CEDC Capstone Program 2026

Lola & Rob Salazar Student Wellness Center Friday, May 8, 2026 | 9:00 am -12:30 pm

SCHEDULE OF EVENTS SET UP PROJECTS ON DISPLAY

8 a.m.

9 a.m. – Noon

LUNCH/JUDGES DELIBERATE

Noon – 1:30 p.m.

AWARDS

1:30 – 2:30 p.m.

THANK YOU TO OUR ALUMNI JUDGES TTejveer Singh Bath (Computer Science & Engineering ’24) Jason Brand (Civil Engineering ’10) Ross Cohlmia (Mechanical Engineering ’12) Jackie Duarte (Construction Engineering ’23) Madison Gast (Mechanical Engineering ’22) Braden Giali (Mechanical Engineering ’23) Venkata Stiram Kalaga (Mechanical Engineering ’24) Areeb Khan (Biomedical Engineering ’22) Nabeal Khatib (Civil Engineering ’26) Deacon Joshua Knight (Civil Engineering ’13) John Kuriakose (Computer Science & Engineering ’17) Warren Linn (Mechanical Engineering ’12) Ramon Martinez (Civil Engineering ’10) Michael Millan (Biomedical Engineering ’22)

Oscar Nurmat (Electrical Engineering ’22) Gabriela Ortiz (Biomedical Engineering ’22) Kulprawee Prayoonsuk (Computer Science & Engineering ’21) Raphael Provosty (Mechanical Engineering ’23) Chamali Ranasinghe (Mechanical Engineering ’19) Wendy Schadler (Biomedical Engineering ’22) Shakira Sanders (Mechanical Engineering ’99) Mukhtar Satar (Civil Engineering ’12) Eric Sherman (Civil Engineering ’23) Justin Stiles (Electrical Engineering ’17) Ryan Thomson (Civil Engineering ’23) Antonio Valenzuela (Mechanical Engineering ’23) Jeff Wiencrot (Electrical Engineering ’13) Chase Williamson (Computer Science & Engineering ’23)

SPECIAL THANKS TO OUR INDUSTRY SPONSORS FOR THEIR SUPPORT!

WELCOME TO THE CAPSTONE EXPO! This signature event is one of the highlights of our academic year, an opportunity to celebrate the creativity, ingenuity, and hard work of our students. Today, our Capstone Design teams showcase projects that bring together the knowledge, technical expertise, and problem-solving skills they have developed throughout their time in our programs.

This year’s Expo highlights the breadth and impact of student innovation. Projects such as ZapWrap and ThAIRapy demonstrate advances in healthcare and human-centered design, while DeepTrace and PROOF (Prediction Reference Object-Oriented Framework) reflect the growing role of data and intelligent systems. Multidisciplinary efforts like the Experimental Launch Module (ELMo) and infrastructure-focused work such as Lynx Construction further illustrate how our students are tackling complex, real-world challenges.

We also celebrate our first-year students whose projects are on display. In our college, design is woven throughout the entire educational experience, from their first semester to their final Capstone, our students continuously build and refine the skills needed to turn ideas into solutions.

At its core, engineering is about creating technologies and systems that improve lives and serve society. Few professions combine technical depth with such a direct and meaningful impact on the world around us. The projects presented today reflect not only technical excellence, but also the collaboration, creativity, and empathy that define outstanding engineers.

Events like this are only possible because of the many individuals who support our students and programs. I extend my sincere thanks to the faculty and staff who mentor these teams, the alumni who return to serve as judges and advisors, and the industry and community partners who provide meaningful, real-world design challenges. Your engagement is vital to the success of our students and our college.

To our students: congratulations on the remarkable work you present today and on your upcoming graduation. You represent the future of engineering innovation, and I am proud to welcome you as alumni of the College of Engineering, Design and Computing. I look forward to seeing the impact you will make and to staying connected in the years ahead.

Martin L. Dunn Dean and Professor

BIOMEDICAL ENGINEERING

CapSure

Faculty Advisor: Steve Lammers

Team Members: Alina Pena, Sienna Phipps Sarita, Novotny-Shandas

Helicobacter pylori (H. pylori) is a bacterium that has infected nearly half of the world’s population. The bacterium is largely comprised of the enzyme urease. This urease breaks down urea in the stomach through hydrolysis to produce ammonia, which neutralizes stomach acid and allows the rest of the bacteria to survive. From there, H. pylori adhere to gastric epithelial cells in the lower lining of the stomach triggering a prolonged immune response, secreting toxins that promote further damage to the stomach and ultimately leading to ulcers and gastric cancer.

H. pylori is difficult to detect. Invasive tissue endoscopies are used for diagnosis but for rural regions where H. pylori is more present, access to these tools is limited. In this way, there is a need to develop a minimally invasive and quick method of H. pylori diagnosis for rural populations to allow for early intervention and prevention of serious gastric conditions.

The EnteroTracker, a minimally invasive esophageal string test, has been seen to collect H. pylori through PCR. However, CapSure was created by utilizing the mechanisms of a rapid urease test to accommodate areas without access to laboratory technology. It uses a highly absorbent rayon string and increases the surface area, so there is a larger likelihood of collecting more H. pylori. The string will be swallowed and following retrieval it will be placed in a solution of urea to observe a color change due to an increase in pH if the bacteria is present. This test will allow for a minimally invasive, quick, and low-cost method of H. pylori detection.

POLAR

Faculty Advisor: Steve Lammers

Team Members: Rose Carmack, Mariana Ballard, Chris Roeske, Layla Blair

In extreme cold environments, a preventable injury can quickly become life-altering.

Frostbite occurs when prolonged exposure to low temperatures causes tissue to freeze, often leading to severe damage or amputation if not treated promptly. It is most common among unhoused individuals, outdoor workers, and winter sports participants. Effective treatment requires rapid warming of the affected areas, followed by intravenous (IV) administration of specific medications to improve circulation and reduce the risk of permanent tissue damage or amputation. However, standard IV infusion systems rely on electronic pumps that malfunction or lose accuracy in freezing environments, making them unreliable in remote or emergency settings.

This project presents the design of a manually powered IV infusion system intended for use in sub-freezing conditions. The system uses a hand-operated pump to pressurize the IV bag, maintaining a pressure of at least 2 psi to enable consistent fluid delivery without electricity. A flow regulator allows for controlled infusion rates between 10-20 mL/hr with a target accuracy of ±10%.

To ensure proper drug delivery, the IV fluid is stored in a vacuum-insulated container with a chemical heat pack, maintaining an internal temperature range of 15–30°C. Doubleinsulating the tubing further reduces heat loss as the fluid travels to the patient. The system is compact, portable, and designed for ease of use in field conditions.

By combining mechanical simplicity with thermal protection, this design provides a reliable alternative to traditional IV systems, enabling effective frostbite treatment in environments where current technologies are limited.

CathMatch

Faculty Advisor: Steve Lammers

Team Members: Caden Baugus, Annie Dinh, Brooke Hagan, Saron Solomon

Establishing intravenous (IV) access is one of the most common procedures in healthcare, yet it can be especially challenging in pediatric patients with small or difficult-to-visualize veins.

Even using an ultrasound-guided process, clinicians often estimate vein diameter visually and select catheter size based on experience. This process can introduce variability and may lead to multiple insertion attempts, shorter catheter lifespan, and increased patient discomfort.

