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Researcher
- Soydan Ozcan
- Xianhui Zhao
- Adam Siekmann
- Alex Roschli
- Dali Wang
- Diana E Hun
- Easwaran Krishnan
- Erin Webb
- Evin Carter
- Halil Tekinalp
- Hong Wang
- Hyeonsup Lim
- James Manley
- Jamieson Brechtl
- Jeremy Malmstead
- Jian Chen
- Joe Rendall
- Karen Cortes Guzman
- Kashif Nawaz
- Kitty K Mccracken
- Kuma Sumathipala
- Mengdawn Cheng
- Mengjia Tang
- Muneeshwaran Murugan
- Oluwafemi Oyedeji
- Paula Cable-Dunlap
- Sanjita Wasti
- Tomonori Saito
- Tyler Smith
- Vivek Sujan
- Wei Zhang
- Zhili Feng
- Zoriana Demchuk

We have developed a novel extrusion-based 3D printing technique that can achieve a resolution of 0.51 mm layer thickness, and catalyst loading of 44% and 90.5% before and after drying, respectively.

This invention is directed to a machine leaning methodology to quantify the association of a set of input variables to a set of output variables, specifically for the one-to-many scenarios in which the output exhibits a range of variations under the same replicated input condi

Estimates based on the U.S. Department of Energy (DOE) test procedure for water heaters indicate that the equivalent of 350 billion kWh worth of hot water is discarded annually through drains, and a large portion of this energy is, in fact, recoverable.

The use of biomass fiber reinforcement for polymer composite applications, like those in buildings or automotive, has expanded rapidly due to the low cost, high stiffness, and inherent renewability of these materials. Biomass are commonly disposed of as waste.

The incorporation of low embodied carbon building materials in the enclosure is increasing the fuel load for fire, increasing the demand for fire/flame retardants.

No readily available public data exists for vehicle class and weight information that covers the entire U.S. highway network. The Travel Monitoring Analysis System, managed by the Federal Highway Administration covers only less than 1% of the US highway network.

We have developed an aerosol sampling technique to enable collection of trace materials such as actinides in the atmosphere.

Pairing hybrid neural network modeling techniques with artificial intelligence, or AI, controls has resulted in a unique hybrid system that creates a smart solution for traffic-signal timing.