2025-26 Project Portfolio
The Senior Design Capstone provides an opportunity for industry and academic sponsors to engage and utilize the minds of some of the brightest students on campus. Read more about what the students are working on in the 2025-26 academic year.
Anchovy
WEB APP
Project Type: Web Development, Mobile Application
Anchovy seeks to extend its mobile recipe and mealplanning platform to a desktop-optimized web app with QA and Production under anchovy.app. Aimed at adults 50–65 who prefer tablets/laptops, it mirrors the mobile experience with web-specific enhancements: a profile hub with search, extensive recipe views, and friends’ profiles. Users can create/upload (link, text, file), edit, share, and print recipes—including printable formats with QR codes—plus view a wholeweek meal plan with draganddrop (stretch) and manage printable grocery lists (stretch). High points include desktop print options, a weekly planner, and expanded upload methods. The team will reuse existing components and deliver a functioning web app supporting login/logout, robust recipe management, and friends’ views, with mealplan and grocerylist features as stretch goals.
Technologies used:
- Angular
- Ionic
- .NET
- Azure
- SQL
- Auth0
Aulick
E-COMMERCE PLATFORM TOOLING YEAR 3
Project Type: Web Development, E-Commerce
In Phase III of its multi-year effort, Aulick will turn its parts catalog foundation into a full online sales channel. Building on Year 1–2 tools (EPC and the E-Commerce Manager for content, photos, and AI-aided descriptions), this year focuses on operations at scale: syncing inventory with the storefront, automating order and shipping workflows, and delivering integrations and admin tooling inside Aulick’s COHORT platform to import inventory, export sales data, manage customer communications, and control product visibility. The solution will integrate with BigCommerce, enabling customers to self-serve search and purchase, improving SEO-driven traffic, reducing wrong-part orders, and streamlining labor across fulfillment. Deliverables are working tools and integrations with clear documentation and production-ready code in Aulick’s repo.
Technologies used:
- MongoDB
- Express
- React
- Node.js
- AWS Lambda
- AWS S3
- AWS EC2
- SendGrid Twilio
BinMaster
POINT CLOUD DATA PROCESSING AND MANIPULATION
Project Type: Embedded System, Data Analytics, Internet of Things
BinMaster seeks a web-based pipeline that ingests radar-generated point clouds to accurately estimate volumes of bulk materials in bins, silos, and flat warehouses, and to display an intuitive 3D visualization in BinCloud. Students will deliver an interactive surface view (rotate/zoom/slice) with heat-map elevation, supporting two sensor modes: high-density “full scans” for detailed meshes and “lite scans” that interpolate between full scans for continuous insight. The system will pair surface reconstruction with known container geometry to handle irregular topographies (peaks, voids, slopes) and quantify the minimum scan coverage needed. This closes a critical gap as BinMaster moves from legacy acoustic tools (without source code) to a new radar platform. High points: real-time visualization, reliable volume tracking from sparse data, seamless BinCloud integration, and a tool that processes .xyz files into clear, customer-ready results.
Technologies used:
- 3D Visualization
- Web Integration
- Point Cloud Processing
Blue Cross Blue Shield of Nebraska
BENNETIQ
Project Type: Artificial Intelligence, Data Analytics
Blue Cross Blue Shield of Nebraska (BCBSNE) seeks an expansion of its Bennet AI co-pilot (launched April 2024) to learn from CSR chat logs and make every interaction smarter. The team will build a data-driven agent that ingests and anonymizes logs, surfaces trends (top topics, intent, volumes, sentiment), and measures performance, then delivers interactive dashboards and recommendations to improve self-service and CSR workflows. Work includes refining Bennet’s responses with RAG, detecting patterns tied to positive/negative ratings, flagging benefits or questions that need attention, and enabling basic agent-to-agent handoffs for future use. Deliverables include a functional prototype, demo, and concise technical documentation, designed to scale to additional BCBSNE agents. Students will work in BCBSNE’s Azure environment with access to tools, repos, and support. The outcome is a smarter Bennet and a better member experience with reduced effort for service teams.
