Available Technologies
# of Displayed Technologies: 10 / 30
Applied Category Filter (Click To Remove): Algorithms
Computational Design of Experiment Framework for Processing of Metal Alloys
TS-067792 — A software 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 software 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 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.
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
Three-dimensional cellular automation codes for solidification microstructure and porosity simulation of multi-component alloys
TS-063911 —
Porosity formation during the solidification of aluminum-based alloys, induced by hydrogen gas and alloy shrinkage, presents a significant challenge for industries relying on high-performance solidification products such as castings, welds, and additively manufactured components. This issue advers…
- College: College of Engineering (COE)
- Inventors: Luo, Alan; Gu, Cheng
- Licensing Officer: Zinn, Ryan
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; Srinivasan, 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
