Global Arc

With foundation built upon statistical and algebraic learning theory, this course offers an in-depth learning experience on machine learning for (big) data analysis for senior and graduate students in electrical engineering, computer science, and applied statistics - with some exposure to algebra and statistics. It covers various kernel-based unsupervised and supervised learning models and provides an integrated understanding of the mathematical theory and their potential applications. With the accompanied software learning laboratories. It also demonstrates how kernel learning models work for pattern recognition and data analysis.

How can we decode what people are thinking by looking at their brain scans? Over the past several years, researchers have started to address this question by applying sophisticated pattern-classification algorithms to patterns of functional MRI data, with the goal of decoding the information that is represented in the subject's brain at a particular point in time. In lectures, students will learn about cutting-edge techniques for finding meaningful patterns in large, noisy datasets; in weekly computer labs, students will use these techniques to gain insight into fMRI datasets.

Power electronics circuits are critical building blocks in a wide range of applications, ranging from mW-scale portable devices, W-scale telecom servers, kW-scale motor drives, to MW-scale solar farms. This course is a design-oriented course and will present fundamental principles of power electronics. Topics include: 1) circuit elements;2) circuit topology; 3) system modeling and control; 4) design methods and practical techniques. Numerous design examples will be presented in the class, such as solar inverters, data center power supplies, radio-frequency power amplifiers, and wireless power transfer systems.

The lectures will cover: (1) Basic principles of digital signal processing. (2) Design of digital filters. (3) Fourier analysis and the fast Fourier transform. (4) Roundoff errors in digital signal processing. (5) Applications of digital signal processing.

This course will present data analytics perspectives of electric power systems. The course offers an introduction to the basic concepts of power system operation and planning, along with necessary theories and methods in optimization. Topics include modeling and optimization of power networks, power flow analysis, state estimation and observability, bad data detection, introduction to the electricity market, and selected topics in smart grids. Strong emphasis will be placed on developing practical techniques to solve convex and stochastic optimization problems.

An introduction to lossless data compression algorithms, modulation/demodulation of digital data, error correcting codes, channel capacity, lossy compression of analog and digital sources. Three hours of lectures. Prerequisites: 301, ORF 309.

Introduction to the basic theory and techniques of two- and three-dimensional image processing. Topics include image perception, 2-D image transforms, enhancement, restoration, compression, tomography and image understanding. Applications to HDTV, machine vision, and medical imaging, etc. Three hours of lectures, one laboratory.

This course takes up the twentieth-century Vietnam wars as a subject of international history, with a cast of actors ranging from Vietnam and the United States to France, China, and the Soviet Union. It is a subject that sheds light on some of the most significant dynamics of political, economic, and social change at work in the twentieth-century world. Themes include self-determination and imperialism, colonialism and counterinsurgency, social revolution and state control, liberalism and communism, policymaking and diplomacy, memory and legacy, and literature and history.

The 1980s was one of the critical decades in twentieth-century U.S. history and, even now, one of the most controversial. The seminar is designed to explore the key shifts in economy, politics, society, and ideas that marked the decade, from the stagflation crisis of the late 1970s to the collapse of the cold war and emergence of a "culture war " at home. Using a mix of primary documents and analytical readings, our task will be to treat this period as history: to map the actual contours of change, to sort through competing explanations for the era's transformations, and to think critically about its legacy.

Today, only a dreamer like John Lennon can "imagine no possessions." However, the idea of society without property has recurred with persistent regularity since the beginning of the eighteenth century. Property has not always been what it seems today, a natural, even inevitable feature of human society. It has a history, and this course will trace that history, showing the ways in which events, politics, and culture shaped property regimes and how property regimes in turn shaped the way people lived.