Technologies used:
- Azure
- Azure OpenAI
- Azure AI Search
- Azure SQL
- .NET
- Python
CLAAS
BOLTED JOINT WITNESS MARK FUNCTIONALITY
Project Type: Embedded System, Internet of Things
Year 3 aims to finalize a compact add-on that automatically sprays a permanent witness mark the moment a torque tool reaches spec. Triggered by the tool’s clutch/exhaust (or equivalent), it provides clear visual proof, speeds inspection, and helps distinguish technician error from clamp-load failure. The focus is production-ready robustness—low-profile, durable hardware with quick-dry media—compatible with varied air/DC tools, socket sizes, tight spaces, 90-PSI air, and rechargeable power. Deliverables include multiple pilot units and an assembly-bay setup for deployment.
Technologies used:
- CAN bus
- Bluetooth
- Microcontrollers
- Python
- C/C++
DMSi
VOICE SCALING
Project Type: Mobile Application, Voice Recognition, AI
Add hands-free voice entry to DMSi’s React Native log-scaling app so sawmill scalers can speak diameter, length, species, grade, price, and defects while working. The system must map speech to each customer’s configurable tables, accept fields in any order, validate (with optional read-back), then save and reset for the next log—fully offline. Ship as production code (Android first, iOS if feasible) with minimal backend changes and as an optional alternative to manual entry. Result: faster, safer, and more consistent scaling across multi-tenant deployments.
Technologies used:
- React Native
- Android
- iOS
- AI Voice Tools
DPA Auctions
HIGH-STAKES DECISIONS: AN ASSET MANAGER BLUEPRINT
Project Type: Artificial Intelligence, Data Analytics, Automation
Stage 2 of the Asset Manager project focuses on transforming the Scenario section into a robust liquidation and replacement planning engine while introducing a Commodity Tracker & Predictor module. This evolution aims to empower farmers and equipment owners to model asset sales' financial and tax impacts, strategically time reinvestments, and incorporate real-time commodity market intelligence into their decisions.
By combining deterministic tax calculations with AI-assisted explanations and layering in commodity price forecasting, Asset Manager will move from being a static valuation tool to an active decision-making platform for operators and lenders.
Technologies used:
- Palantir Foundry
- Python
- SQL
- REST APIs
- GraphQL
Farm Credit Services of America
DOCUSIGN PROTOTYPE UI
Project Type: Web Development, Workflow Automation
Farm Credit Services of America seeks a proof-of-concept web UI that streamlines e-signature prep, which is now spread across multiple systems. The prototype will let users select/upload documents, pull mocked recipient data, and send envelopes via secure calls to the DocuSign sandbox—all from one interface. Deliverables include core requirements, wireframes, a functional front end (React/Angular), API integration, and end-to-end testing to prove a faster, less error-prone workflow.
Technologies used:
- Angular
- C#
- .NET
- DocuSign API
First National Band of Omaha
FNBO FOUNDATIONS
Project Type: Mobile Application, Financial Tech
This project’s goal is to prove a youth financial ecosystem that builds lifelong FNBO customers through engaging education and clear upgrade paths. The team will prototype three age-linked experiences: (1) a child savings journey with visual learning and milestone tracking to build habits; (2) a teen checking app (13+) with intuitive budgeting and purchase visualization, leveraging Amazon data and appropriate parental controls; and (3) a young-adult path that teaches credit fundamentals and introduces a first credit-building product. Success is a streamlined UX that increases activation and retention across stages, lays a path to profitability (deposits, interchange, future loans), and differentiates FNBO’s brick-and-mortar + digital model—delivered as clickable prototypes, user flows, and research-backed content that meet COPPA/privacy requirements and show how customers transition between products.
Technologies used:
- Java
- Spring Boot
- PostgreSQL
- Swift
- SwiftUI
- Kotlin
- React native
L.U.C.A Coaching by TJ
LUCA APP
Project Type: Mobile Application, Artificial Intelligence, Virtual Reality
This project delivers an MVP mobile app that puts nurse coaching directly in the hands of novice nurses working in high-acuity units—reducing overwhelm, improving care, and lowering turnover. The app will use interactive prompts (and, where applicable, AI/VR scenarios) to let users enter patient/unit details and receive just-in-time guidance, red-flag checklists, and “what to watch for” tips across multiple specialties. Core goals include a clear, self-paced experience that builds confidence, easy-to-update modules, and a path to monetization (e.g., subscriptions) plus optional contact with a live coach. Stretch goals add continuing-education content and expanded specialty libraries, creating a scalable alternative to costly, hard-to-staff in-person mentoring.
