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Lav R. Varshney - CoursesFall 2009ESD.172/SP.793 - X PRIZE Workshop on Energy
Examines the intersection of incentives and innovation, drawing on economic models, historic examples, and analytic tools to help develop new prize concepts that can generate revolutionary progress in the area of energy.
6.ThG - Graduate Thesis
Program of graduate research leading to the writing of an SM, EE, ECS, PhD, or ScD thesis; to be arranged by the student and an appropriate MIT faculty member.
Spring 20096.981 - Teaching Electrical Engineering and Computer ScienceFor Teaching Assistants in Electrical Engineering and Computer Science, in cases where teaching assignment is approved for academic credit by the department.
Fall 20086.ThG - Graduate Thesis
Program of graduate research leading to the writing of an SM, EE, ECS, PhD, or ScD thesis; to be arranged by the student and an appropriate MIT faculty member.
Spring 2008MAS.964 - Camera Culture
With more than a billion people with networked, mobile cameras in their hands, we are seeing a rapid evolution in activities based on visual exchange. People’s daily activities are increasingly based on pervasive recording and eager consumption of images and video. In this seminar course, we will look at the technical as well the social aspects of this rapidly evolving camera culture.
Fall 2007STS.260 - Introduction to Science, Technology, and Society
Intensive reading and analysis of major works in historical and social studies of science and technology. Introduction to current methodological approaches, centered around two primary questions: how have science and technology evolved as human activities, and what roles do they play in society? Preparation for graduate work in the field of science and technology studies and introduction to research resources and professional standards.
6.ThG - Graduate Thesis
Program of graduate research leading to the writing of an SM, EE, ECS, PhD, or ScD thesis; to be arranged by the student and an appropriate MIT faculty member.
Spring 200718.103 - Fourier Analysis: Theory and Applications
Roughly half the subject devoted to the theory of the Lebesgue integral with applications to probability, and half to Fourier series and Fourier integrals.
6.435 - Theory of Learning and System Identification (Listener)
Mathematical models of systems from observations of their behavior. Time series, state-space, and input-output models. Model structures, parametrization, and identifiability. Non-parametric methods. Prediction error methods for parameter estimation, convergence, consistency, andasymptotic distribution. Relations to maximum likelihood estimation. Recursive estimation; relation to Kalman filters; structure determination; order estimation; Akaike criterion; and bounded but unknown noise models. Robustness and practical issues.
6.ThG - Graduate Thesis
Program of graduate research leading to the writing of an SM, EE, ECS, PhD, or ScD thesis; to be arranged by the student and an appropriate MIT faculty member.
Fall 20066.981 - Teaching Electrical Engineering and Computer ScienceFor Teaching Assistants in Electrical Engineering and Computer Science, in cases where teaching assignment is approved for academic credit by the department.
STS.482 - Science, Technology, and Public Policy
Analysis of issues at the intersection of science, technology, public policy, and business. Cases drawn from antitrust and intellectual property rights; health and environmental policy; defense procurement and strategy; strategic trade and industrial policy; and R&D funding. Structured around theories of political economy, modified to take account of integration of uncertain technical information into public and private decision-making.
Spring 20066.ThG - Graduate Thesis
Program of graduate research leading to the writing of an SM, EE, ECS, PhD, or ScD thesis; to be arranged by the student and an appropriate MIT faculty member.
6.262 - Discrete Stochastic Processes (Listener)
Review of probability and laws of large numbers; Poisson counting process and renewal processes; Markov chains (including Markov decision theory), branching processes, birth-death processes, and semi-Markov processes; continuous-time Markov chains and reversibility; random walks, martingales, and large deviations; applications from queueing, communication, control, and operations research.
6.882 - Advanced Computational Photography
Computational photography is a new field at the convergence of photography, computer vision, image processing, and computer graphics. It leverages the power of digital processing to overcome limitations of traditional photography and it offers unprecedented opportunities for the enhancement and enrichment of visual media. This advanced undergraduate course covers fundamentals and applications of hardware and software techniques, with an emphasis on software methods. The course will emphasize hands-on aspects and the course will culminate into a final project. The goal is to provide students with sufficient backgrounds to implement new solutions to photography challenges and opportunities. Topics include cameras and image formation, image processing and image representations, high-dynamic-range-imaging, human visual perception and color, single view 3D model reconstruction, morphing, data-rich photography, superresolution, image-based rendering.
Fall 20056.ThG - Graduate Thesis
Program of graduate research leading to the writing of an SM, EE, ECS, PhD, or ScD thesis; to be arranged by the student and an appropriate MIT faculty member.
