MuAMO: an Intelligent Maintenance Optimization Framework for Safety-Critical Systems
TS-073254 —
Industries operating safety‑critical and asset‑intensive systems struggle to leverage the full value of disparate maintenance data sources. Current maintenance management and optimization tools operate in silos, limiting real‑time decision‑making, automation, and scalability. No existing s…
- College: College of Engineering (COE)
- Inventors: Smidts, Carol; Diao, Xiaoxu; Khafizov, Marat; Pietrykowski, Michael; Vaddi, Pavan Kumar; Zhao, Yunfei
- Licensing Officer: Giles, David
DPRA: Dynamic Probabilistic Risk Assessment for Cyber Security Risk Analysis
TS-073146 —
As industrial systems become increasingly digital and interconnected, traditional risk assessment tools struggle to capture how cyber threats interact with physical processes in real time. Existing methods typically assess hardware failures or isolated cyber events, but they cannot model how attac…
- College: College of Engineering (COE)
- Inventors: Smidts, Carol; Diao, Xiaoxu; Vaddi, Pavan Kumar; Zhao, Yunfei
- Licensing Officer: Giles, David
Model-Based, Multi-Criteria Optimization for Sensor Placement and Selection
TS-073138 —
Designing online monitoring (OLM) for safety‑critical systems is constrained by scarce early‑stage operational data and by quantitative models that are slow to build, brittle across configurations, and costly to iterate. This creates expensive sensor networks with blind spots, poor diagnosabil…
- College: College of Engineering (COE)
- Inventors: Smidts, Carol; Diao, Xiaoxu; Olatubosun, Samuel; Rownak, Md Ragib; Vaddi, Pavan Kumar
- Licensing Officer: Giles, David
Immersive VR Platform for Human Reliability Assessment for Physical Security
TS-073103 —
Physical protection remains a major driver of nuclear plant operations and maintenance costs, yet current security risk models rely on conservative assumptions and sparse empirical data on how defenders and operators actually behave under extreme threat. They rarely capture errors of commission, k…
- College: College of Engineering (COE)
- Inventors: Smidts, Carol; Dechasuravanit, Atitarn; Diao, Xiaoxu; Olatubosun, Samuel; Rownak, Md Ragib; Shafieezadeh, Abdollah; Yilmaz, Alper; Zhao, Yunfei
- Licensing Officer: Giles, David
Propagation-Based Fault Detection and Sensor Optimization for Complex Industrial Systems
TS-072175 — The Need
Modern industrial and energy systems are increasingly complex, making timely fault detection and discrimination critical for safety, reliability, and cost control. Existing fault diagnosis methods often struggle with transient states, require extensive historical data, or lack interpretabil…
- College: College of Engineering (COE)
- Inventors: Smidts, Carol; Diao, Xiaoxu; Li, Boyuan
- Licensing Officer: Giles, David
Efficient Cyclic Redundancy Check Encoding with Low-Complexity LFSR Design
TS-071388 — The Need
Cyclic redundancy checks (CRC) are utilized in digital communication and storage systems for error detection. Current CRC encoding and decoding methods in digital communication and storage systems are complex and require a high gate count, leading to inefficiencies in hardware design. There…
- College: College of Engineering (COE)
- Inventors: Zhang, Xinmiao; Cai, Jiaxuan; Tang, Yok Jye
- Licensing Officer: Giles, David
Thermotropic liquid crystal-based sensors for naked-eye detection of SARS-CoV-2 with ultrahigh sensitivity and selectivity
TS-063069 —
In the wake of the global pandemic caused by SARS-CoV-2, the need for rapid, accurate, and efficient diagnostic methods for respiratory viral infections has become more critical than ever. Traditional diagnostic methods, while reliable, are often time-consuming, labor-intensive, and lack the neces…
- College: College of Engineering (COE)
- Inventors: Wang, Xiaoguang "William"; Qin, Rongjun; Rather, Adil; Xu, Yang
- Licensing Officer: Randhawa, Davinder
Method for Prediction of Artificial Intelligence Model Generalizability for Unseen Data
TS-063039 — Medical-based AI systems have seen increased use in recent years across a range of applications (e.g., diagnostics, prognostics, treatment response prediction). Their widespread adoption by the medical community is still restricted, primarily due to their limited ability to realize a high degree of …
- College: College of Medicine (COM)
- Inventors: Dikici, Engin; Nguyen, Xuan; Prevedello, Luciano
- Licensing Officer: Hampton, Andrew
Visual Function Mapping Technology: Enhancing Vision Care and Diagnostics
TS-062335 — The Need: In the field of ophthalmology and vision care, there is a critical need for accurate and comprehensive measurements of visual function over the entire visual field. Conditions such as glaucoma, age-related macular degeneration (AMD), diabetes, stroke, pituitary disease, brain tumors, and n…
- College: College of Arts & Sciences
- Inventors: Lu, Zhong-Lin; Lesmes, Luis; Xu, Pengjing "PJ"; Yu, Deyue
- Licensing Officer: Dahlman, Jason "Jay"
A Model Based Assessment Approach and an Automation Environment for Qualification of Embedded Digital Devices
TS-042856 — A Framework and Automatization process designed to determine the functiona
lity of Embedded Digital Devices.
As our technology becomes increasingly complex, so does the quantity and variation of the Embedded Digital Device [EDD] components that are required within the project. Because not every device is made perfectly to specifications due to a propagation of random error, it is important to have a dive…
- College: College of Engineering (COE)
- Inventors: Smidts, Carol; Diao, Xiaoxu; Li, Boyuan
- Licensing Officer: Giles, David