Technologies used:
- AI
- VR
- Mobile App Framework
McCain Foods
AUTOMATION OF ONION PLACEMENT AND SINGULATION
Project Type: Data Analytics, Web Development
McCain seeks an integrated solution that (1) automates onion pick-and-place and singulation at line front using a delta robot and vision to orient onions to 0–5° and achieve ~99% pocket fill; (2) measures and reports “% Straight” from camera data with real-time dashboards, shift/day reports, and alarms for out-of-control conditions; and (3) replaces manual spreadsheets with automated daily data collection. Deliverables include a prototype robotic picker, singulation concepts, improved onion pocket design, and a software pipeline that bins angles (e.g., 0–5°, 5–10°…30°), provides operator red/green feedback, and drives process control. Expected impact: higher throughput, 2–5% yield improvement in the end-cutter area, and recovery of 2–4 hours/day now spent compiling data.
Technologies used:
- Python
- AWS
- PostgreSQL
Midwest Holding
MOBILECONNECT: CUSTOMER & AGENT WEB PORTAL
Project Type: Web Development
Build a mobile-first portal (PWA) that lets customers self-serve policy, statement, and transaction info and lets agents handle service requests on the go—reducing call-center volume and speeding resolution. Goals: deliver simple, secure access on any device; provide clear policy/transaction views and a support-ticket flow; enable role-based dashboards for customers and agents; and prove measurable gains in self-service, first-call resolution, and operating cost reduction, setting the foundation for a unified, modern digital experience.
Technologies used:
- JavaScript
- React
- PostgreSQL
- AWS
Mutual of Omaha
DQC, R&S
Project Type: Web Development, Machine Learning
Build a production-ready toolset that guarantees the integrity and privacy of our JSON-based domains: automatically validate documents and cross-collection relationships to enforce completeness and referential integrity; generate clear quality reports; and deterministically sanitize sensitive fields while preserving structure and linkages so production-like test data can be created safely. Success means faster, safer development cycles, continuous quality monitoring across test and prod, and a scalable rules framework that improves data reliability, strengthens compliance, and becomes a reusable foundation for future data governance.
Technologies used:
- Python
- AWS
- React
- MySQL
Nebraska EPSCoR
NSPIRE
Project Type: Web Development
NSPIRE’s goal is to grow Nebraska’s research capacity by building a low-maintenance, statewide hub that connects people and physical resources across all IHEs, industry, and K-12. Phase 1 delivers a specialized, searchable directory of research infrastructure and services—equipment, fees, contacts, and request steps—with filters for location, cost, availability, and organizations' ability to add listings. Next, the platform adds a researcher/subject-matter-expert finder (interests, publications, affiliation) that can link to Nebraska Extension’s community-needs system, plus a dynamic site for news and event/registration. The solution should be easy to use and mobile-friendly, support basic roles (admin/organization/public), and, where feasible, automate data ingestion (scraping/APIs) and gather satisfaction signals—creating equitable access and durable collaborations statewide.
Technologies used:
- Vue.js
- JavaScript
- Python
- PostgreSQL
Nebraska Public Media
KYNE-TV ATSC 3.0 VIRTUAL CHANNEL AND APP DEVELOPMENT
Project Type: Web Development, Data Analytics
Goal: enhance the existing RUN3TV broadcaster app to deepen engagement, improve public safety, and measure impact. The team will add Advanced Emergency Alerting with user-set preferences, integrate analytics to track feature usage and viewing time, and build a simple, family-friendly TV game (remote-control navigation, regular content updates, anonymous leaderboard) that works in a standard web browser. Features should be platform-agnostic to reach viewers beyond the ATSC 3.0 signal, maintain a modern, accessible UI, and support future modules (e.g., news, revenue experiments, social reach), ultimately driving discovery, repeat use, and data-informed programming decisions.
