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
SPARKLE: Machine Learning Platform for Rapid Organic Battery Material Discovery
TS-071386 — The Need
The search for sustainable, high-performance battery materials is hindered by reliance on finite metal-based resources and slow, trial-and-error development cycles. Organic electrode materials (OEMs), composed of earth-abundant elements, offer a more sustainable path but present challenges …
- College: College of Engineering (COE)
- Inventors: Paulson, Joel; Muthyala, Madhav; Park, Jay; Sorourifar, Farshud; Zhang, Shiyu
- Licensing Officer: Mess, David
Efficient Machine Learning Prediction of Solvation Thermodynamics
TS-071267 — The Need
Modeling solvent effects on catalytic surfaces is critical for designing industrial processes like biomass conversion, fuel synthesis, and electrocatalysis. Traditional multiscale simulations combining density functional theory (DFT) and molecular dynamics (MD) offer accuracy but are comp…
- College: College of Engineering (COE)
- Inventors: Getman, Rachel; Punyapu, Rohit; Shi, Jiexin
- Licensing Officer: Randhawa, Davinder
AI-Driven Intersection Safety System for Vulnerable Road User Protection
TS-070954 — The Need
Intersections are among the most dangerous areas on U.S. roadways, accounting for approximately 25% of traffic fatalities and nearly half of all injuries annually. Vulnerable Road Users (VRUs), including pedestrians and cyclists, face increasing risk due to complex traffic dynamics and limi…
- College: College of Engineering (COE)
- Inventors: Yurtsever, Ekim; Giuliani, Michele; Rizzoni, Giorgio
- Licensing Officer: Ashouripashaki, Mandana
GPS Independent Lane Level Vehicle Localization
TS-069654 — Technology bundle containing T2025-148 and T2024-150.
The Need
Reliable vehicle localization is critical for autonomous and human-driven vehicles, especially in GPS-denied environments such as dense urban areas, tunnels, and off-road farms and construction sites. Current localization methods relying solely on GPS are prone to signal loss and inaccurac…
- College: College of Engineering (COE)
- Inventors: Javed, Nur Uddin; Ahmed, Qadeer
- Licensing Officer: Ashouripashaki, Mandana
SyMANTIC – Novel Symbolic Regression to Discover Accurate Models from Data
TS-069523 — The Need
In many scientific and industrial fields, there is a critical need for interpretable and accurate models that can be derived from complex datasets. Traditional machine learning methods often produce black-box models that lack transparency and interpretability, making it difficult to unders…
- College: College of Engineering (COE)
- Inventors: Muthyala, Madhav Reddy; Paulson, Joel; Sorourifar, Farshud
- Licensing Officer: Randhawa, Davinder
Joint Activity Testing (JAT): A Testing & Evaluation Methodology for Human-Machine Teams
TS-068443 —
In high-stakes industries, the integration of humans and advanced automation systems demands evaluation methods that reliably predict performance under varying challenges. Current testing methods often focus on individual components, failing to assess how human-machine teams operate as a unit, par…
- College: College of Engineering (COE)
- Inventors: Morey, Dane; Rayo, Michael
- Licensing Officer: Giles, David
Optimal and Pure Leaf Classification Trees for Machine Learning (ML) Decision-Making
TS-067550 — A method to improve the performance and accuracy of ML-based decision trees.
Decision trees are popular machine learning (ML) methods used in classification and regression problems, and they have numerous applications in the real world. Various industries use decision trees to help decide strategies, investments, and operations. In addition, they are used in healthcare to he…
- College: College of Engineering (COE)
- Inventors: Allen, Theodore "Ted"; Arrey, Evelyn; Booth, Matthew; Liu, Enhao; Mashayekhi, Medhi
- Licensing Officer: Giles, David
A Cybersecurity Vulnerability Prioritization System Including Identifying "Super-Critical" Vulnerabilities, predicting "Dark Host" Vulnerabilities, and Addressing Economic Costs
TS-066063 — Our cybersecurity vulnerability maintenance system stands as a pillar of modern security strategy, transforming reactive security measures into a preemptive defense mechanism. This integration of technology and economics ensures that your most critical assets are protected efficiently and effectively, making it an invaluable tool for any organization serious about security.
In today’s hyper-connected world, the escalation in cyber threats poses significant risks to organizational data and systems. Vulnerabilities within network infrastructures can lead to massive security breaches, as demonstrated by incidents like the 2017 Equifax hack. Effective vulnerability…
- College: College of Engineering (COE)
- Inventors: Allen, Theodore "Ted"; Liu, Enhao
- Licensing Officer: Giles, David
SimulationAI -- AI-Enabled Software Solution for Physics-Based Simulations
TS-066058 — By adopting our AI-driven solution, engineering teams can achieve more in less time, push the boundaries of innovation, and significantly cut down costs, all while maintaining or increasing the reliability and accuracy of their structural and material analysis. This is not just an evolution in FEM technology—it's a revolution.