To address this problem, our team developed CathMatch, a simple, low-cost handheld device that allows clinicians to hold a calibrated transparent sizing guide up to the ultrasound screen and quickly match vein diameter to an appropriate catheter gauge. By providing a visual reference based on recommended catheter-to-vein ratios (guidelines used to reduce vein damage and catheter failure), the device reduces reliance on estimation and supports more consistent catheter selection during real-time scanning.

The design process was guided by extensive clinical engagement. Over eight months, the team conducted more than twenty hospital visits to Children’s Hospital Colorado. During these visits, the team observed ultrasound-guided IV procedures, shadowed clinicians, and gathered direct user feedback. Multiple prototype concepts were developed and refined based on this feedback to ensure the device is portable, intuitive to use, compatible with common ultrasound systems, and practical to sanitize in clinical environments.

While CathMatch may appear simple, it represents a carefully engineered solution grounded in clinical workflow and user-centered design. By standardizing catheter selection without adding complexity to the procedure, the device has the potential to improve efficiency, reduce failed insertion attempts, and enhance patient comfort during vascular access procedures.

Twistomy

Faculty Advisor: Steve Lammers

Team Members: Sydney Vonesh, Kristeen Cai, Nicholas Austin, Zahra Alli

Ostomy procedures, including ileostomies and colostomies, are life-saving surgical interventions for patients with colorectal cancer, inflammatory bowel disease, or congenital abnormalities. Despite their clinical importance, current ostomy care relies primarily on external wafer and pouch systems that commonly cause leakage, skin irritation, odor, reduced discretion, and decreased quality of life.

With approximately 725,000-1,000,000 individuals living with an ostomy in the United States, there remains a significant unmet need for a continent ostomy solution that allows controlled bowel evacuation without continuous reliance on an external pouch. The Twistomy device addresses the gap using a twistable conduit that functions as an artificial sphincter to regulate fecal flow.

The device integrates with a standard ostomy wafer and uses concentric rings surrounding a flexible conduit positioned within the bowel lumen. Rotating the outer annulus twists the conduit closed, creating an airtight seal that restores continence and enables patients to perform daily activities without leakage or odor. To evacuate waste, the user attaches a standard pouch and untwists the conduit, allowing controlled passage of fecal matter directly into the bag.

A key design challenge is regulating pressure exerted on the bowel wall during closure.

Excessive pressure may cause ischemia, while insufficient pressure risks leakage. Twistomy incorporates a ratchet-based force-limited mechanism combined with a compressive material that maintains consistent axial force. The device operates within a calculated safe force range, ensuring sealing without tissue damage.

RATional Motion

Faculty Advisor: Steve Lammers

Team Members: Anthony Sawaged, Lluvia Mejia Tovar, Raseel Zmily

Achilles tendon injuries are among the most common and debilitating musculoskeletal conditions, often resulting in impaired mobility, prolonged rehabilitation, and reduced quality of life. Despite their high incidence, the biological mechanisms underlying tendon healing remain poorly understood. A key limitation in advancing this understanding is the lack of reliable, quantitative tools to assess functional recovery throughout the healing process. In both preclinical and clinical research, ankle range of motion (ROM) and joint stiffness serve as critical indicators of tendon integrity and overall limb function. ROM is the angular range through which the ankle moves, while stiffness is its resistance to angular rotation. Current assessment methods, including manual goniometers, imaging techniques, and qualitative observation, are often limited by poor precision, low reproducibility, and weak correlation with functional outcomes, hindering meaningful evaluation of tendon healing.

The RATional Motion project addresses this need by developing an automated, low-cost benchtop device that measures ankle biomechanics in rat models, which are widely used due to their anatomical similarity to human tendons. The device secures the hindlimb in a controlled position and applies a known rotational torque to the ankle while recording the resulting motion. This enables the real-time generation of a torque-angular displacement curve within a graphical user interface (GUI), from which ROM and stiffness values can be extracted for easier visualization and analysis.

By providing accurate, repeatable, and objective measurements, this system improves the consistency and reliability of preclinical tendon research. Ultimately, the RATional Motion device offers a practical tool for evaluating tendon healing, with the potential to support more effective treatment strategies and improve the translation of research findings to clinical care.

Zapwrap

Faculty Advisor: Steve Lammers

Team Members: Shifa Lakhani, Clarissa Chinchilla

Advancing neurological monitoring beyond the clinic requires systems that are both technically robust and seamlessly wearable. This project presents the design and development of a compact EEG platform capable of continuous, real-time brain activity monitoring in natural environments. The device is intended to provide reliable, low-noise signal acquisition while prioritizing user comfort, mobility, and ease of use, making it suitable for long-term monitoring applications such as seizure tracking.

The system integrates a three-electrode configuration with a high-gain, low-noise bioamplifier and analog filtering stages to ensure high signal fidelity in non-controlled settings. Data acquisition is paired with a wireless microcontroller platform, enabling Bluetooth-based transmission to a custom software interface for real-time visualization and storage. An eventmarking feature allows users to log subjective experiences, facilitating temporal alignment between reported symptoms and recorded EEG signals.

Significant emphasis has been placed on the physical design, including a lightweight, ergonomic enclosure that supports extended wear without compromising electrode stability or signal quality.

The current prototype incorporates onboard battery power and local data buffering, advancing the system toward fully portable operation.

In parallel, collected EEG data is being used to explore preliminary signal classification methods for distinguishing normal and abnormal neural activity. This establishes a foundation for future implementation of automated event detection algorithms. Overall, the project represents a transition from benchtop circuitry to an integrated, user-centered wearable system, with ongoing validation focused on performance, comfort, and reliability in real-world conditions.

ELECTRICAL ENGINEERING

AI Arcade

Faculty Advisor: Kyle Mize

Team Members: Gray Carstens, Kelsey Tran, Ben Johnson, Danae Castaneda Villa, Almutsaem Dhaou, Andre Arellano, Boonyarit Seemung, Naser Aldousari, Mohammed Alsaei

The CU Denver AI Arcade is a systems engineering project that gives the general public an opportunity to collaborate with generative AI in a process to create a unique creative digital object. Through the process of playing a series of retro arcade games, the user is unknowingly tailoring a custom AI experience with each game they play.

Based on their input from each game, a generative AI model creates a unique set of questions per-user. After answering the questions, the AI generates a custom Pokémonthemed card based on their input, paired with a mystical one-line-prophecy. This project showcases the design skills of both mechanical and electrical engineering students, coming together to create a one-of-a-kind experience at the Senior Design Expo.

RAVEN DRONE

Faculty Advisor: Kyle Mize

Team Members: Tara Ghaeli, Joel Nunez, Ryan Meeker, Ali Alrumaih, Gabriel Elftman-Hanson, Andrew Mincey, Benjamin Hunter, Kameren Kelly

The Retrofitted Airframe with Virtualized Edge Nodes(RAVEN) project, sponsored by BAE Systems, aims to improve the modular capabilities of first responder drones by containerizing multiple computer vision models to change tasks based on the situation needed. This process combines Docker. Ultralytics, and the high-performance GPU of a Nvidia Jetson Orin Nano, to create trained spacious containers for the detection of fires, vehicles, and personnel from an aerial view. This interdisciplinary project combined the skills of mechanical, electrical, and software engineering to create a system that responds seamlessly over far distances.

The mechanical portion of this project included designing an enclosure for the single-board computer/cameras, analyzing performance under thermal loads, and accessing mounting points to maintain optimal flight control. The electrical portion of this project includes creating converters for seamless component connection and creating a power budget to ensure electrical loads will be met at desired levels. The software portion of this project included training computer vision models, creating wireless links for transmitting data over long distances, and creating localized containers for all processes to run independently.

