# Special Topics Courses

**Spring 2016**

ENG BE700 A1, A2, A3 and A4 are restricted to PhD students in BME.

Students must take 2 of 4 modules including A1 and either A2, A3, OR A4.

All modules are 2 credits each.

The goals of these module courses are two-fold: To present pertinent mathematical concepts for graduate researchers in biomedical engineering, and moreover, to provide students with the foundations to further explore advanced mathematical topics necessary for their research. Students will be exposed to a minimum of 2 (non-limiting) of the 4 available mathematical modules, where (*) is required while other topic(s) of choice are optional: Linear algebra*, ordinary differential equations, partial differential equations, and numerical methods. Selected topics include:

Spring 2016:

**ENG BE 700 A3 - Partial Differential Equations: Laplace's equation, wave equation; Fourier transform solutions; Green's functions, Poisson's equation**

TR 2-4, F 2-3

2 credits

1/19/16-3/4/16

**ENG BE 700 A4 - Intro to Numerical Methods: QR factorization, successive overrelaxation, Newton's method / conjugate gradient, discrete Fourier transform (DFT), fast Fourier transform (FFT), introduction to finite elements**

TR 2-4, F 2-3

2 credits

3/15/16-4/29/16

**ENG BE 700 A5 - Cells to Tissues (Chen)**

This is a literature-based course that introduces students to engineering concepts in understanding and manipulating the behavior of biological cells. We will try to understand the interplay between cells, their extracellular microenvironment, and intracellular signaling pathways in regulating cellular and multicellular structure and function. In particular, we will explore the use of modern experimental approaches to characterize and manipulate cells for bioengineering applications, and the concepts in scaling cellular engineering to functional tissues. In this context, we will focus on several topics, including signal transduction and the molecular regulation of cell function, cellular microenvironment, cell adhesion and mechanics, stem cells, multicellularity, and experimental models of tissue development. Substantial weekly reading and presentation is required.

TR 10-12

4 credits

**Fall 2015**

**ENG BE 700 A1 and A2 (Fall) and A3 and A4 (Spring) - Fan [see below for individual descriptions of modules]**

ENG BE700 A1, A2, A3 and A4 are restricted to PhD students in BME.

Students must take 2 of 4 modules including A1 and either A2, A3, OR A4.

All modules are 2 credits each.

The goals of these module courses are two-fold: To present pertinent mathematical concepts for graduate researchers in biomedical engineering, and moreover, to provide students with the foundations to further explore advanced mathematical topics necessary for their research. Students will be exposed to a minimum of 2 (non-limiting) of the 4 available mathematical modules, where (*) is required while other topic(s) of choice are optional: Linear algebra*, ordinary differential equations, partial differential equations, and numerical methods. Selected topics include:

Fall 2015:

ENG BE 700 A1 - Linear Algebra: LU factorization, least squares, eigenvalues, transformations, diagonalization, singular value decomposition, functional vector spaces, generalized Fourier series (trigonometric, Legendre, Bessel)

TR 2-4, F 2-3

2 credits

From 9/3/15 to 10/22/14

ENG BE 700 A2 - Ordinary Differential Equations: 1st and 2nd order ODE systems, reduction of order, state equations, Laplace transforms, Sturm-Liouville problems, calculus of variations
TR 2-4, F 2-3

2 credits

From 10/27/14 to 12/10/14

**ENG BE 700 A6 - Methods and Logic in Quantitative Biology (Mehta)**

Biology is in the midst of a transformation into a fully quantitative, theory-rich science. For example, the advent of genomic techniques has presented the opportunity to study genetic processes on a genomic scale and to achieve quantitative understanding, not just of individual molecular mechanisms but also of their interactions and regulation at the systems level. This graduate course in quantitative biology is based on original path-breaking papers in diverse areas of biology. Each of these papers depends on quantitative reasoning and theory as well as experiment. Through close reading and discussion of these papers, students of diverse backgrounds (biology, engineering, physics, computational sciences) will learn essential ideas and how to communicate in a common language of modern/quantitative biology. This course should be considered essential education for students interested in pursuing research in systems biology, synthetic biology, and biophysics. Although it is a graduate course, we encourage advanced undergraduates to enroll, too.

