News & EventsDepartment Events
Events
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Oct7
EVENT DETAILS
Quantum computing promises to solve some otherwise intractable problems, but there is not yet a generally accepted technology for building a quantum computer. Electrons bound to superfluid helium have been suggested as qubits, utilizing either a motional state or an electron's spin as the qubit. Our work has largely concentrated on spin qubits, which have been calculated to have exceptionally long coherence. A key anticipated advantage of these qubits is that the size scale of the quantum gates can be comparable to that of semiconductor devices, opening the possibility of monolithically integrating the entire computer on one chip. At the same time there is evidence that devices will not require individual tuning since there are no random trapped charges, as one finds in semiconductors. However, we must essentially invent a new technology for controlling these electrons. I will show data on shuttling small packets of electrons around a chip in Charge Coupled Devices (CCD), and above thin He films which we need for small devices. I will also discuss recent experiments on electron confinement in 100nm-scale quantum dots, and pushing the sensitivity of capacitive sensing to near the single-electron level.
TIME Monday, October 7, 2024 at 2:00 PM - 3:00 PM
LOCATION L440, Technological Institute map it
CONTACT Catherine Healey catherine.healey@northwestern.edu EMAIL
CALENDAR Department of Electrical and Computer Engineering (ECE)
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Oct9
EVENT DETAILS
Advances in machine learning (ML) offer unprecedented opportunities for transforming cardiac care, particularly using imaging data. This talk will explore the intersection of ML, health, and cardiac imaging, focusing on how novel methodologies can drive personalized care and improve clinical outcomes. We will discuss the translation of cutting-edge ML techniques, such as deep learning and transformers, into real-world healthcare systems, specifically in the detection and analysis of coronary anatomy. Additionally, the talk will highlight ongoing research into explainable models, adaptive learning algorithms, and the integration of ML into existing clinical workflows. By addressing challenges like data complexity and generalizability, this presentation will shed light on the path forward for developing AI-powered solutions that not only improve diagnosis and treatment planning but also continuously learn from clinical experience to enhance patient outcomes.
TIME Wednesday, October 9, 2024 at 2:00 PM - 3:00 PM
LOCATION L440, Technological Institute map it
CONTACT Catherine Healey catherine.healey@northwestern.edu EMAIL
CALENDAR Department of Electrical and Computer Engineering (ECE)
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Dec7
EVENT DETAILS
Fall classes end
TIME Saturday, December 7, 2024
CONTACT Office of the Registrar nu-registrar@northwestern.edu EMAIL
CALENDAR University Academic Calendar