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Researcher
- Adam M Guss
- Amit Shyam
- Alex Plotkowski
- Srikanth Yoginath
- Andrzej Nycz
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- Jerry Parks
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- Jovid Rakhmonov
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- Kyle Davis
- Liangyu Qian
- Mengdawn Cheng
- Nance Ericson
- Nandhini Ashok
- Nicholas Richter
- Oluwafemi Oyedeji
- Pablo Moriano Salazar
- Paul Abraham
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- Sunyong Kwon
- Tomas Grejtak
- Tyler Smith
- Varisara Tansakul
- Vincent Paquit
- William Peter
- Xianhui Zhao
- Yang Liu
- Yasemin Kaygusuz
- Ying Yang
- Yiyu Wang
- Yukinori Yamamoto

Mechanism-Based Biological Inference via Multiplex Networks, AI Agents and Cross-Species Translation
This invention provides a platform that uses AI agents and biological networks to uncover and interpret disease-relevant biological mechanisms.

By engineering the Serine Integrase Assisted Genome Engineering (SAGE) genetic toolkit in an industrial strain of Aspergillus niger, we have established its proof of principle for applicability in Eukaryotes.

Currently available cast Al alloys are not suitable for various high-performance conductor applications, such as rotor, inverter, windings, busbar, heat exchangers/sinks, etc.

The invented alloys are a new family of Al-Mg alloys. This new family of Al-based alloys demonstrate an excellent ductility (10 ± 2 % elongation) despite the high content of impurities commonly observed in recycled aluminum.

The lack of real-time insights into how materials evolve during laser powder bed fusion has limited the adoption by inhibiting part qualification. The developed approach provides key data needed to fabricate born qualified parts.

We present a comprehensive muti-technique approach for systematic investigation of enzymes generated by wastewater Comamonas species with hitherto unknown functionality to wards the depolymerization of plastics into bioaccessible products for bacterial metabolism.

A new nanostructured bainitic steel with accelerated kinetics for bainite formation at 200 C was designed using a coupled CALPHAD, machine learning, and data mining approach.

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.

Digital twins (DTs) have emerged as essential tools for monitoring, predicting, and optimizing physical systems by using real-time data.