These components integrate into a modular drone with real-time processing to meet first responder needs.

Very Small Array

Faculty Advisor: Kyle Mize

Team Members: Ilayca Kalkandelen, Steven Salinas, Kai Borie, Alex Sandersfeld, Gabriel Kelly-Ramirez

Evaluating whether deployments of new connectivity technologies such as 5G cellular might impact existing communications links can be difficult due to environmental conditions which aren’t easily modeled until measured on-location. Thus there is a need to measure the actual received cumulative radio spectrum in areas where existing infrastructure might be impacted. The measurement equipment that would do so must have the same radio reception characteristics as existing systems. With a wide variety of operational equipment installed in diverse and often austere locations, that equipment must also be flexible, resilient, and offer capability for future expansion.

While equipment with some of these capabilities exist already, we seek to build a recording system to gather data for the modeling of cellular frequency spectrum usage that is flexible and easily re-configurable. Our solution is to design a distributed, precisely time-synchronized network of software-defined radio (SDR) receiver nodes, collectively able to act as a combined receiving antenna array. This array will be able to capture live radio emissions in the 3.7 to 3.98 GHz band used in both 5G cellular networks and pointto-point communications infrastructure. Data from each receiver node will be aggregated on-site within the system to be made available for offline retrieval and post-processing.

Output data from this system can then be used to assist existing statistical models of spectrum usage, helping industry and regulatory agencies with future radio spectrum planning and analysis.

The C.O.R.E. Jet

Faculty Advisor: Kyle Mize

Team Members: Matthew Mata, Liam Gonzalez, Jacquie Sammel, Payton Kallaher, Derek Knauf, Daniel Uribe, Anthony Giattini

The C.O.R.E. Jet is a DMX-controlled, beat-responsive CO₂ effects jet developed by a multidisciplinary team of mechanical and electrical engineering students at the University of Colorado Denver. Designed for the live entertainment and event production market, the system addresses a key limitation of commercial CO₂ jets: while existing units fire statically, the C.O.R.E. Jet adds programmable angular oscillation and beat-driven triggering, tightening the synchronization between the visual effect and the music being performed.

The system integrates four core subsystems. A stepper-driven three-bar linkage (redesigned from an original four-bar concept) sweeps the nozzle through 100° of motion, powered by a NEMA 23 motor paired with a 50:1 planetary gearbox delivering approximately 48 N·m of effective output torque. Industry-standard flexible CO₂ hose rated to 2,500 psi handles gas delivery, gated by a normally-closed solenoid valve. A Teensy 4.1 microcontroller decodes DMX-512 frames from a standard lighting board, mapping eight channels to RGB lighting, motor direction/speed, solenoid mode, fire trigger, and emergency cutoff. An ESP32 runs an audio-driven BPM detection algorithm — sampling the venue's audio feed, applying an IIR envelope filter and adaptive threshold to isolate beat events, then generating a synchronized pulse train that triggers the solenoid on-beat.

Finite element analysis across five oscillation positions returned a minimum factor of safety of 10× under a 100 N nozzle load, well above the 2.5× target. The team reached full-system integration at week 10–11 of the 16-week semester, with the final demonstration proceeding as an integrated-system showcase.

HYDRA - Liquid Antenna Team

Faculty Advisor: Kyle Mize

Team Members: Nicholas Nowak, Joe Cosner, Rachel Lee, Landon Kohler, Andrew Johnson, Nikola Hilderbrand

Next generation communication systems require antennas that are more adaptable, compact, and frequency agile than traditional designs. This research investigates liquid antennas as an alternative to rigid metallic structures, focusing on their ability to dynamically reconfigure and tune electromagnetic performance.

By utilizing a conductive liquid medium, the antenna can alter its effective geometry, enabling operation across multiple frequency bands without the need for separate fixed designs or utilizing a wide band approach. This work explores the potential of liquid based antenna technology to improve flexibility and efficiency in RF systems, with the goal of supporting more versatile and adaptive communication platforms in future applications.

Isotrol

Faculty Advisor: Kyle Mize

Team Members: Lonnie Gambrell-Potts, Emmanuel Beka, Lucas Valle

The Isotrol project consists of a small scale microgrid that powers a 120 Vac bus with three AC loads. This happens through grid energy when available, but also counts on a battery management system and solar energy backup. Solar energy - or the available AC grid when there is no sun - charges the battery system. The battery charging and discharging is controlled by a microcontroller that chooses optimal times of operation. The control of the whole plant is centered in a model control room with mechanical relays controlling the physical connections of the system.

These relays are operated by microcontrollers that contains the operation logic. The plant counts with full telemetry, displaying data and controls via WiFi to a dashboard that can be controlled via phone app or computer.

MECHANICAL ENGINEERING

Herban Warfare

Faculty Advisor: Ron Rorrer

Team Members: Adam Cate , Breanna Herrera, Cameron Bain-Faus, Cash Stephens , Ethan Le

This project presents the design and development of an autonomous weed-removal robot, “Herbie,” intended for use in residential backyard environments. With approximately 80% of U.S. homes maintaining lawns and a significant portion of homeowners seeking convenient maintenance solutions, this system addresses a growing demand for efficient, low-effort lawn care. Herbie integrates mechanical design, embedded systems, and computer vision to identify and neutralize weeds with minimal user intervention.

The robot utilizes a Raspberry Pi-based vision system paired with an onboard AI camera to detect and classify weeds in real time. A Teensy microcontroller coordinates mobility and actuation, controlling dual drive motors and a targeted spraying mechanism. The system is powered by a rechargeable battery pack designed to balance runtime, weight, and cost efficiency. Mobility improvements, including optimized wheel selection and traction analysis, ensure reliable performance on uneven grass terrain. Testing demonstrated motion capabilities on slopes up to 25 degrees at a top speed of approximately 0.28 m/s, while the AI detection model classifies weeds consistently with 85% accuracy and above.

Overall, this project demonstrates a practical, scalable solution that combines automation and precision agriculture principles to modernize residential lawn care.

International Sustainability

Faculty Advisor: Ron Rorrer

Team Members: Annahlese Wise, Jeremy Crocker

Organizations are increasingly seeking to reduce carbon emissions and energy use in aging university facilities without sacrificing performance. This project evaluated sustainability opportunities at University of Colorado, Colorado Springs (UCCS), Colorado College (CC), and Białystok Technical University (BUT).

Rather than developing comprehensive recommendations for each campus, detailed analysis of the Osborne and Worner Centers was used to develop a software tool to create a scalable framework that could be used across buildings and campuses for practical, economically viable campus improvements.

An audit of existing facilities was completed to identify possible sustainability measures. To reduce the amount of repeated manual calculations when comparing diverse solutions, a generalized software tool that allows campus planners to efficiently estimate energy savings and financial payback periods was developed. This tool was used to prioritize interventions that yield a return on investment in under 15 years, encompassing mechanical systems as well as landscaping modifications such as trees for wind barriers and native plants to reduce water demand.

The analysis of lighting retrofits at the Osborne Center showed savings of 14,500 kWh annually while the Worner Center achieved 126,500 kWh in savings with both buildings having a 20 -year payback.

Regarding photovoltaic solar installation, the Osborne Center is estimated to save 886,226 kWh, with the Worner Center saving 175425 kWh, both with 14 paybacks. Finally, ventilation occupancy setbacks resulted in 51,000 kWh of savings for the Osborne Center laboratories with a 0-year payback, while the Worner Center kitchen ventilation reached 770,414 kWh in savings with a 3-year payback period.