MW 10-12

4 credits

**ENG EC 500 A1 - Fourier Optics for Engineers (Dal Negro)**

Scalar and vector waves, spatial frequency, linear systems and transforms, Fourier transform in rectangular and cylindrical coordinates, some special functions and their Fourier transforms. Correlation and convolution operations. Hints on linear canonical transformations in optical engineering. Rigorous Kirchhoff diffraction theory, wave propagation and angular spectrum representation, application to free-field propagation. The beam propagation method. Single scattering theory (kinematic scattering) by arbitrary arrays of scatterers, elements of vector wave scattering. Introduction to phase-space optics. Optical transmittance functions, imaging systems, diffraction-based imaging and photonic devices. Analysis and synthesis of photonic gratings, applications to optical biosensors, spatial light modulators and phase-space engineering of optical beams. Elements of imaging theory and microscopy, aberration theory, coherent and incoherent imaging, partial coherence, correlation op tics. Wave propagation in inhomogeneous and random media, speckle formation and applications to super-resolution imaging and optical detection. Numerical examples and implementations in Matlab.

Prerequisites: Matlab programming, Electromagnetics

TR 2-4

4 credits

**ENG EC 500 B1 - Introduction to Learning From Data (Ishwar)**

This is an introductory course in statistical learning covering the basic theory, algorithms, and applications. This course will focus on the following major classes of supervised and unsupervised learning problems: regression, classification, clustering, and dimensionality reduction. Both generative (Bayesian) and discriminative (frequentist) formulations/interpretations of learning objectives (in parametric and non-parametric settings) will be developed in tandem. A variety of contemporary applications will be explored through homework assignments and a project. Prerequisites: Linear Algebra, Multivariate Calculus, Probability, Detection, Estimation, MATLAB proficiency, EC505 Stochastic Processes

*
Prerequisites: Probability, Linear Algebra and Matlab
TR 4-6
4 credits
*

**ENG EC 700 A1 - Advanced Computer Systems (Coskun)**

This class is designed to enable students to follow the latest developments in computer systems and architecture, especially those related to novel multicore, heterogeneous, or large-scale systems. The course is useful for those who wish to do research related to computing systems, architecture, embedded systems, data centers, and cloud computing. In addition, the course aims to develop skills and background for those who would like to work in industry in related areas or who have general interests in the design and analysis of computing systems.

The lectures will cover a broad array of recent subjects including memory/cache management in multicore systems, hardware multithreading, tiled architectures, heterogeneous systems, large-scale system architectures, virtualization and hypervisors, data center management, energy awareness in computing systems, and system reliability/resiliency. The concepts will be reinforced with research paper readings and also with homework and project assignments that involve system design and analysis. The assignments will involve using microarchitectural and cluster simulators as well as experiments on commercial systems.

Prerequisites: students should have programming experience (C, C++ or Python), basic experience with Linux, and should have taken one (or more) of the following classes: EC513, EC535, EC527, EC500 (Cloud Computing).

MW 2-4

4 credits

**ENG EC 700 B1 - Computational Neuroscience (Schwartz)**

This course is a research seminar on computational neuroscience. Topics of current interest, according to class interest, will be covered, in addition to a review of the experimental and theoretical body of work on the columnar and topographic functional architecture of visual cortex. Additional topics to be covered will included computational vision, applications of computer methods to optical and magnetic imaging , anatomical reconstruction, and the computational bases of biological vision.

R 2-5

4 credits

**ENG ME 500 A1 - Quantum mechanics for Engineering Devices (Barouch)**

Most courses teach QM as a separate issue, simply going over the principles, without connecting to the vast quantity of devices in nano and micro technologies that are directly effected by these principles. In contrast, this course uses these applications as the starting point to aid students in understanding the fascinating world of QM, while equally emphasizing that QM is critical for engineering students intent on a future such growing areas as nanotechnology.

TR 4-6

**Spring 2015**

**ENG BE 700 A1 and A2 (Fall) and A3 and A4 (Spring) - Fan [see below for individual descriptions of modules]**

ENG BE700 A1, A2, A3 and A4 are restricted to PhD students in BME.