In an era where precision and efficiency drive the success of engineering projects, the finite element method (FEM) remains indispensable but is burdened by high operational and computational costs. These costs often lead to overlooked uncertainty factors, suboptimal designs, and significant finan…
- College: College of Engineering (COE)
- Inventors: Soghrati, Soheil; vemparala, Balavignesh; Yang, Ming
- Licensing Officer: Giles, David
Deep Reservoir Computers for Precise Chaos Control
TS-065447 — The Need:
In the realm of nonlinear control engineering, managing systems with chaotic dynamics poses a significant challenge. Conventional methods often fall short in achieving precise control over such systems due to their complexity and unpredictability. There's a pressing need for a solutio…
- College: College of Arts & Sciences
- Inventors: Canaday, Daniel; Gauthier, Daniel; Griffith, Aaron
- Licensing Officer: Dahlman, Jason "Jay"
Reservoir Computing: Revolutionizing Rapid Processing
TS-065446 — The Need: In today's fast-paced commercial landscape, there's an increasing demand for rapid processing of complex data sets. Traditional computing methods often struggle to keep pace with real-time requirements, leading to inefficiencies and missed opportunities. Addressing this need for sw…
- College: College of Arts & Sciences
- Inventors: Canaday, Daniel; Gauthier, Daniel; Griffith, Aaron
- Licensing Officer: Dahlman, Jason "Jay"
A Regularized Conditional GAN for Posterior Sampling in Inverse Problems
TS-063238 — A novel regularization technique applicable for medical imaging applications that leverages conditional generative adversarial networks (cGANs) to generate reconstructed images in significantly shorter timeframes.
The Need
Several techniques are used for image reconstruction in the medical aren…
- College: College of Engineering (COE)
- Inventors: Bendel, Matthew; Ahmad, Rizwan; Schniter, Philip
- Licensing Officer: Hampton, Andrew
Hybrid Collaborative Filtering Methods for Recommending Search Terms to Clinicians
TS-063237 — Electronic Health Records (EHR) are used in over 88% of all US medical clinics to improve care and streamline data. In addition, they enable sharing of data to multiple providers dealing with the same patient, thereby enhancing efficiency and care.
The Need
In the last decade, medical practices…
- College: College of Medicine (COM)
- Inventors: Ning, Xia; Peng, Bo; Ren, Zhiyun
- Licensing Officer: Hampton, Andrew
Convolutional Neural Network to Assess Phayngeal and Laryngeal Pathology and Function on Nasopharyngolaryngoscopy
TS-063154 — Worldwide, 686,000 new head and neck (H&N) cancers are diagnosed yearly, and 375,000 people will die annually. Human papillomavirus (HPV) is responsible for an increasing subset of H&N malignancies called oropharyngeal squamous cell carcinomas (OPSCC). Although it has a better prognosis than…
- College: College of Engineering (COE)
- Inventors: Krening, Samantha; Gifford, Ryan; Jhawar, Sachin; VanKoevering, Kyle
- Licensing Officer: Hampton, Andrew
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
Auditing Fairness Online through Interactive Refinement
TS-063038 — The Need
In the era of machine learning, high-stakes decisions are increasingly being made by black box models, leading to concerns about accountability and fairness. These models can exhibit inherent biases, raising the need for a system that ensures accountability and fairness in decision-making …
- College: College of Engineering (COE)
- Inventors: Maneriker, Pranav; Burley, Codi; Parthasarathy, Srinivasan
- Licensing Officer: Mess, David
Novel Deep Learning Model for Reconnaissance of Infrastructure on Drones
TS-063007 — The Need
In disaster-stricken areas, timely and accurate reconnaissance is paramount for effective response and recovery efforts. Traditional methods of assessing damage to critical infrastructure, such as power distribution poles, often involve time-consuming manual inspections, leading to delays …
- College: College of Engineering (COE)
- Inventors: Shafieezadeh, Abdollah; Bagheri Jeddi, Ashkan
- Licensing Officer: Giles, David
Transforming PAH Management with PHORA: Empowering Physicians for Better Patient Care
TS-062764 — The Pulmonary Hypertension Outcomes Risk Assessment (PHORA): a PAH risk stratification tool.
Pulmonary Arterial Hypertension (PAH) demands precise risk stratification for effective patient management. Clinical decision support tools can help inform treatment decisions made by physicians and other healthcare providers, usually at the point of care.
The Need
Current methods for assistin…
- College: College of Medicine (COM)
- Inventors: Benza, Ray; Lin, Shili; Mathur, Puneet
- Licensing Officer: Hampton, Andrew
AI Software for Complex NMR Spectra Analysis
TS-062576 — The Need
Like a molecular “fingerprint”, NMR spectra provide valuable insights into the properties and structures of molecular compounds. However, analyzing and interpreting NMR spectra is inherently challenging as comprehensive and explicit identification of a compound is tedious and t…
- College: College of Arts & Sciences
- Inventors: Li, Da-Wei; Bruschweiler, Rafael
- Licensing Officer: Panic, Ana
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