer that exploits flexibility to generate propulsion via fluid-structure interactions.

Bi-directional Kerr Lens Mode Locked Ti-Sapphire Laser
2:55 – 3:30
Ricky Arnold, Stratos Koutroulis, Dylan Meyer
Advisors: Drazen Fabris, Bachana Lomsadze
The objective is to provide the Physics Department with a precision laser for the use of optical imaging. Using the Kerr-lens mode-locking behavior, the laser will be able to acquire more accurate wavelength identification and can acquire the data in a vastly accelerated time frame.

Ninja-300 Luggage Rack
3:40 – 4:15
Ethan Gatchalian, Mikel Hirigoyen, Eric Tsuchiya
Advisor: Vlad Ivashyn
Our goal is to design a strong, modular bike rack for the Kawasaki Ninja-300 Motorcycle. There are no true modular racks on the market right now, and the majority of what is there cannot hold all that much weight. We aim to fill this need.
Soft Robotic Locomotion via Mechanical Metamaterials: Application in Pipe Inspections
4:20 – 5:00
John Barr, Andrew Boyle, Matthew Goodfellow, Nicholas Rogers, Caroline Stephens
Advisors: On Shun Pak, Michael Taylor
This project investigates the capabilities of auxetic and conventional metamaterials as a tool for pipe inspections, utilizing their opposing reactions to a controlled displacement. Our work serves as a proof of concept aiming to validate the use of metamaterials as an effective means of locomotion in an enclosed conduit.
GRVLR Rock Crusher
5:05 – 5:40
Samuel Broyles, James Forman, Karla Raigoza, Hailee Silva
Advisor: Gaetano (Tony) Restivo
The GRVLR team seeks to design a manual rock crusher that is more safe, efficient, cost-effective, and ergonomic than hammering river rocks into gravel. Partnered with a non-profit abroad, our goal is to lessen the physical and economic burden of impoverished Nepalese women who make their living crushing rocks.