Technologies used:
- JavaScript
- Python
- PostgreSQL
Nebraska Trucking Association
DIESEL TECH CAREER EXPLORATION VR EXPERIENCE
Project Type: Mobile Application, Web Development
The Nebraska Trucking Association’s Year 2 goal is to turn its diesel-tech VR shop into a portable, attention-grabbing career exploration tool that boosts interest and applications among high-school and young-adult audiences. Building on last year’s environment and first tire-change demo, the team will create several short, self-contained “mini-games” that simulate real diesel-tech tasks (timed, scored, and easy to restart) and refine the shop’s realism and interactivity—without aiming for full training mastery. The experience must run smoothly on Meta Quest 3S headsets, be simple to deploy at schools and public events, and encourage repeat play. Deliverables include completed tasks, performance tuning, and polish that make the app engaging, durable, and shareable with other state associations, schools, and workforce partners. Outcome: a proprietary VR experience that sparks curiosity about diesel technology and strengthens Nebraska’s technician pipeline.
Technologies used:
- React
- Swift
- AWS
Nelnet
OBSERRA
Project Type: Web Development, Artificial Intelligence
Obserra aims to turn Nelnet’s manual, fragmented audit prep into a structured, intelligent workflow. The team will deliver a web platform that centralizes audit artifacts with versioning and ownership, maps documents to specific regulations, and uses AI to score relevance, validate content against controls, and flag inconsistencies or missing evidence. Dashboards will let risk/audit teams track requests and status (Sent/WIP/Done), reuse prior submissions, and see cross-team coverage gaps, while SSO/role-based access protects sensitive data. Stretch goals include change-detection on regulations, recommendations, reminders/escalations, and richer reporting. Success is faster, safer, and more accurate audits—with traceability and reusable, high-quality documentation that can evolve into a marketable product.
Technologies used:
- React
- Python
- AWS
TWIL Luxury Innovations
TWIL DESIGN LABS
Project Type: Web Development, Augmented Reality
TWIL seeks an MVP web-based 3D configurator that lets non-technical users (designers, clients, completions centers) load or upload interior models for aircraft, yachts, or hospitality spaces; apply TWIL’s ultra-realistic scanned surface patterns; interactively adjust grain, scale, and orientation; and export visuals and sample requests to speed decisions. The goal is to replace today's manual mockups with an intuitive, demo-ready tool that shortens sales cycles, improves accuracy, and showcases the product line to customers and investors. The team will deliver a clean, usable prototype with basic asset libraries, mockup/output flows, and documentation—positioned for future growth (larger pattern libraries, pricing and order configuration, and optional Apple LiDAR scan imports).
Technologies used:
- JavaScript
- Unity
- AWS
UNL Department of Agricultural Economics
OPEN ACCESS ONLINE EXPERIMENTAL RETAIL FACILITY
Project Type: Web Development, Data Analytics
Build a customizable, web-based “research retail” site that lets scholars design realistic online grocery experiences and capture rich behavioral data. The platform should allow researchers to define product assortments and presentation (with optional web-scraped catalogs), toggle features like search, filters, and sorting, host multiple concurrent study versions for A/B tests, and log detailed choice-process variables (queries, filters used, dwell time, clicks) alongside final selections. An easy, researcher-friendly admin will enable setup without heavy coding, and the site should either embed survey questions or integrate cleanly with external survey tools for unified datasets. Security must support collecting non-protected study data, with scaling options as usage grows. The goal is an open-source resource that makes complex, realistic consumer-choice experiments feasible and repeatable—advancing research on healthier and lower-impact food decisions.
Technologies used:
- Python
- PostgreSQL
- Django
UNL Department of Classics and Religious Studies
RETOOLING THE ALPHEIOS LANGUAGE TOOLS
Project Type: Web Development
This project modernizes the open-source Alpheios Reading Tools to remain widely usable for studying Ancient Greek, Latin, and Classical Arabic. The team will rebuild the browser extension to comply with Chrome’s Manifest V3, refresh outdated JavaScript dependencies, and restore stable, cross-browser access to morphology, dictionaries, and syntax help. A second thrust is planning—and, if feasible, prototyping—a new Arethusa Treebank Editor to replace the legacy Angular app: define architecture and UX for creating, editing, and viewing syntactic dependency trees in teaching/research settings, and explore assistance from contemporary NLP/LLM parsers. Expected outcomes are a working Manifest V3 extension plus an actionable redesign plan (and initial code if time allows) that protects and strengthens a toolset used by thousands worldwide.