The final deliverable is a scalable framework and a generalized software tool that empowers campus planners to move beyond manual calculations. The final recommendations ensure that institutions can prioritize projects that are both environmentally impactful and economically viable.

Maj-J

Faculty Advisor: Ron Rorrer

Team Members: Anna Fortier, Jordan Gammel, Magnus Weicht, Jesse Romero

This project investigates the feasibility of fabricating a functional electric commuter bike as a home engineering project using common 3D printing materials for structural components, shown and listed in green in Figure 1 and Table 1. Force analysis, finite element analysis with a factor of safety of 2.6, material research and part-representative testing, and topology optimization were employed to evaluate PLA, PETG, and ABS in a motorcycle application.

Topology optimization reduced part masses by up to 21% while 40% triangle infill decreased print time and material usage by an additional 50%, contributing to the target bike weight under 100 lb. Experimental material testing results showed 35-54% increases in tensile strength and up to 77% increase in toughness when parts were printed on their side. PETG was selected for its ductility and impact resistance, and carbon fiber reinforcement provided an elastic modulus increase from 0.30 to 2.45 GPa, enabling better withstanding of dynamic loading and fatigue.

CIVIL ENGINEERING & CONSTRUCTION

Building Bridges and Beyond

Faculty Advisor: Peter Marxhausen

Team Members: Jesus Gonzalez Robles, Mosa Farmer, Keidyfer Leon, Mason Petsch, Vivian Hua

The National Student Steel Bridge Competition (SSBC) challenges student teams to design and fabricate a one-tenth-scale steel bridge. Annual contest rules reflect structural specifications and construction regulations. Students practice structural design/analysis and project management, as well as learn fabrication techniques and gain an appreciation for the strength and constructability of steel. NSSBC is sponsored by the American Institute of Steel Construction (AISC) and the American Society of Civil Engineers (ASCE).

The company of “Building Bridges & Beyond” has been invited to compete in this competition by submitting a 1:10 scale model of a code-compliant, efficient, and constructible steel bridge design that satisfies the given constraints within the competition rules. The new bridge must be designed to support the weight of the pedestrians using it, as well as the maintenance and emergency vehicles that may occasionally need to access it. The 1:10 scale models entail specific design constraints such as structural material cost, construction cost, clearance requirements, bridge height, aesthetics, and sustainability.

The bridge is to be erected under simulated field conditions considering member sizes and quantities, span limitations, height restrictions, and environmental protection requirements.

Engineers associated with the project will judge the competition and will award the design/ build contract to the company whose model satisfies the specified requirements and best achieves the project objectives.

Transit Flow

Faculty Advisor: Peter Marxhausen

Team Members: Hussain M A S Abdullah, Awrad Al Sarraf, Ali Alfaraj, Huda Alfayadh, Edlyn Nevarez, Abdulla Mohammad

Rock Canyon High School, with over 2,300 students, shares its location with Rocky Heights Middle School, which has over 1,100 students, at the southwest corner of the McArthur Ranch Road and Quebec Street/Monarch Boulevard intersection in Highlands Ranch. Douglas County (County) manages four signalized intersections around the campus, while the Douglas County School District (DCSD) oversees traffic and parking on its property. Student parking demand exceeds the available spaces on school grounds, leading to overflow into nearby neighborhoods.

The County would like the internal circulation and parking layout at Rock Canyon High School evaluated for improvements. Any opportunities to increase parking capacity should be explored within the existing paved areas or on the vacant lot northeast of the school. In addition to the internal analysis, the signalized intersections around the campus need to be evaluated for potential optimization.

The County will provide traffic volume and crash data, existing traffic signal timing plans, historical documents (e.g., as-builts, drainage report, and traffic impact analysis), aerial imagery, Douglas County design criteria and specifications, and a source for estimating costs. The County will facilitate a meeting with relevant stakeholders and a guided site visit. Follow-up site visits are encouraged but must be coordinated before entering Rock Canyon High School property.

The Constantia

Faculty Advisor: Peter Marxhausen

Team Members: Mahdi Alattar, Mohammed Aljedi, Ali Alhabshy, Abdulaziz, Zamira Chavez, Hamad Boodai

Constructed during the building and early operation of the Moffat Tunnel, the East Portal Camp Cabins provided housing for workers and maintenance staff in a remote alpine environment. Today, only five cabins remain, representing a rare surviving example of early twentieth-century support housing in Colorado. The buildings show age-related deterioration, deferred maintenance, harsh climate exposure, and limited documentation. The cabins also face significant winter snow loads that can overstress already-weakened roof framing.

This project will provide engineering documentation and stabilization planning for the five remaining cabins: the Master Mechanic’s home (Building 1577), Commissary Manager’s home (1574), Paymaster’s home (1573), Assistant Superintendent’s home (1576), and Superintendent’s home (1575).

Students will prepare measured drawings and condition documentation focused on structural systems, foundations, the exterior envelope, and active deterioration. Using historic research and field observation, the team will reconstruct the original structural intent and compare it to current performance. Concept-level evaluations will identify deformation, settlement, load-path discontinuities, moisture-related distress, and material degradation. Stabilization concepts will emphasize minimum intervention, reversibility, retention of historic character, and life-safety awareness.

The final outcome will be a prioritized stabilization and preservation strategy, including drawings, recommendations, and order-of-magnitude cost estimates to inform grant applications and stewardship planning. Stabilization is critical because structural collapse results in irreversible loss of historic material; once a roof fails, recovery efforts shift from preservation to documentation of remains. This work balances historic sensitivity with modern engineering ethics, ensuring the East Portal Camp Cabins endure as tangible evidence of the Moffat Tunnel construction era.

SC Risk Reduction

Faculty Advisor: Peter Marxhausen

Team Members: Login Alali, Ahmed Alazemi, Hams Albuloushi, Hailie Connell, Warsame Egal

Second Creek is a major drainage way in Commerce City that is expected to experience increased flood risk under future land use and master-planned flow conditions. The project reach extends approximately 1.6 miles from Chambers Road at the upstream end to the Burlington Northern Santa Fe Railroad (BNSF) corridor and Interstate 76 at the downstream end. Existing conveyance deficiencies, an inefficient irrigation canal alignment, and planned roadway and development expansions create system-level challenges that must be addressed holistically.

The purpose of this project is to develop conceptual flood risk reduction improvements for Second Creek that improve conveyance, support future infrastructure expansion, and integrate with adjacent public open space. Key components include natural stream design for the full reach using future master-planned flows, realignment and redesign of the O’Brian Canal to support an extension of East 112th Avenue, conceptual design of a roadway bridge crossing sized for extreme flood events, and evaluation of an in-line detention feature upstream of the existing canal crossing to reduce downstream flood impacts. Opportunities to integrate flood infrastructure with Second Creek Park should also be identified.

This is a forward-looking, conceptual-level project focused on systems thinking, engineering judgment, and effective communication. Students will develop and recommend a preferred solution that balances flood risk reduction, infrastructure needs, public safety, and long-term functionality.

Lynx Builders

Faculty Advisor: Peter Marxhausen

Team Members: Ana Montenegro, Damaris Rojas, Saleh Almusallam, Nasser Aledilah, Hussain Altamimi, Ayantu Yemane

For our Food Forest Project, our team was tasked with laying out a path and designing a pavilion inside of a garden owned by the Elyria Swansea Coalition. We also removed and relocated a section of their fence and replaced it with a gate. Our team includes 3 students from the construction management department and 3 from the civil engineering department.

