GRAFT-Stereo: Cost-Effective, High-Accuracy 3D Depth Perception
TS-071747 — The Need
High-accuracy 3D depth perception is critical for autonomous systems, but current stereo camera methods falter in complex outdoor environments. While LiDAR can improve accuracy, its effectiveness plummets when using sparse data from affordable, lower-beam sensors, making high performance …
- College: College of Engineering (COE)
- Inventors: Chao, Wei-Lun "Harry"; Asare Boateng, Jeffery; Jeon, Sooyoung; Krishna, Sanjay; Musah, Tawfiq; Yoo, Jinsu
- Licensing Officer: Randhawa, Davinder
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
Motion-Guided Deep Image Prior (M-DIP) for Dynamic Image Reconstruction in Cardiovascular MRI
TS-069527 — The Need
Cardiovascular MRI (CMR) data acquisition is often time-consuming and relies on complex reconstruction methods that do not fully exploit the spatial and temporal structure of CMR data. There is a need for a more efficient, unsupervised approach that can accelerate CMR imaging while maintai…
- College: College of Engineering (COE)
- Inventors: Ahmad, Rizwan; Chen, Chong; Sultan, Muhammad
- Licensing Officer: Randhawa, Davinder
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
Environmental Damage Model for Predicting Mechanism Transition under Time-Dependent Crack Growth Conditions.
TS-065131 — Metal fatigue is the weakened condition induced in metal parts by repeated normal stresses or loadings, which causes the initiation and expansion of cracks, fractures, and eventual metal part failure. Battelle Inc. estimates that material fatigue, including metal fatigue, causes 80-90% of structural…
- College: College of Engineering (COE)
- Inventors: Viswanathan, Gopal; Mills, Michael; Mills, David
- Licensing Officer: Randhawa, Davinder
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
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
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
Golden-shift Ordered Cartesian sampling (GOC) for Dynamic MRI (Free-breathing Accelerated MRI Portfolio)
TS-062486 — Magnetic Resonance Imaging (MRI) is a versatile noninvasive imaging tool that is routinely used to evaluate many diseases and conditions. MRI offers exquisite soft tissue contrast and high spatial resolution to enable comprehensive structural and functional assessment of internal organs. Recent innovations in data acquisition and processing can expand the clinical applications of MRI.
The Need
A major limitation of MRI is slow data acquisition, which can compromise patient comfort, drive up costs, and increase susceptibility to motion. The clinical adoption of volumetric imaging for musculoskeletal and neuro applications, the growing
demand for free-breathing real-time imaging …
- College: College of Engineering (COE)
- Inventors: Ahmad, Rizwan; Jin, Ning; Liu, Yingmin; Simonetti, Orlando
- Licensing Officer: Randhawa, Davinder
Vehicle-in-Virtual-Environment Method for Autonomous Driving System Development and Evaluation
TS-054005 — This technology is a Vehicle-in-Virtual Environment (VVE) method for testing and evaluating Autonomous Vehicles (AV). The VVE approach is a safe, reliable, repetitive, and scalable method of testing AVs, decreasing the risks and costs of testing AVs on public roads.
The demand for autonomous vehicles continues to grow as companies and cities realize the effect on the costs, safety, and efficiency that AVs have on everyday lives. Initiatives such as MCity in Detroit, Michigan, and Smart City in Columbus, Ohio, show a strong commitment to the development of aut…
- College: College of Engineering (COE)
- Inventors: Guvenc, Levent; Aksun Guvenc, Bilin
- Licensing Officer: Randhawa, Davinder
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