Technologies used:
- JavaScript
- React
- Python
- PostgreSQL
UNL Department of Special Education
EMPOWERING VOICES: ADVANCING EMOTION-AWARENESS IN AAC
Project Type: Web Development
Build a prototype, emotion-aware Augmentative & Alternative Communication (AAC) system for children (ages 6–12) that detects a user’s emotional state and adapts communication in real time. The MVP should (1) identify a few basic emotions via multimodal cues (e.g., facial/gesture/audio/context), (2) adjust synthesized speech prosody with an on/off control and intensity slider, and (3) surface quick-access, picture-based vocabulary relevant to the detected emotion (e.g., show “help” when frustration is sensed). The project emphasizes user-centered design and portability (touch-screen UI), with initial usability testing and stakeholder feedback (children/families, clinicians, educators). Stretch goals include improving emotion accuracy with ML, broadening emotion sets, and considering cultural/physical differences. The solution should be positioned for integration with commercial AAC platforms (e.g., Smartbox) to scale impact in the long term.
Technologies used:
- JavaScript
- React
- PostgreSQL
UNL School of Natural Resources
IMMERSIVE CONSERVATION
Project Type: Geographic Information Systems, Data Analytics
Build a producer-facing VR prototype that lets landowners “step into the future” of their own fields and see how 1–2 conservation practices (e.g., prairie or filter strips) change conditions, profitability, and ecological outcomes across seasons and years using real geospatial farm data. Year-1 goals: visualize seasonal/annual progression, provide a simple scenario UI, and run a structured stakeholder co-design/usability loop; pilot the experience at Extension events. Core outcome: reduce uncertainty and accelerate the adoption of practices that improve soil health, water quality, wildlife habitat, and whole-field profitability. Longer term, evolve into a full decision-support system with ROI calculators (CRP/EQIP, input savings, yield changes), USDA eligibility, ecosystem-service projections, and scenario planning for climate/market variability, delivered on VR for demos and web/mobile for everyday access. Deliverables include the functional VR prototype, integrated field data, user documentation, and a usability/feedback summary.
Technologies used:
- ArcGIS
- PostgreSQL
- Python
UNL SoC Bohn
RUNNING ROBOT: ROCK'EM SOCK'EM
Project Type: Web Development, Data Analytics
Build a fun, fully playable, robot “laser-tag” platform by finishing and extending the existing Running Robot system: camera-equipped ground vehicles fire encoded IR “shots,” report hits to a web scoreboard, and are driven via Raspberry Pi + smartphone app with a bot’s-eye view (VR-ready). This year’s goals are to finalize the electronics (complete/clean up the PCB) and port the phone app to iOS, then add high-impact features such as autonomous driving/aiming, two-person crew mode (separate driver/gunner controls), VR-headset controls, additional camera options, and the embedded systems support those require. Deliverables include working hardware, KiCad/3D print files, firmware, Android/iOS apps, web services/scoreboard code, and full build/use documentation.
Technologies used:
- Python
- PostgreSQL
- JavaScript
- HTML
- CSS
UNL SoC Cui
SMART HEALTH ASSISTANT
Project Type: Data Analytics, Artificial Intelligence
Build an AI-powered mobile app that automates multi-modal health behavior monitoring to reduce the burden of manual tracking and enable data-driven interventions for obesity and metabolic health. The app will pair image-based meal logging (segmentation/classification and nutrient estimation) with passive sensing and wearable data (Fitbit/Apple HealthKit, SmartPlate) via the AWARE framework, then standardize signals with the RAPIDS pipeline to surface personalized trends in diet, activity, sleep, location, and phone use. Core deliverables: a cross-platform (Android/iOS) app, integrations with wearables and food analysis models, secure storage, intuitive dashboards/reports; stretch goals include just-in-time nudges and real-time alerts. Sponsored by Dr. Juan Cui’s Systems Biology & Biomedical Informatics Lab, the goal is to improve adherence to personalized nutrition, detect unhealthy patterns early, and advance research in personalized health.
