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Course Criteria
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0.00 - 4.00 Credits
Introduction to the topics and methods of research in electronic materials and devices, providing an overview of current research of the faculty in electronic materials and devices, and in optical and optoelectronic engineering.
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0.00 - 4.00 Credits
Course covers impurity states and impurity band formation in doped semiconductors. The evolution of optical, dielectric, transport, magnetic and thermodynamic properties as a function of dopant concentration, from the insulating regime at low doping, through the metal insulator transition, to the metallic phase, are studied. Topics include hopping transport, band tails, Coulomb gap, weak localization and the scaling theory of the localization transition.
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0.00 - 4.00 Credits
Introduction to nonlinear optics, second harmonic generation, parametric amplification and oscillation, the electro-optic effect, third order nonlinearities, phase-conjugate optics, photorefractive nonlinear optics, solitons.
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0.00 - 4.00 Credits
This is an entry level graduate course concentrated on physical foundations of modern quantum electronic devices that have sprung up in the last decade and will become the mainstay of electronic and photonic systems. Understanding of functionality of these devices calls for a deeper comprehension of the underlying quantum theories. Examples of the topics covered: nano-lasers, plasmonics, graphene electronics and micromechanics, single electron transistors, and other topics selected by the students. The course will include students¿ presentations on topics of their choice.
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0.00 - 4.00 Credits
Qn overview of several approaches to implementing quantum information and computation, touching briefly on quantum algorithms, but the main focus being physical systems. In particular, the course discusses what makes a good quantum system, the physics behind the leading implementations, and the limitations on each. Topics covered will include: superconducting qubits, electron and nuclear spin qubits, and ion trap qubits, as well as descriptions of gate-based, adiabatic, and topologically protected quantum architectures.
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0.00 - 4.00 Credits
The course will cover machine learning techniques & applications. Machine learning techniques topics: a) adaptive techniques for feature selection & dimension reduction, b) unsupervised cluster discovery: K-means, SOFM, hierarchical clustering, c) supervised classifiers e.g. linear discriminant analysis (LDA), support vector machines, & d) kernel-based clustering/classification techniques. Genomic and multimedia applications will be explored.
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0.00 - 4.00 Credits
Sources of power consumption; simulation power analysis, probabilistic power analysis; circuit and logic level power optimization; power analysis and optimization at the register-transfer, behavior and system levels; power management; software power estimation and optimization; hardware-software co-synthesis for low power.
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0.00 - 4.00 Credits
Current topics in trustworthy computing, especially hardware-enabled trust and security. Topics include enabling hardware to thwart attacks (e.g., with randomization), measuring and characterizing normal software-hardware behavior, hardware that does not leak information, building cryptographic support into computers, dynamic information flow tracking, building resilient computers that operate under both faults and attacks, multicore security, secure virtual machines and secure cloud storage.
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0.00 - 4.00 Credits
Course covers key research and industry efforts in Green Information Technology. Computing systems face increasing challenges in maintaining performance while improving energy-efficiency. These problems are particularly pressing in the data centers used by Google and other internet services. Discussion-oriented class focuses on in-depth analysis of research papers and other primary materials. Final project/paper required. Juniors, Seniors, and Graduate students from ELE, COS, and related fields welcome.
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0.00 - 4.00 Credits
This "hands-on" practical course introduces students to the analysis and actions required to launch a successful high tech company. Using several conceptual frameworks and analytical techniques, it addresses the challenges of evaluating technologies for commercial feasibility, determining how best to launch a new venture, attracting the resources needed to start a company (e.g. people, corporate partners, and venture capital), preparing comprehensive business plans, structuring business relationships, and managing early stage companies toward "launch velocity" and sustainable growth.
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