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Researcher
- Omer Onar
- Subho Mukherjee
- Vivek Sujan
- Mostak Mohammad
- Vandana Rallabandi
- Rafal Wojda
- Shajjad Chowdhury
- Erdem Asa
- Burak Ozpineci
- Emrullah Aydin
- Isabelle Snyder
- Jon Wilkins
- Prasad Kandula
- Adam Siekmann
- Ali Riza Ekti
- Emilio Piesciorovsky
- Gui-Jia Su
- Raymond Borges Hink
- Suman Debnath
- Veda Prakash Galigekere
- Yaosuo Xue
- Aaron Werth
- Aaron Wilson
- Alex Plotkowski
- Christopher Fancher
- Elizabeth Piersall
- Eve Tsybina
- Fei Wang
- Gary Hahn
- Hong Wang
- Hyeonsup Lim
- Isaac Sikkema
- Jin Dong
- Joseph Olatt
- Kunal Mondal
- Lingxiao Xue
- Mahim Mathur
- Marcio Magri Kimpara
- Mingyan Li
- Nils Stenvig
- Oscar Martinez
- Ozgur Alaca
- Peter L Fuhr
- Phani Ratna Vanamali Marthi
- Praveen Kumar
- Sam Hollifield
- Sreenivasa Jaldanki
- Sunil Subedi
- Viswadeep Lebakula
- Yarom Polsky
- Yonghao Gui

Real-time tracking and monitoring of radioactive/nuclear materials during transportation is a critical need to ensure safety and security. Current technologies rely on simple tagging, using sensors attached to transport containers, but they have limitations.

Stability performance of interconnected power grids plays crucial roles on their secure operation to prevent cascading failure and blackout.

This invention proposes a Honeycomb-DD coupling structure that addresses the shortcomings of the conventional honeycomb coil array and gathering the advantage of DD and honeycomb designs advantages in a single design.

Additively manufacturing of the windings with a conductor distributed in the cross-section according to the Hilbert curve provides many benefits as it allows for the reduction of the high-frequency losses due to the reduction of the effective winding conductor size.

Wireless charging systems need to operate at high frequency, at or near resonance, to maximize power transfer distance and efficiency. High voltages appear across the inductors and capacitors. The use of discrete components reduces efficiency, increases system complexity.

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.

The disclosed technologies are directed to the smart control of a system that integrates underground TES into geothermal heat pumps.

Technologies directed to a multi-port autonomous reconfigurable solar power plant are described.