Technologies used:
- Python
- TensorFlow
- Jupyter
UNL SoC Cui-Wang
UNLOCKING MUNICIPAL BONDS
Project Type: Web Development, Machine Learning
Build a web platform that ingests municipal bond official-statement PDFs, automatically parses and highlights key financial/legal details, and lets users search, filter, and visualize results in clear dashboards. The system will also identify comparable bonds currently trading to provide pricing benchmarks, with an architecture ready to add an AI/LLM-based rating predictor for unrated issues. The goal is to make unrated municipal bonds easier to evaluate, increase market transparency, and lower community financing costs by giving issuers and investors fast, actionable insights. Sponsored by Drs. Liying Wang (Finance) and Juan Cui (School of Computing), the project blends NLP, data engineering, and UI design into a practical fintech tool.
Technologies used:
- Python
- Django
- MySQL
- JavaScript
- AI Models
UNL SoC Falkinburg
CAREER EXPLORE XR
Project Type: Gaming, Web Development
Build a Unity-based Meta Quest 3 app that lets middle and high school students explore skilled-career pathways through immersive XR modules. The experience will showcase hands-on roles urgently needed for AI data centers and other critical sectors—e.g., electricians, HVAC, welding, plumbing, nursing, dental assisting, pharmacy tech, PT assistant, automotive, and IT—while guiding learners toward vocational, community-college, or four-year options. The goal is workforce development: demystify jobs, illustrate day-to-day tasks, and spark interest in high-demand careers. Deliverable: a polished, store-ready Quest app (SideQuest/Meta) optimized for ≥72 FPS, with content authored by computing faculty Jeff Falkinburg and career-advising SME Britney Falkinburg.
Technologies used:
- JavaScript
- React
- Unity
UNL SoC Falkinburg
HUSKER STEM VR 3.0
Project Type: Virtual Reality
Expand and modernize the Husker STEM VR outreach app across Android, iOS, Web, and Meta Quest 3 to boost recruitment and inclusive STEM engagement. The team will update mobile builds (Android 16, iOS 18.6), port/optimize the VR app for Quest 3 (≥72 FPS), and ship store-ready releases (Google Play, Apple App Store, SideQuest/Meta). New content includes a 3D walkthrough of Kiewit Hall classrooms/labs and fresh interactive “escape room”–style activities showcasing CoE programs (e.g., Robotics, Data Science, Architectural, Agricultural, Construction, Environmental Engineering). Outcome: a polished, multi-platform experience that makes learning fun and highlights UNL engineering pathways at scale.
Technologies used:
- Unity
- C#
- Oculus SDK
- 3D Modeling Tools
- Git
UNL SoC Guo
HOLOGRAPHIC-TYPE VIDEO CONFERENCING SYSTEM DESIGN
Project Type: Machine Learning, Artificial Intelligence
Build a foundational mixed-reality telepresence platform that captures a person with an RGB-D camera array, reconstructs a realistic 3D model with computer vision/deep-learning refinement, and streams it with low latency to a Microsoft HoloLens 2 for life-size, interactive viewing. The team will implement end-to-end capture → compression/streaming → rendering software (Python/PyTorch/OpenCV/Open3D + Unity/MRTK), optimize visual quality and responsiveness, and evaluate latency and user experience. Out of scope for now are multi-user/group meetings and bandwidth optimization; stretch goals include spatial audio, user studies, and GPU/edge acceleration. Deliverable: a working demo where two remote users wearing HoloLens 2 devices see each other as full-scale 3D holograms, positioning the project for research publications, patents, and future expansion.
