Global Arc

Fossil fuel combustion is the largest contributor to anthropogenic pollutant emissions. Thus the energy security and the impact on climate change require cleaner transportation fuels. In this course a broad perspective ranging from the recent development of green fuels, through active combustion control and sensing using in-situ laser spectroscopic techniques, to global environmental impacts will be discussed. The course will cover both fundamentals such as physics of fuel combustion or light-matter interactions in combustion diagnostics as well as will review pollutant chemistry, transport, and the global standards of emission regulations.

The course covers basic theories of modern machine learning: 1. statistical learning theory: generalization, uniform convergence, Rademacher complexity, VC theory, reproducing Hilbert kernel space and their applications on simple classification/regression models; 2. optimization theory: gradient descent, stochastic gradient descent and their convergence analyses for convex functions, nonconvex functions 3. deep learning theory: basic approximation, optimization and generalization results for deep neural networks; 4. reinforcement learning theory: MDP, Bellman equations, planning, and sample complexity results for value iteration/Q-learning.

The course is an introduction to the theoretical foundations of machine learning. A variety of classical and recent results in machine learning and statistical analysis including: Bayesian classification, regression, regularization, sparse regression, support vector machines, kernels, neural networks and gradient descent.

An introduction to the properties of solids. Theory of free electrons--classical and quantum. Crystal structure and methods of determination. Electron energy levels in a crystal: weak potential and tight-binding limits. Classification of solids--metals, semiconductors, and insulators. Types of bonding and cohesion in crystals. Lattice dynamics, phonon spectra, and thermal properties of harmonic crystals. Prerequisite: 342, or PHY 208 and 305, or permission of instructor.

Electronic structure of solids. Electron dynamics and transport. Semiconductors and impurity states. Surfaces and interfaces. Dielectric properties of insulators. Electron-electron, electron-phonon, and phonon-phonon interactions. Anharmonic effects in crystals. Magnetism. Superconductivity. Alloys. Three hours of lectures. Prerequisites: 441 or equivalent.

The physics and technology of solid-state electronic devices. Covers electronic structure of semiconductors, energy bands and doping, followed by discussion of carrier transport by drift and diffusion and recombination/generation. Detailed analysis of p-n junctions, bipolar transistors and field effect transistors. Survey of a wide range of devices, including photodetectors, solar cells, light-emitting diodes and semiconductor lasers, highlighting contemporary concepts such as thin film electronics and 2D semiconductors.

This course will investigate the technology and underlying science of micro-and nano-fabrication, which are the methods used to build billions of electronic and optoelectronic devices on a chip, as well as general small sensors and actuators generally referred to as micro-electromechanical systems (MEMS). The general approach involves deposition modification, and patterning of layers less than one-micrometer thick, hence the generic term 'thin-film' processing. Topics to be covered film deposition and growth via physical and chemical vapor deposition, photolithography, pattern transfer, plasma-processing, ion-implantation, and vacuum science.

The course will discuss electromagnetism (mostly classical electromagnetism) and its applications in modern day science and technology, with an emphasis on sensing and communication. The emphasis will be on fundamental theories and how they influence practical application ranging from biosensing, to modern day wireless, wire line communication and radar architectures along with multiple antenna array systems.

Bioelectronics plays an increasingly vital role in fundamental research, therapeutics, and everyday life. This course will explore the basic principles of bioelectronics and their applications in biomedicine. The first part of the course will cover the fundamentals of bioelectricity, different types of biosensors, and related signal processing. The second part of the course will introduce the interface between bioelectronics and biological systems and the applications of bioelectronics devices in neuroscience, cardiology, tissue engineering, and wearable technologies.

This course gives a general introduction to biological and biomedical imaging. Topics covered include basic imaging theory, microscopy, tomography, and imaging through tissue. Both physical and computational imaging will be covered, across a variety of different modalities (including visible light, x-ray, MRI, and ultrasound). The gaps between current technology and limits suggested by information theory will be discussed.