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
Vision System Using MDP-Based Tracking for Automated Dimensional Analysis
TS-068440 —
Accurate measurement of physical attributes, such as dimensions, alignments, and surface features, is essential for ensuring quality and consistency across industries. Traditional measurement methods, often reliant on manual tools and human oversight, are time-intensive, prone to errors, and lac…
- College: College
of
Engineering
(COE)
- Inventors: Allen, Theodore; Rodriguezbuno, Ramiro; Zhang, Yifei
- Licensing Officer: Zinn, Ryan
Computational Design of Experiment Framework for Processing of Metal Alloys
TS-067792 — A s
oftware tool for optimizing the manufacturing process for metal alloys.
Metallic alloys are composed of a homogeneous mixture of two or more metals or of metals and nonmetal or metalloid elements to provide specific characteristics or structural properties. Alloys are used in many applications, such as aircraft, offshore drilling, automobiles, and others.
Obtaining t…
- College: College
of
Engineering
(COE)
- Inventors: Alexandrov, Boian; Forquer, Matthew; Jang, Eun; Luo, Yuxiang; Stewart, Jeffrey
- Licensing Officer: Zinn, Ryan
AIDRIN (AI Data Readiness Inspector)
TS-067116 — AIDRIN (AI Data Readiness Inspector) is a system designed to comprehensively evaluate datasets through a diverse range
of metrics, giving an overall perspective on their readiness for AI applications.
In the contemporary digital landscape, the explosive growth in data generation has created a pressing need for efficient and scalable database systems. Traditional databases struggle with the increasing volume, variety, and velocity of data, leading to performance bottlenecks, high operational cos…
- College: College
of
Engineering
(COE)
- Inventors: Byna, Suren; Hiniduma, Kaveen
- Licensing Officer: Zinn, Ryan
Unveiling the Nanoscale: Breakthrough Analytical Speed of Real-Time Super-Resolution Microscopy and Beyond
TS-066926 — This Ohio State University s
oftware innovation
offers groundbreaking analytical speed and automation
of Single-Molecule Localization Microscopy (SMLM) as well as analysis
of 3D data and images extending beyond the field
of microscopy. Our technology
offers real-time spatial analysis in continuous and discrete space, enabling unprecedented speed and efficiency in data processing that translates into faster decision-making, high-throughput screening capabilities, and broad applicability beyond traditional microscopy.
Single-molecule localization microscopy (SMLM) describes a family of fast-evolving, powerful imaging techniques that dramatically improve spatial resolution over standard, diffraction-limited microscopy techniques and can image biological structures at the molecular scale. SMLM can now be performe…
- College: College
of
Engineering
(COE)
- Inventors: Soltisz, Andrew; Veeraraghavan, Rengasayee
- 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
Automatic Mechanical Assembly Loops/Stacks Detection
TS-064578 — This s
oftware solution revolutionizes the process
of tolerance stack analysis in mechanical assemblies. It automatically detects and extracts tolerance stacks as the foundational step for precise tolerance analysis and schema generation.
This software solution revolutionizes the process of tolerance stack analysis in mechanical assemblies. It automatically detects and extracts tolerance stacks as the foundational step for precise tolerance analysis and schema generation.
The Need
Analyzing tolerance stacks in mechanical assembl…
- College: College
of
Engineering
(COE)
- Inventors: Haghighi, Payam; Shah, Jami
- Licensing Officer: Randhawa, Davinder
Systems and Methods of Reminding Drivers of the Stalking Vehicles on the Road
TS-063308 —
In today’s world, privacy and safety are paramount. Being followed by other vehicles during driving can be unnerving and potentially dangerous, leading to privacy leakage and even significant traffic accidents. There is a pressing need for a solution that can detect abnormal following vehicl…
- College: College
of
Engineering
(COE)
- Inventors: Sun, Wei; Athreya, Kannan
- Licensing Officer: Randhawa, Davinder
Vulnerability and Attackability analysis of automotive controllers using structural model of the system
TS-063239 — The Ohio State University has developed a vulnerability analysis technique for connected and autonomous vehicles that assesses the vulnerability and attackability of the automotive controllers to determine the security of the system.
The Need
Automated vehicle technologies improve safety, assis…
- College: College
of
Engineering
(COE)
- Inventors: Renganathan, Vishnu; Ahmed, Qadeer
- Licensing Officer: Ashouripashaki, Mandana
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
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
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
Counterattacking Smart Contract Exploits: An Active Defense Approach
TS-063027 — The Need
Smart contracts have revolutionized the way transactions are conducted, but their unique nature makes them susceptible to exploitation. Despite extensive efforts in vulnerability identification, exploitable vulnerabilities persist, resulting in substantial financial losses. To mitigate thi…
- College: College
of
Engineering
(COE)
- Inventors: Lin, Zhiqiang; Morales, Marcelo
- Licensing Officer: Mess, David
Fresh Caching of Dynamic Content: Algorithm and Implementation
TS-063024 — The Need
In today's data-driven world, efficient caching of dynamic content is crucial for delivering timely and responsive services. Conventional caching methods struggle to adapt to frequent updates in the back-end database, leading to suboptimal system costs and decreased user satisfaction. …
- College: College
of
Engineering
(COE)
- Inventors: Abolhassani, Bahman; Eryilmaz, Atilla
- Licensing Officer: Hampton, Andrew
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
3DScope: Detecting 3D Model Clones
TS-057129 — Algorithm for extracting 3D models, indexing them using a value-insensitive normalization algorithm, and comparing the model indexes to detect cloned 3D models.
The unauthorized copying of 3D models robs designers of property, reduces innovation going into the creation of 3D models, creates liability for entities unknowingly using copied models, and indicates a lapse in IP security. With the vast amount of 3D assets in use, it is infeasible for humans to …
- College: College
of
Engineering
(COE)
- Inventors: Zuo, Chaoshun; Lin, Zhiqiang
- Licensing Officer: Mess, David
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