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Recent advances in engineering science have led to new classes of medical devices with emergent mechanical, electrical, and thermal properties that offer new opportunities for interfacing with living cells. I will discuss conceptual advances in microfabrication, device physics, power transfer and microscale transport phenomena that enable novel biosensors and cell delivery systems, with an emphasis […] |
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Although machine intelligence is taking over the world, its current digital electronic platform is very inefficient in terms of energy consumption. Switching to analogue computation, which function more like human brains than digital computers, will allow enhancing the energy efficiency by several orders of magnitude. Optics presents a particularly promising platform for analogue AI; however, […] |
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The rich set of mechanoreceptors found in human skin offers a versatile engineering interface for transmitting information and eliciting perceptions, potentially serving a broad range of applications in patient care and other important industries. Targeted multisensory engagement of these afferent units, however, faces persistent challenges, especially for wearable, programmable systems that need to operate adaptively […] |
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: Generative priors are effective countermeasures to combat the curse of dimensionality, and enable efficient learning and inversion that otherwise are ill-posed, in data science. This talk begins with the classical low-rank prior, and introduces scaled gradient descent (ScaledGD), a simple iterative approach to directly recover the low-rank factors for a wide range of matrix […] |
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Multiferroic micro-electromechanical systems (MEMS) enable small, room temperature, low power magnetic sensing and wireless power transfer (WPT) in biomedical applications. Current biomagnetic sensing relies on sensitive magnetometers like superconducting quantum interference devices (SQUIDs), but their reliance on cryogenic temperatures is undesirable. This thesis presents the theory, design, microfabrication, and characterization of multiferroic MEMS magnetic […]
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Deep learning with neural networks has emerged as a key approach for discovering patterns and modeling relationships in complex data. AI systems powered by deep learning are used widely in applications across a broad spectrum of scales. There are strong needs for scaling deep learning both upward and downward. Scaling up highlights the pursuit of […] |
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Methods from algebraic topology enable simplifications and extensions of fundamental concepts in structural and mechanical engineering. Chief among these tools are cellular sheaves and cosheaves - abstract mathematical data structures over polyhedra and discrete spaces. The homology of cellular cosheaves (and cohomology of cellular sheaves) combines and distills distributed data into the most meaningful algebraic-topological […] |
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Medical electronic devices are an integral part of the healthcare system today and are used in a variety of applications around us. The design of such devices has several stringent requirements, the key being miniaturization, low-power operation, and wireless functionality. In this talk, I will present CMOS-based miniaturized, low-power and wireless biomedical devices in three […] |
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Entrepreneurship Seminar Series: Pathways to Impact This session brings together a panel of current and former faculty and PhDs that have brought their technology to market and have worked in both academia and commerce. Panelists will discuss the opportunities and approaches they took to create companies, leverage experience in academia, and drive research into commercial […] |
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