Technologies used:
- Python
- TensorFlow
- PyTorch
UNL SoC Ramamurthy-McChargue
SPORTS BETTING AMONG AT-RISK COLLEGE MALES
Project Type: Data Analytics, Web Development
Build an alpha Android app and admin web portal that helps at-risk college men bet more responsibly by interrupting impulsive, in-the-moment wagers. The app will (1) detect or prompt for sports-betting activity, trigger a brief “cooling-off” cognitive exercise (target ~30s), and then resume access; (2) deliver short financial-literacy videos; (3) support limit-setting, goal/feeling logging, and behavior feedback; and (4) send just-in-time notifications, with optional geofenced prompts (e.g., near casinos). A secure backend will manage content, interventions, and research data (usage, goal attainment, attitudes) to enable feasibility testing next year. Year-1 goal (Aim 1): co-design and ship the working prototype (Android 10+, Firebase auth/notifications; UsageStats/Accessibility for app detection; React/Node or Django portal). Longer-term goals (Aims 2–3): run a pilot RCT with 60 students comparing cooling-off vs. assessment-only and evaluate usability/acceptability to inform scale-up and future funding.
Technologies used:
- Python
- R
- Tableau
- PostgreSQL
UNL SoC Samal
ADVANCING JUSTICE COLLABORATORY
Project Type: Artificial Intelligence, Data Analytic
The project will build a Nebraska-focused, web-based “A2J” platform to narrow the civil justice gap by giving residents fast, trustworthy self-help and referrals. Core goals are to (1) develop A2J Assistant, a multilingual text/voice LLM chatbot fine-tuned on Nebraska civil law to triage issues, provide jurisdiction-relevant information, and assist with legal form completion; (2) launch A2J Explore, a map interface showing nearby courts, legal aid, attorneys, and related data layers; (3) add A2J Engage, a community portal for dialogue and research participation; and (4) implement A2J Logger to capture usage analytics in a searchable database. Scope is civil matters in Nebraska (extensible to other jurisdictions), with accessibility, low latency, and UNL authentication where required. The system will run on CSE infrastructure using MySQL and likely Ruby on Rails, with locally deployed LLMs (via Ollama) evaluated and tuned for performance. Deliverables include a deployable application, documentation, and guidance for future expansion.
Technologies used:
- Python
- AWS
UNL SoC Sharif-Hughes
COCHLEAR IMPLANT RESEARCH LAB - MOBILE AUDIO TEST
Project Type: Web Development, Mobile Application
Build an easy-to-administer, web-based hearing test (not just a screening) on a smartphone/tablet with headphones so community health workers can identify hearing loss in underserved areas and trigger referrals. The app will use tester registration/approval for quality control, guide the user through an automated protocol, capture air-conduction thresholds at 500, 1k, 2k, 4k, and 8k Hz for both ears, and display a plotted audiogram with pass/fail results. Results will be saved per session to a secure, queryable cloud database (REDCap preferred; AWS acceptable) to report volumes, pass/fail rates, referrals, and follow-ups. Scope includes a simple GUI, data schema design, secure storage, reporting tools, and hosting on a dedicated website; the system should remain database-portable and open-source friendly (e.g., informed by TabSINT). Deliverables include requirements/design docs, implemented features above, a user guide, and pilot testing data with participants.
Technologies used:
- JavaScript
- AWS
- RedCap
UNL SoC Vuran
RURALCONNECT
Project Type: Research and Development, Internet of Things, Wireless Networks
RuralConnect will prototype a portable, private 5G small-cell network to bring reliable broadband to rural communities and rapidly deployable communications to disaster responders. Using srsRAN (O-RAN), software-defined radios, and a satellite backhaul, the team will run CU/DU/RU functions and an Open5GS/srsEPC core on local edge hardware (no cloud required), then dynamically adapt RAN behavior to satellite latency/bandwidth constraints. Core deliverables include SDR small-cell integration, satellite-link emulation, bandwidth-aware O-RAN reconfiguration, CBRS operation with SAS integration, and end-to-end field tests measuring latency, throughput, and reliability. The initial scope targets a single-cell, self-sufficient deployment (with an option to compare a cloud-based EPC), while stretch goals explore rugged low-power packaging, QoS enhancements, a simple monitoring dashboard, and multi-cell expansion.