Students must take 2 of 4 modules including A1 and either A2, A3, OR A4.

All modules are 2 credits each.

The goals of these module courses are two-fold: To present pertinent mathematical concepts for graduate researchers in biomedical engineering, and moreover, to provide students with the foundations to further explore advanced mathematical topics necessary for their research. Students will be exposed to a minimum of 2 (non-limiting) of the 4 available mathematical modules, where (*) is required while other topic(s) of choice are optional: Linear algebra*, ordinary differential equations, partial differential equations, and numerical methods. Selected topics include:

Fall 2014:

ENG BE 700 A1 - Linear Algebra: LU factorization, least squares, eigenvalues, transformations, diagonalization, singular value decomposition, functional vector spaces, generalized Fourier series (trigonometric, Legendre, Bessel)

MW 2-4, F 2-3

2 credits

9/3/14 - 10/17/14

ENG BE 700 A2 - Ordinary Differential Equations: 1st and 2nd order ODE systems, reduction of order, state equations, Laplace transforms, Sturm-Liouville problems, calculus of variations

MW 2-4, F 2-3

2 credits

10/20/14 - 12/5/14

Spring 2015:

ENG BE 700 A3 - Partial Differential Equations: Laplace's equation, wave equation; Fourier transform solutions; Green's functions, Poisson's equation

TR 2-4, F 2-3

2 credits

1/20/15-3/6/15

ENG BE 700 A4 - Intro to Numerical Methods: QR factorization, successive overrelaxation, Newton's method / conjugate gradient, discrete Fourier transform (DFT), fast Fourier transform (FFT), introduction to finite elements

TR 2-4, F 2-3

2 credits

3/17/15-4/28/15

**EC 500 A1 - Cloud Computing (Krieger)**

The course will combine group reading and discussion of influential publications in cloud computing, some lectures by instructor and by invited speakers, independent review of talks coupled with classroom discussion, and a large project. For the most part, the course will be flipped, with most of the material independently studied, and then group discussion of the material. The project will be done by teams of 3 to 5 students working with an industry leader.

This course assumes students have a strong programming background.Undergrads must have taken EC327 or equivalent and preferably another software course, EC330 or EC440, before taking this course. Graduate students must have taken a rigorous programming class recently, such as EC504 or equivalent (or have major software design experience in industry). If you have questions about the prerequisites, please consult the instructor.

*TR 12pm-2pm*

**ENG EC 500 A2 - Design of Secure and Reliable Computer Systems (Karpovsky)**

Fundamentals of design of secure and reliable computer systems. Attack models. Security and reliability measures. Introduction to finite fields. Linear error detecting codes and design of fault-tolerant hardware. Self checking checkers. Error detecting codes for design of secure hardware. Robust codes for prevention of fault injection attacks. Algebraic manipulation detection codes for design of hardware resistant to strong fault injection attacks. Design of secure and reliable communication links, memories, multipliers and cryptographic hardware.

*4 credits MW 10-12
Prerequisite: ENG EC 311*

**ENG EC 500 A3 - Introduction to Computational Neuroscience (Schwartz)**

This course is part of a sequence of that includes a 700-level research seminar in computational neuroscience. This course will focus on synaptic and single neuron level fundamentals, leading up to compartmental modeling. Circuit theory methods are adapted to solving compartmental modeling problems, in the context of MATLAB coding. The Nernst Equation, Nernst-Planck Equation, Goldman Equations, Hodgkin-Huxley and Cable equations are surveyed and derived. Then, these are used to build a compartmental solver in MATLAB. In addition, brief surveys will be presented on supra-neuronal functional architecture (cortical maps and columns) and on some aspects of Brain Imaging (cortical flattening and fMRI fundamentals), with further discussion of these latter topics continued in more depth in the second course in this sequence.

*R 1:00pm-4:00pm
4 cr
Prereq: Calculus*

**ENG EC 700 A1 - Vulnerability, Defense Systems, and Malware Analysis (Egele)**

This will be a project-led course to survey and understand the landscape of vulnerability detection, malware analysis, and defense systems. We analyze proposed and currently used systems for finding vulnerabilities on a system or in software, defending against vulnerabilities that might be present on a system, and performing malware analysis.

