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Degree in Electrical and Computer Engineering at Carnegie Mellon University in 2022. After my undergraduate degree, I worked as an electrical systems designer for large electrical power and control systems in New York City. I was part of an elite team of engineers conducting short circuit, coordination, and arc flash studies for mission critical clients, including banking data centers in the financial capital of the world. An inband return loss of -13.2dB is obtained with a center frequency of 2.4GHz, while providing 25.8dB of voltage gain and a bandwidth of 300MHz. The amplifier consumes 5mW of power with a 1.2V supply, has a noise figure of 2.43dB, and an input referred third intercept point of -4.5dBm. The amplifier schematic has been realized in Cadence Virtuoso using a 65nm process, and the pre-layout performance has been simulated in SpectreRF.

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  • I’m an electrical engineer with a passion for electronics, signals, and systems.
  • As part of the Energy-Efficient Circuits and Systems Group, I worked on computational data converters and microelectronic circuits such as this Analog Neural Network.
  • While pursuing my masters degree, my renewed focus on analog circuits and data converters led to a concentration on mixed-signal integrated circuit design.

While pursuing my masters degree, my renewed focus on analog circuits and data converters led to a concentration on mixed-signal integrated circuit design. As part of the Energy-Efficient Circuits and Systems Group, I worked on computational data converters and microelectronic circuits such as this Analog Neural Network. My research interests include low power data converters, RF and audio circuits, and brain-inspired machine learning circuits. In this project, I demonstrate how to build and train an artificial analog neural network that can compute common logic functions. I’m an electrical engineer with a passion for electronics, signals, and systems. Degree in Electrical Engineering from the University of New Haven in 2022, and the M.S.

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