Technologies used:
- O-RAN
- srsRAN
- Software Defined Radio
- Satellite
- CBRS
- Linux
- Docker
- Kubernetes
- C/C++
- Python
UNL SoC Vuran
SKYBEAM
Project Type: Internet of Things, Embedded Systems, Wireless Networking
SkyBeam will prototype a closed-loop mmWave (≈60 GHz) link between a ground station and a fast-moving drone with multi-gigabit throughput while the aircraft maneuvers. The team will combine a phased-array front end (electronic beam steering) with a lightweight pan-tilt mount (coarse pointing) and SDR-based baseband to detect a drone beacon, estimate direction-of-arrival, and continuously steer the beam in real time. An out-of-band sub-6 GHz channel carries control/telemetry; once aligned, the mmWave link moves user data (e.g., high-rate video).
Core goals
- Integrate the mmWave phased array, SDR, and pan-tilt hardware; calibrate and characterize array beams.
- Build GNU Radio/Python DSP for beaconing, DoA estimation, adaptive beamforming, and a closed-loop tracker with logging (RSSI/SNR/beam index/angles/throughput).
- Fly a drone with a compact mmWave transmitter and demonstrate a sustained multi-Gb/s link over representative outdoor flight paths, meeting safety and regulatory constraints.
Technologies used:
- Software Defined Radios (SDR)
- O-RAN
- Python
- Microcontrollers
- Satellite Communications
UNL SoC Weitzel
NPR OPEN ONDEMAND
Project Type: Artificial Intelligence, Machine Learning
Build and deploy Open OnDemand (OOD) apps on the National Research Platform (NRP, Kubernetes-based) so researchers can launch GPU-backed workflows—starting with JupyterHub for interactive AI/ML and AlphaFold for structure prediction—through a simple web interface. The work removes HPC/K8s complexity, enabling one-click access to distributed NRP resources while following patterns proven on HCC’s Swan system.
Core goals
- Package JupyterHub and AlphaFold as OOD Interactive Apps for NRP (Docker images, job templates, GPU requests, storage, logs).
- Integrate OOD with NRP (Kubernetes) and validate end-to-end launches on Nautilus; use Swan’s existing setups as references.
- Ensure usability (resource selection, status/monitoring, error surfacing) and document deployment/operations in Git.
- Collaborate with NRP/OOD experts; meet security and access expectations (UNIX/K8s best practices).
Technologies used:
- Python
- AWS
- Jupyter
UNL SoC Yao
IMMERSIVE VIRTUAL REALITY
Project Type: Machine Learning, Data Analytics
Build on an existing prototype to deliver an intuitive web + VR platform for exploring protein language-model embeddings (motifs, clusters, functions). The tool should work in a browser and on headsets, focusing on Apple Vision Pro, so researchers and instructors can interactively inspect complex protein spaces and lead group demos.
Core goals:
- Dataset expansion & scale: Import/standardize additional protein sets (plant, microbiome; optionally AI-generated proteins) and stress-test rendering limits.
- Leader Mode: Presenter-controlled session sync (follow-my-view, highlight/annotate, step-through) for classrooms/lab meetings.
- Performance & UX optimization: Apple Vision Pro offers smooth navigation/gestures and crisp 3D rendering; keep a lightweight WebXR version for broad access.
- Better visuals & analysis: Improved motif/cluster views, multi-select comparison, selection tools, and functional overlays.
- Polish & portability: Refine UI for solo/group use; document pipelines and deployment.
Technologies used:
- Python
- AWS
Valmont
IRRIGATION MAINTENANCE
Project Type: Web Development, Mobile Application
Valmont wants a simple maintenance-management feature inside its AgSense 365 web/mobile apps to keep costly center-pivot irrigation machines running optimally over their 30–40-year life. Using each machine’s run-hour data (like vehicle mileage), the system will let growers set hour/date-based service schedules, receive timely notifications, and quickly record completion with basic details—reducing reliance on manual tracking or dealer reminders. The goals are to prompt on-time upkeep across large fleets, improve user experience and adoption, and build a searchable service history that adds value now and enables future offerings such as warranties, service plans, and broader fleet-management tools.
Technologies used:
- Angular
- .NET
- MySQL
- iOS
- Android
- Azure