18.100B - Analysis I (Listener)
Covering fundamentals of mathematical analysis: convergence of sequences and series, continuity, differentiability, Riemann integral, sequences and series of functions, uniformity, interchange of limit operations. Shows the utility of abstract concepts and teaches understanding and construction of proofs. Option B is more demanding and is for students with more mathematical maturity; it places more emphasis on point-set topology and n-space.
6.255 - Optimization Methods (Listener)
Introduces the principal algorithms for linear, network, discrete, nonlinear, dynamic optimization and optimal control. Emphasis on methodology and the underlying mathematical structures. Topics include the simplex method, network flow methods, branch and bound and cutting plane methods for discrete optimization, optimality conditions for nonlinear optimization, interior point methods for convex optimization, Newton's method, heuristic methods, and dynamic programming and optimal control methods.
Spring 20056.991 - Research in Electrical Engineering and Computer Science
For Research Assistants in Electrical Engineering and Computer Science, in cases where the assigned research is approved for academic credit by the department.
6.441 - Transmission of Information
Introduction to the quantitative theory of information and its applications to reliable, efficient communication systems. Mathematical definition and properties of information. The source coding theorem, lossless compression of data and optimal lossless coding. Noisy communication channels, channel coding theorem, the source-channel separation theorem, multiple access channels, broadcast channels, Gaussian noise, time-varying channels. Readings from the literature in these topics.
6.451 - Principles of Digital Communications II
Coding for the AWGN channel; the gap to capacity; binary block and convolutional codes; finite fields and Reed-Solomon codes; trellis representations; codes on graphs and iterative decoding; capacity-approaching codes; lattice and trellis codes.
Fall 20046.961 - Introduction to Research in Electrical Engineering and Computer Science
Opportunity to become involved in graduate research, under guidance of a staff member, on a problem of mutual interest to student and supervisor.
6.450 - Principles of Digital Communications I
Communications sources and channels; data compression; entropy, and the AEP; Lempel-Ziv universal coding; scalar and vector quantization; signal space and its representation by sampling and other expansions; aliasing; the Nyquist criterion; PAM and QAM modulation; Gaussian noise and random processes; detection; rake receivers; fading channels and wireless communication; introduction to communication system design.
6.432 - Stochastic Processes, Detection, and Estimation
Fundamentals of detection and estimation for signal processing, communications, and control. Vector spaces of random variables. Bayesian and Neyman-Pearson hypothesis testing. Bayesian and nonrandom parameter estimation. Minimum-variance unbiased estimators and the Cramer-Rao bounds. Representations for stochastic processes; shaping and whitening filters; Karhunen-Loeve expansions. Detection and estimation from waveform observations. Advanced topics: linear prediction and spectral estimation; Wiener and Kalman filters.
Spring 2004ECE 426 - Applications of Signal Processing
Applications of signal processing, including signal analysis, filtering, and signal synthesis. The course is laboratory oriented, emphasizing individual student projects. Design is done with signal-processing hardware and by computer simulation. Topics include filter design, spectral analysis, speech coding, speech processing, digital recording, adaptive noise cancellation, and digital signal synthesis.
ECE 492 - Sensor Network Reachback Communication
Individual study, analysis, and, usually, experimental tests in connection with a special engineering problem chosen by the student after consultation with the faculty member directing the project.
ECE 526 - Signal Modeling and Representation
Sampling and signal reconstruction. Approximation theory. Linear inversion theory. Exponential signal modelling. Multirate filter banks, wavelets, and lifting. Laboratory experiments with speech and image signals.
GOVT 327 - Civil Liberties in the United States
An analysis of contemporary issues in civil liberties and civil rights, with emphasis on Supreme Court decisions. Cases are analyzed in terms of democratic theory and the social and political context in which they arose.
MATH 336 - Applicable Algebra
An introduction to the concepts and methods of abstract algebra and number theory that are of interest in applications. Course covers the basic theory of groups, rings and fields and their applications to such areas as public-key cryptography, error-correcting codes, parallel computing, and experimental designs. Applications include the RSA cryptosystem and use of finite fields to construct error-correcting codes and Latin squares. Topics include elementary number theory, Euclidean algorithm, prime factorization, congruences, theorems of Fermat and Euler, elementary group theory, Chinese remainder theorem, factorization in the ring of polynomials, and classification of finite fields.
P ED 375 - Classical Fencing
Classical fencing is a martial art that uses the practice of the sword to cultivate self-mastery. In this introductory class students will learn safety, etiquette and the fundamental fencing skills required for advancement to the rank of Scholar I in the IFV system.
H ADM 430 - Introduction to Wines
An introduction to the major wine-producing regions of the world, and what the consumer needs to know to purchase wine at retail outlets and in a restaurant setting. Lecture topics include flavor components in wine, pairing wine and food, responsible drinking, selecting quality and value wine, and wine etiquette. Samples from a variety of countries, regions, and vineyards are evaluated.
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