*Prerequisite: EC521 or equivalent
TR 4pm-6pm*

**Fall 2014**

**ENG BE 700 A1 and A2 (Fall) and A3 and A4 (Spring) - Fan [see below for individual descriptions of modules]**

ENG BE700 A1, A2, A3 and A4 are restricted to PhD students in BME.

Students must take 2 of 4 modules including A1 and either A2, A3, OR A4.

All modules are 2 credits each.

Fall 2014:

ENG BE 700 A1 - Linear Algebra: LU factorization, least squares, eigenvalues, transformations, diagonalization, singular value decomposition, functional vector spaces, generalized Fourier series (trigonometric, Legendre, Bessel)

MW 2-4, F 2-3

2 credits

From 9/3/14-10/17/14 to 9/3/14 - 10/20/14

ENG BE 700 A2 - Ordinary Differential Equations: 1st and 2nd order ODE systems, reduction of order, state equations, Laplace transforms, Sturm-Liouville problems, calculus of variations

MW 2-4, F 2-3

2 credits

From 10/20/14-12/5/14 to 10/22/14-12/10/14

Spring 2015:

ENG BE 700 A3 - Partial Differential Equations: Laplace's equation, wave equation; Fourier transform solutions; Green's functions, Poisson's equation

TR 2-4, F 2-3

2 credits

1/20/15-3/6/15

ENG BE 700 A4 - Intro to Numerical Methods: QR factorization, successive overrelaxation, Newton's method / conjugate gradient, discrete Fourier transform (DFT), fast Fourier transform (FFT), introduction to finite elements

TR 2-4, F 2-3

2 credits

3/17/15-4/28/15

**ENG BE 700 C1 - Methods and Logic in Quantitative Biology (Khalil)**

The main focus of this course is the close reading of published papers illustrating the principles, achievements, and difficulties that lie at the interface of theory and experiment in biology. Two (or three) important papers, read in advance by all students, will be considered each week; the emphasis will be on discussion with students as opposed to formal lectures. Topics include: cooperativity, robust adaptation, gene regulation & genetic circuits, kinetic proofreading, pattern formation, sequence analysis, clustering, phylogenetics, analysis of fluctuations, maximum likelihood methods, and single-molecule approaches.

*MW 10-12
4 credits*

**ENG EC 500 A1 - Fourier Optics for Engineers (Dal Negro)**

Scalar and vector waves, spatial frequency, linear systems and transforms, Fourier transform in rectangular and cylindrical coordinates, some special functions and their Fourier transforms. Correlation and convolution operations. Hints on linear canonical transformations in optical engineering. Rigorous Kirchhoff diffraction theory, wave propagation and angular spectrum representation, application to free-field propagation. The beam propagation method. Single scattering theory (kinematic scattering) by arbitrary arrays of scatterers, elements of vector wave scattering. Introduction to phase-space optics. Optical transmittance functions, imaging systems, diffraction-based imaging and photonic devices. Analysis and synthesis of photonic gratings, applications to optical biosensors, spatial light modulators and phase-space engineering of optical beams. Elements of imaging theory and microscopy, aberration theory, coherent and incoherent imaging, partial coherence, correlation optics. Wave propagation in inhomogeneous and random media, speckle formation and applications to super-resolution imaging and optical detection. Numerical examples and implementations in Matlab.

TR 2-4

4 credits

Prerequisite: Matlab programming, Electromagnetics

**ENG ME/MS 500 A1 - Materials and Processes (Sarin)**

The goals of this course are two-fold: To present pertinent mathematical concepts for graduate researchers in biomedical engineering, and moreover, to provide students with enough foundations to further explore advanced mathematical topics necessary for their research. The four main themes will be: Probability / statistics, linear algebra, partial differential equations / boundary value problems, and complex variables. Exemplary problems will be drawn from biomedical engineering topics. * Registration is limited to first year graduate students.

Selected topics include: Basic probability, hypothesis testing, regression, non-parametric tests, intro to multivariate methods (principle component analysis, clustering); linear algebra and vector spaces, Sturm-Liouville equations, PDEs and boundary-value problems, calculus of variations; integral transforms (Fourier / Laplace), complex variables, vector calculus, tensors.