Part of the scope included planning, scheduling and creating a cost estimate for the work of the fence and path. In the case of designing the pavilion, we used the Revit software to then prepare a blueprint and a cost estimate for the future team who will be tasked with building it. This included the foundation plan, framing plan, materials, and all the detailed specifications that made up the structure.

Value engineering was a key part of the process of this entire project given that we were working with a slim budget. Another important deliverable was our Master plan which included all of the components of our project and a deeper look into the coalition and their vision for the future of the garden. We were able to successfully complete our project with the support of GH Phipps, volunteers, and our professor Heidi Brothers and Peter Marxhausen. And a special thanks to our mentor Jackie Duarte.

Lynx Construction

Faculty Advisor: Heidi Brothers

Team Members: Jose J Gonzalez Vidal, James Holland, Natalia Perez Martinez

This senior capstone project represents a full preconstruction and planning effort based on a real world style wastewater treatment facility in a coastal and highly constrained environment.

Our team, Lynx Construction, put together a complete proposal by applying what we have learned in class along with what we have seen in the field. The project pushed us to think through environmental impacts, geotechnical conditions, site logistics, safety, scheduling, estimating, and overall coordination across different parts of the job.

Our approach focused on planning early and making sure everything we proposed could actually be built under the given conditions. A big part of our work was developing a logistics plan for a site with limited access, along with building a schedule that made sense and kept the project moving efficiently.

Safety was a major focus throughout, especially considering the type of work and the conditions on site. We relied heavily on our real world experience and classroom knowledge to guide decisions, and we also used input from industry professionals to better understand how these challenges would be handled on an actual project.

Cost estimating and value decisions played a big role in shaping our final approach. We looked at different options and chose solutions that made sense from both a cost and constructability standpoint. Overall, this project shows how we take what we have learned and apply it to a realistic construction problem. It reflects our ability to work as a team, think through challenges, and put together a plan that is practical and well thought out.

ASC Competition Mixed Use / Concrete Teams

Faculty Advisor: Heidi Brothers

Team Members: Mario Herrera, Leslie Burciaga, Nicholas Williams

The Associated Schools of Construction Regions 6 and 7 Student Competition is an annual event that brings together university teams from across the Rocky Mountain and Far West regions to compete on real-world construction problems under industry conditions. The 39th edition of the competition was held February 4 through February 7, 2026, at the Nugget Casino Resort in Sparks, Nevada. The University of Colorado Denver fielded two teams as part of the CEMT 4067 Senior Capstone course: a Mixed Use team sponsored by Layton Construction, and a Concrete Solutions team sponsored by Sundt Construction.

The Mixed Use team -(led by Mario Herrera) was tasked with acting as an internal project team for Layton Construction, responding to a multi-stage IRFP for a development encompassing residential, amenity and retail components. The Concrete Solutions team (led

by Leslie Burciaga) was required to act as self-performing contractors for Sundt, tackling a student housing project at Cal Poly Humboldt with significant site challenges including high annual rainfall, limited local labor, and difficult operating conditions. Both teams had approximately 14 to 16 hours to develop and submit full proposal packages covering areas such as estimating, scheduling, quantity takeoffs, site logistics, safety planning, and vendor selection, before presenting to panels of industry professionals in live interviews.

The CU Denver Mixed Use team earned second place in the regional competition; the first podium finish for the school in this competition problem. Preparation for both teams began in the fall semester, with time spent reviewing prior year materials, assigning internal project roles, and sharpening deliverable skills alongside industry coaches. This capstone report reflects on how both teams prepared, the decisions they made under competition conditions, and what the experience revealed about applying construction management knowledge when the stakes are real.

COMPUTER SCIENCE & CYBERSECURITY

ComSa

Faculty Advisor: Salim Lakhani

Team Members: Lisa Cho, Paul Kim, Kyungju Moon, Sybil Raphael

In dense urban environments, drivers often waste significant time and fuel circling for parking, contributing to traffic congestion and increased emissions. Foresight is a smart parking assistance app designed to reduce this inefficiency by providing real-time and predictive parking availability using computer vision and machine learning.

Rather than relying on expensive IoT sensors, Foresight leverages camera-based infrastructure from parking garages, lots, and public street cameras to detect and analyze parking occupancy at scale. Foresight employs advanced computer vision models to identify and segment vehicles from live or periodically updated camera feeds. These detections are combined with historical parking transactions, weather conditions, traffic patterns, and public event data to train predictive models such as ARIMA, LSTM, clustering algorithms, and anomaly detection techniques.

This hybrid approach enables both accurate real-time availability updates and short-term forecasts of parking demand. A dual-database system distinguishes between paid and unpaid vehicles through license plate recognition, enabling automated enforcement insights and reducing operational overhead for parking operators. The results are delivered through an intuitive cross-platform mobile application that guides users to optimal parking locations based on estimated arrival time, occupancy levels, and proximity to their destination.

Visual tools such as heatmaps and predictive maps further support both drivers and city planners in understanding parking trends and high-demand areas. Foresight will be evaluated through real-world testing by measuring reductions in average parking search time before and after application use. By combining scalable camera-based sensing with datadriven prediction, Foresight aims to improve urban mobility, reduce congestion, and transform the parking experience for modern cities.

Clara

Faculty Advisor: David Ogle

Team Members: Todd Cresswell, Marlon Williams, Joseph Milliken, Abigail Easterly

CLARA is an AI-assisted pathology support system designed to help detect colorectal cancer earlier, especially in younger adults where cases have been increasing. As colorectal cancer becomes a leading cause of cancer-related death in people under 50, early and accurate diagnosis is more important than ever. At the same time, pathologists often manage heavy workloads, and subtle abnormalities in gastrointestinal polyp slides can be difficult to catch during an initial review. CLARA helps address this challenge by acting as a reliable second set of eyes.

Using machine learning–based image analysis, it carefully reviews biopsy slide images and highlights areas that may need closer attention. This added support strengthens the pathologist’s assessment and builds confidence earlier in the diagnostic process, reducing the chances of missed findings.

Importantly, CLARA is not meant to replace human expertise. The pathologist remains fully in control of all final decisions. Instead, the system works alongside clinicians, enhancing their capabilities within a secure and efficient workflow. By reducing the need for repeat reviews and helping prioritize critical cases, CLARA can streamline the diagnostic process.

Overall, CLARA has the potential to shorten the time to treatment, lower healthcare costs, and improve patient outcomes, especially during the early, most treatable stages of colorectal cancer.

Black Synapse

Faculty Advisor: Salim Lakhani

Team Members: Elyas Larfi, Ridwan Mohamud, Christian Mandujano Borjas

Knowledge workers and students increasingly struggle with "context-switching" fatigue as they navigate disconnected digital tools like email, calendars, and personal notes. While existing voice assistants provide basic utility, they often lack the deep personalization, long-term memory, and emotional intelligence required to be truly effective productivity partners.

Furthermore, current productivity automation software typically lacks a physical presence, limiting user interaction to desktop applications. Black Synapse addresses this gap by introducing an affordable, desk-based robot that serves as a proactive, embodied AI assistant.

The system is powered by a Large Language Model (LLM) integrated with a RetrievalAugmented Generation (RAG) pipeline, enabling it to access a local vector database for long-term memory storage. This architecture allows the assistant to maintain contextual awareness of a user’s specific role, projects, and personal preferences. Built on a Jetson AGX platform, the hardware features a 3D-printed embodiment with a screen for facial expressions, a monochrome camera for perception, and a robotic arm with multiple degrees of freedom for physical interaction.

