Available Technologies
# of Displayed Technologies: 10 / 23
Applied Category Filter (Click To Remove): Artificial Intelligence & Machine Learning
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; Arrey, Evelyn; Booth, Matthew; Liu, Enhao; Mashayekhi, Medhi
- Licensing Officer: Zinn, Ryan
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; Liu, Enhao
- Licensing Officer: Zinn, Ryan
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: Zinn, Ryan
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
An information extraction, enrichment, and caching framework for augmented reality applications
TS-063109 — The Need
In the age of augmented reality (AR), there's a growing opportunity for a comprehensive solution that facilitates the seamless exploration of real-world data through camera-based AR applications. These applications require the ability to extract, cache, and enrich information, enhancin…
- College: College of Engineering (COE)
- Inventors: Nandi, Arnab; Burley, Codi; Sarkhel, Ritesh "Ritesh"
- Licensing Officer: Mess, David
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
Method and system for generating data-enriching augmented reality applications from a domain-specific language
TS-063032 — The Need
In the age of augmented reality (AR), there's a growing opportunity for a comprehensive solution that facilitates the seamless exploration of real-world data through camera-based AR applications. These applications require the ability to extract, cache, and enrich information, enhancin…
- College: College of Engineering (COE)
- Inventors: Nandi, Arnab; Burley, Codi; Sarkhel, Ritesh "Ritesh"
- Licensing Officer: Mess, David