Functionally, Black Synapse utilizes speech-emotion classification to adapt its responses and visual "eyes" to the user's mood. Through specialized tool-calling capabilities, it can manage calendars, draft emails, and interact with Notion databases autonomously. By bridging the gap between digital automation and robotic embodiment, this project demonstrates a future where AI assistants act not just as reactive tools, but as proactive, emotionally aware companions integrated into the physical workspace

Scheduler App

Faculty Advisor: Ashis Biswas

Team Members: Chau Nguyen, Paul Nguyen, Khasar Munkh-Erdene, Hossein Mohammadi

Our project is a mobile productivity app designed to make personal growth feel more engaging, smooth, and structured instead of overwhelming. The idea behind our project is simple: people struggle to stay consistent with their goals because planning and scheduling becomes a hassle. Our app’s purpose is to help users turn their goals into manageable “quests” and then generates a weekly schedule that adapts to their availability and priorities.

Our application is built using Expo and React Native for the frontend, with a Node.js and Express backend connected to MongoDB for data storage. Users can create goals by setting time commitments, deadlines, and preferred times to work on them. The system then uses a contextual bandit algorithm (LinUCB) to recommend how those goals should be distributed throughout the week.

Instead of using static scheduling rules, the algorithm adjusts recommendations over time based on what the user actually completes, helping the schedule become more personalized and realistic.

The app includes light gamification elements such as XP and levels to encourage consistency and engagement, but the primary focus of this project is the intelligent scheduling and adaptive learning.

Users can view their tasks in a timeline interface, complete quests, and track their progress across different areas of life like academics, fitness, and work. The system also prevents scheduling conflicts and distinguishes between user-created and automatically generated time blocks.

Overall, our application helps users move from intention to action. Instead of facing a blank calendar and an overwhelming to-do list, users can easily create and receive a clear, adaptive plan that supports steady progress toward meaningful goals.

Medtronic Complaint Process Software for Trending & Analysis

Faculty Advisor: Debra Parcheta

Team Members: Oluwatosin Omiteru, Marwa Abassi, Jacob Lord, Ashley Vo

Medical device companies are required by the U.S. Food and Drug Administration (FDA) and other regulatory agencies to track and analyze product complaints to identify possible issues. Detecting these problems early helps companies investigate, fix the issue, and reduce the risk of further complaints or harm to patients. At Medtronic Acute Care & Monitoring, this process is currently done manually using Excel and PowerPoint, which is time-consuming and can lead to errors or inconsistencies.

This project aims to create an automated system that takes a five-year Excel file of complaint data and generates monthly PowerPoint reports. The system will produce rolling 12-month trends of complaints by product and product family, while separating reportable and non-reportable events. It will also calculate key statistics such as mean, median, mode, standard deviation, and upper control limits to help identify unusual patterns. In addition, the tool will generate Pareto charts to highlight the most common causes of complaints, including report codes, findings, hospitals, and countries.

The system will also track injury-related complaints and group them by severity, such as minor injury, major injury, serious injury, and death. A simple user interface will allow users to remove certain outliers from statistical calculations when needed, while still showing them in the graphs.

Overall, this project will make the complaint trending process faster, more accurate, and easier to use through automation.

Brady Public Humanities Archive

Faculty Advisor: Debra Parcheta

Team Members: Saif Sarsour, Hanna Aamir, Echo Trimble

Brady Public Humanities Archive is a public database for placemaking projects all around the world, designed to bring community improvements to light. Placemaking is communityfocused, community-driven approach to urban development. Projects such as these are important to build communities, and thus are driven by engagement and public knowledge.

Anyone can contribute to the database, and anyone can read its entries, ensuring that those who wish to contribute have a strong ground from which to begin.

Additionally, one can also use the website to plan trips and design lesson plans, passing the knowledge and the means to support the community ahead to others. The project boasts a sophisticated project submission system, and in order to ease the user's project submission process, we've added a specialized AI Agent to assist. Their name is Brai!

Built on an intelligent language model, Brai can search the web for any project title that the user inputs, returning with a description that's elegant and informative. What's more, if the user wants to improve it, then they can give a bit of feedback, such as "make it more informal," for instance, and Brai will take that into account, generating a new description that meets the user's needs. Once this description is generated, the user can move on to other important details, such as the project's sponsor and organizers, having avoided getting stuck on that bit of more interpretive writing. Brady Humanities is an archive. An archive is a promise - that no community ever fades.

Cornerstone Geologic

Faculty Advisor: Debra Parcheta

Team Members: Sunil Gupta, Paul Valdivia, Aanchal Acharya, Adam Vanbaelinghem

Cornerstone GEOLogic is a full-stack web application designed for hydraulic fracturing and petroleum engineering teams to transform raw well and completion data into actionable, data-driven insights.

The platform streamlines the most time-consuming stages of analysis—including data ingestion, cleaning, validation, storage, and statistical exploration—allowing users to focus on interpreting results and making informed operational decisions. Users can upload CSV or Excel datasets through a guided interface that performs automated formatting checks, required-field validation, and data-cleaning routines before storing validated records in a MySQL database for reliable querying and reuse.

Cornerstone GEOLogic then provides interactive analytics and visualizations to identify key drivers of well performance and compare outcomes across variables and time periods. The system supports variable relationship exploration through scatterplots and time-series charts, along with advanced multivariate techniques such as correlation analysis, multiple regression (including Lasso), Random Forest regression, and K-means clustering for segmentation. A MANOVA-based workflow is also included to evaluate the impact of categorical variables using effect-size reporting and post-hoc comparisons.

To support real-world workflows, the application tracks analysis history, enables exporting results for reporting, and includes a dashboard with system alerts and contextual market indicators such as crude oil and natural gas prices. The backend is built with FastAPI and the frontend with React/Vite, providing a responsive, secure, and scalable foundation for future development.

GLAAS - Geological Laboratory Analytical Archive System

Faculty Advisor: Debra Parcheta

Team Members: Killian Bertsch, Carlos Cortes Garcia, Ian Keitlen, Matthew Kenner

GLAAS — the Geological Laboratory Analytical Archive System — is an open-source, web-based Laboratory Information Management System (LIMS) designed to modernize sample data management for tephrochronology research laboratories. Developed in partnership with Dr. Stephen Kuehn's research group, GLAAS replaces fragmented, spreadsheet-driven workflows with a unified, rolebased platform that supports the complete sample lifecycle from field collection through analytical reporting and archival.

The system supports six physical collection types — Core, Cutting, Dredge, Grab, Hole, and Other — with structured data entry, bulk import via type-specific Excel templates, and multi-format export across all collection types. A hierarchical GLAAS ID system automatically generates human-readable, traceable identifiers for every entity in the system, including projects, station sites, strata, samples, subsamples, and analytical records. Role-based access control governs all data operations across four user classes, from read-only external collaborators to project owners and system administrators.

GLAAS provides full workflow support for three industry-standard tephra analysis pipelines — Physical Analysis, Physical Microanalysis, and Geochemical Analysis — spanning eighteen distinct analysis branches with support for manual entry, import, export, and inline editing. Additional capabilities include project and grant management, contributor tracking with ORCID integration, station site and stratigraphic hierarchy, subsample lineage tracking with inventory management, and sample disbursement recording.

Built on Django and PostgreSQL and containerized with Docker, GLAAS is designed as an extensible, open-source platform for adoption across geological research laboratories. The system is completing final integration testing ahead of its demonstration at the 2026 European Geosciences Union General Assembly in Vienna, Austria.

GEORISKMOD

Faculty Advisor: Debra Parcheta

Team Members: Mustafa Azam, Andy Dang, Hai Phan, David Spacek

The GEORISKMOD Borromean Risk Assessment Tool is a geospatial platform designed to evaluate natural hazard risk, particularly events like landslides, debris flows, and rockfalls, by analyzing the interaction between hazard, local knowledge, and vulnerability. Rather than treating risk as a single isolated value, the tool follows a Borromean model, where all three factors must be present for meaningful risk to exist.

The hazard component focuses on physical conditions such as rainfall, slope, and seismic activity to estimate the likelihood of an event. Local lore and historical knowledge provide context through past incidents, community reports, and recorded patterns that may not appear in formal datasets. Vulnerability captures what is at risk, including populations, infrastructure, and how susceptible they are to damage.

These inputs are combined into a single risk score and visualized through an interactive map using a three-ring representation, making it easy to understand how each factor contributes. The system also incorporates AI to assist in organizing and autofilling inputs, especially for unstructured data like historical reports, while still allowing users to review and adjust all values.

Overall, GEORISKMOD provides a more grounded and transparent approach to risk assessment, supporting better decision-making in planning, safety, and disaster preparedness.

Alliance Franciase

Faculty Advisor: Debra Parcheta

Team Members: Meme Chhay, Rayhaan Khan, Hanad Ali

This capstone project focuses on enhancing an existing database system to better support the operational needs of a non profit organization. While a prior development team established the foundational database, it currently lacks the functionality required to effectively manage the organization’s day to day activities. The goal of this project is to transform the database into a comprehensive and user friendly tool that supports membership management, event coordination, communication, and donation tracking.

Key improvements include implementing robust data import and export capabilities to handle various data formats and enable efficient data sharing. These features will allow the organization to seamlessly migrate existing records and generate meaningful reports tailored to specific operational needs. Additionally, the project introduces customized database views aligned with real world tasks. These views streamline workflows by organizing data for targeted communications and engagement strategies.

For membership management, the system will support automated messaging such as welcome emails, birthday greetings with discounts, and notifications about exclusive perks and upcoming events. Class related features include generating welcome letters, introductory materials, post class surveys, and early announcements for future sessions. Event management enhancements enable timely communication such as reminders, thank you messages, and special offers for specific participant groups. The donation component focuses on donor engagement through acknowledgments, exclusive updates, and communications about the organization’s impact.

Overall, this project delivers a scalable and practical solution that empowers the non profit to improve efficiency, strengthen community engagement, and better fulfill its mission.

PracticeSmith

Faculty Advisor: Debra Parcheta

Team Members: Tyler Fink, Kevin Gonzalez, Jessica Nguyen, Jathin Reddy Pati

PracticeSmith is a web-based coaching assistant platform designed to simplify how coaches plan, manage, and execute team practices. Built for sports such as soccer, basketball, hockey, and baseball, the application allows coaches to create customizable practice plans using structured drills, assign players to activities, and organize practice schedules in a clear and efficient way. Coaches can start a plan, save their progress, and return later to update or finalize it, making the process flexible and time-efficient.

A key feature of PracticeSmith is its integration of artificial intelligence to enhance the planning process. The platform includes an AI-powered tool that can automatically generate a complete practice plan based on selected inputs such as sport, focus, and duration. In addition, another AI feature allows coaches to generate visual field-of-play diagrams for individual drills, helping them better communicate positioning and movement to players.

Beyond practice planning, PracticeSmith provides tools for managing teams, including roster creation, player and coach assignments, and season tracking. Coaches can input game results and view both individual and team statistics, including calculated performance metrics, which help guide future practice decisions.

The application supports two main user roles: coaches and players, enabling clear communication and structured access within teams. Overall, PracticeSmith helps coaches save time, stay organized, and improve the overall efficiency of practice planning and team management.

Prediction Reference ObjectOriented Framework (PROOF)

Faculty Advisor: Debra Parcheta

Team Members: Abraham Gutierrez, Sam Fredrick, Hunter Tanksley, Simran Mogadala

PROOF is a full-stack web application that enables analysts and researchers to upload structured CSV datasets and immediately derive predictive insights and anomaly visualizations from their data. Designed to be domain-agnostic, the platform supports any event-driven dataset including terrorism incidents, natural disasters, traffic crashes, and public safety records, making it broadly applicable across government, academic, and private sector use cases.

Users begin by importing a CSV file through an intelligent data pipeline that automatically detects column types, geographic coordinates, and date fields. Variable weighting allows users to assign importance scores to specific columns, directly influencing how the prediction engine prioritizes different factors when generating forecasts. The system then analyzes historical patterns across time and location to produce probability-based predictions of future event likelihood, displayed on an interactive map with hourly or daily resolution.

PROOF also features an anomaly detection module powered by Isolation Forest, an unsupervised machine learning algorithm that identifies statistically unusual records within the uploaded dataset. Anomalies and normal data points are visualized together, allowing users to explore geographic clusters, unusual timing patterns, and outlier severities. Anomalous records are excluded from the prediction pipeline to ensure forecasts reflect reliable historical trends.

Additional features include real-time weather integration, configurable prediction windows, and an anomaly analysis panel that explains what makes each flagged event statistically significant.

PROOF transforms raw CSV data into operational intelligence, making advanced predictive analytics and anomaly detection accessible without requiring specialized data science expertise.

Did You See It?

Faculty Advisor: Debra Parcheta

Team Members: Cole Campbell, Samreet Kaur, Nikitha Alluri

Did You See It? is a citizen science application to report volcanic activity in real time.

Volcanologists rely heavily on visual observations of eruptions to understand and monitor activity. However, of the 150 active volcanoes in the world, only a minority have an observatory staffed by professional volcanologists. Even then, professionals can very rarely achieve 24/7 visual monitoring.

Photos collected through Did You See It? will increase the temporal and spatial resolution of observations available to volcano scientists, enabling them to more accurately document and interpret eruptions.

Synthweaver

Faculty Advisor: Debra Parcheta

Team Members: Cassius Kemp, Emily Groza, Matthew Ruediger, Zachary Lawlor

Synthweaver is a software application specifically designed for the comprehensive generation and analysis of synthetic waveforms. The application supports the creation of both continuous wave (CW) and pulsed signals across a wide spectrum of modulation types. Its compiled list of CW modulations includes foundational types such as Sinusoidal, Amplitude Modulation (AM), and Frequency Modulation (FM), alongside sophisticated digital schemes like Frequency-Shift Keying (FSK), Binary Phase-Shift Keying (BPSK), and Quadrature Phase-Shift Keying (QPSK). For pulsed applications, Synthweaver is equipped to generate complex waveforms including Linear Frequency Modulation on Pulse (LFMOP), Nonlinear Frequency Modulation on Pulse (NLFMOP), and Phase-Shift Keying Modulation on Pulse (PSK-MOP).

Beyond just the generation, Synthweaver integrates an intuitive set of analytical tools centered on a dynamic waveform visualization process. This visualization feature allows users to meticulously examine signals through three critical perspectives: the Time Domain, the Frequency Domain, and a detailed Spectrogram. These multi-domain views are indispensable for in-depth analysis, enabling users to verify modulation parameters, identify key signal characteristics, and troubleshoot data for various testing and validation purposes. To complete the user experience, each generated waveform is accompanied by a concise summary, providing key parameters and contextual information at a glance and thereby streamlining the entire workflow from creation to evaluation.

ATHENA Faculty Advisor: David Ogle

Team Members: Kyle Rohn, Justin Hoang, Shivam Pathak, An Nguyen

ATHENA (AI Tutoring Hub Empowered by Neural Agents) is an adaptive educational platform designed to combat the growing issue of "cognitive debt"—a phenomenon where students lose critical thinking skills by over-relying on standard AI shortcuts.

Developed as a self-contained product built on modern web and AI infrastructure, ATHENA flips this narrative by utilizing AI to foster deep, personalized learning rather than passive memorization.The platform serves two primary user bases: students and instructors. For students, ATHENA provides a customized dashboard featuring specific learning modules and an integrated AI Tutor.

Powered by Large Language Models (LLMs) and a Retrieval-Augmented Generation (RAG) backend utilizing ChromaDB, the AI Tutor processes student queries using vector database context to dynamically adapt to individual learning needs. Instead of simply generating answers, it acts as an interactive guide, helping students synthesize complex concepts (such as Object-Oriented Programming) just-in-time for exams. For instructors, ATHENA features a streamlined course management interface. Educators can quickly construct courses, define specific learning objectives, and upload their own materials.

The backend system then automatically processes these documents into a fully interactive, AI-supported learning environment. Ultimately, ATHENA bridges the gap between powerful AI capabilities and genuine educational growth. By delivering accessible, customized instruction, the platform supports neurodivergent learners, aids underserved communities, and empowers students to build sustainable critical thinking skills.

DeepTrace

Faculty Advisor: Tiago Barreto Goes Perez

Team Members: Chloe Ha, Abdulaziz Al-Shanibani

This project presents ShieldScore, a web-based cybersecurity awareness platform designed to address the human factor in cybersecurity by improving user knowledge and behavior through interactive learning. The primary goal of the system is to increase cybersecurity awareness among students and faculty by combining risk assessment, personalized feedback, and hands-on educational challenges.

ShieldScore features an interactive behavioral survey that evaluates users’ cybersecurity habits, such as password practices and multi-factor authentication usage, and generates a quantitative risk score ranging from 0 to 100. Based on this score, users are categorized into risk tiers (low, medium, or high) and provided with tailored recommendations aligned with established frameworks such as the NIST Cybersecurity Framework and MITRE ATT&CK. To reinforce learning, the platform incorporates game-like challenges such as phishing detection and password creation exercises which allows users to apply cybersecurity concepts in realistic scenarios. Additionally, a Capture-the-Flag (CTF) component introduces users to fundamental security techniques through guided problem-solving tasks.

The system is implemented as a browser-based, locally hosted web application using modern technologies such as React and TypeScript, ensuring accessibility and usability.

Overall, ShieldScore demonstrates an innovative approach to cybersecurity education by integrating assessment, personalization, and interactive engagement. This platform aims to reduce risky user behavior, enhance security awareness, and provide a scalable solution for educational institutions seeking to strengthen their cybersecurity posture.

Threat Intelligence and Guided Operations

Faculty Advisor: Tiago Barreto Goes Perez

Team Members: Mitchel "Ryan" Harvey, Vincent Hollander, Jeffrey Raphel, Yosef Tsegai

The project is a customizable cyber range designed for school cybersecurity programs such as the CU Denver cybersecurity department. This is a server system that generates entirely virtual scenarios that are created and curated by professors to allow students to safely test cybersecurity adversarial and administrative techniques.

MULTIDISCIPLINARY

Torque Titans

Faculty Advisor: Ron Rorrer

Team Members: David Malfavon Campos Jeffrey Guiette Joshua Rathbun

Measuring clamp force in industrial assembly tools is important for making sure everything works safely and consistently, but right now the process is mostly done by hand. This takes a lot of time, requires multiple operators, and can introduce human error.

Working with Atlas Copco, the Torque Titans team set out to improve this by building an automated testing system. The system uses a load cell to measure clamp force while testing an industrial electric pulse torsion tool. Each test uses a new bolt, nut, and washer to keep results consistent, and the goal is to run tests automatically in about one minute per cycle, with the potential for up to 1,000 tests in a row. The load cell allows for accurate and fast force measurements during each test.

This year, our main focus was designing bolt and nut sorting systems that can run on their own and feed parts into the rig without needing someone to load them manually. These systems use stepper motors and simple mechanical designs to keep parts moving and ready for testing. Overall, this project moves the testing process toward full automation, helping reduce errors, save time, and make results more reliable.

Experimental Launch Module (ELMo)

Faculty Advisor: Ron Rorrer

University of Colorado, Denver: Samuel Post,Tyler Stanley

Linkoping University: Joel Bergström, Linnéa Eriksson, Alba Sundqvist, Adam Wannerström

University of Colorado at Colorado Springs: Brayden Brock, Bernadette Felter, Nathaniel Means

Astronauts frequently experience weakened immune systems in space, leading to an increased susceptibility to illness. T-cells, a type of white blood cell critical to the immune system, have had their functional capabilities in microgravity questioned. Previous experiments conducted by the Swedish Space Corporation (SSC) and Karolinska University on the SubOrbital Express-4 (MicACTin experiment) indicate that microgravity significantly impacts T-cell activation, resulting in a weakened immune response. However, those studies were limited to "endpoint" results—analyzing cellular changes only after the flight had concluded.

A collaboration between three schools—the University of Colorado Denver, the University of Colorado Colorado Springs, and Linköping Technical University—has created the Experimental Launch Module (ELMo) to close this knowledge gap. By capturing and documenting data in real time, ELMo aims to bring light to a process previously unexplained. Utilizing an autonomous experimental system, T-cells will be injected onto a stimulatory glass surface when microgravity is achieved. A compact internal microscope will then document the activation sequence as it unfolds. These images will be captured and stored locally to be recovered for analysis following re-entry. Simultaneously, the system will also regulate temperature to maintain the health of the T-Cells.

The results of this experiment will provide critical insights into T-cell adhesion and immune response in space. This data is vital for preparing astronauts for long-term missions to farther regions of space, where maintaining peak physical health is mandatory for mission success.

ThAIRapy

Faculty Advisor: Ron Rorrer

Team Members: Eli Garcia, Anis Benyoucef, Brendan Pham, Edward Rodriguez

The ThAIRapy device is a full-body drying experience that provides an alternative to traditional drying methods. It is designed to produce a fast drying time of less than two minutes, efficiently provides even full-body coverage, be eco-friendly, produce minimal noise, and be used completely hands-free. Although this product can be used by anyone, it is primarily customer-specific to those who are unable to properly dry themselves due to physical limitations and/or disabilities.

The original design of the ThAIRapy device consists of a two-pillar design that utilizes the physics of a crossflow fan combined with a heating system and sensors that read temperature, wind speed, and motion data, as well as air catchers to maintain the momentum of the air. It stands about 7 feet tall with a base area of 15 square feet, optimizing for full body coverage and wheelchair accessibility. Users will be able to create a customizable and controlled environment with the ability to adjust specific parameters to their liking and save preset options using the onboard touchscreen panel.

The ThAIRapy device is able to reach an airflow of 8 m/s, with operating temperatures ranging from 70°F to 95°F, and an automatic turn-on/shut-off system for easy-use and safety. For the sake of the build and budget constraints, only one pillar has been manufactured and cut down in size to about 5 feet tall, all while still being able to achieve system requirements. The device is primarily constructed with materials like aluminum and fiber-reinforced plastic (FRP), which are non-corrosive and perfect for wet/humid environments.

FIRST YEAR DESIGN

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