*TR 12-2
4 credits*

**ENG ME 500 B1 - Quantum Mechanics for Engineering Devices (Barouch)**

When the phenomena and theory of quantum mechanics (QM) was first developed by physicists, starting in the early 1900s, the applications to engineering were few, if nonexistent. At the time, QM was an interesting and most curious physical theory, but not something one needed to know to make relevant engineering devices. Today, the situation is far different, as nearly all of nanotechnology, photonics, laser applications, solar cells, advanced instrumentation and sensors, and aspects of biotechnology, rely to a fair amount on QM principles. This course examines many of these key engineering applications and provides the necessary QM background behind them, thereby enabling engineering students to have a more unified view of applications and theory.

*MW 4-6
4 credits*

**Spring 2014**

**ENG BE 500 A1 - Systems Biology of Human Disease (Kasif)**

This course will train students to apply or develop new computational network and machine learning concepts to probe into the systems biology of disease.

The course will cover computational frameworks such as biological networks (including metabolic, regulatory and signal transduction networks), microarray analysis, proteomic analysis, next. generation sequencing, imaging, machine learning, genetics, pathway analysis and other technologies to medical diseases initially focusing on clinical problems such as cancer, diabetes, inflammation and aging.

The course is aimed at seniors and graduate students in biomedical engineering or bioinformatics. However, students from other disciplines ranging from medicine and biology to physics or computer science can attend the class with some prerequisites.

*4 credits MW 6-8 pm*

NOTE: This course satisfies the Professional elective requirement only

**ENG BE 700 A1 - Advanced Biomedical Design and Development II (Rosenthal & Rosen)**

The course will teach the basic skills required to identify and develop a medical product from the early stages of ideation to pre manufacturing product commercialization.

*MW 1-3
4 credits
Note: ENG BE 700 A1 is restricted to BME M.Eng. students only. Students who register for ENG BE 700 A1 in Spring must have completed ENG BE 700 A1 in Fall. This is a 2-semester course, with each semester being 4 credits.*

**ENG BE 700 A2 - Cells to Tissues (Chen)**

This is a literature-based course that introduces students to engineering concepts in understanding and manipulating the behavior of biological cells. We will try to understand the interplay between cells, their extracellular microenvironment, and intracellular signaling pathways in regulating cellular and multicellular structure and function. In particular, we will explore the use of modern experimental approaches to characterize and manipulate cells for bioengineering applications, and the concepts in scaling cellular engineering to functional tissues. In this context, we will focus on several topics, including signal transduction and the molecular regulation of cell function, cellular microenvironment, cell adhesion and mechanics, stem cells, multicellularity, and experimental models of tissue development. Substantial weekly reading and presentation is required.

*TR 10-12
4 credits*

**ENG BE 700 A3 - Stem Cell Engineering (Khalil)**

Provides a foundation in the application of analytical engineering approaches for the quantitative study of stem cell biology and effective translation of stem cells into therapies and diagnostics. Will provide the conceptual framework for understanding how to identify an appropriate type of stem cell based on desired application(s); isolate and purify desired cell type(s); expand stems cells in a stable state, directing the differentiation to specific phenotype(s); and use appropriate characterization techniques and quality control metrics to quantitatively assess cell phenotype for the development of stem cell-based technologies. Lectures are provided by live videoconference twice per week (1hr 20 min/lecture).

Course meets 1/7/14-4/24/14

*TR 2-3:30
4 credits*

**ENG EC 700 A1 - Advanced Computing Systems and Architecture (Coskun)**

This class is designed to enable students to follow the latest developments in computer systems and architecture, especially those related to novel multicore, heterogeneous, or large-scale systems. The course is useful for those who wish to do research related to computing systems, architecture, embedded systems, data centers, and cloud computing. In addition, the course aims to develop skills and background for those who would like to work in industry in related areas or who have general interests in the design and analysis of computing systems.

The lectures will cover a broad array of recent subjects including memory/cache management in multicore systems, hardware multitheading, tiled architectures, heterogeneous systems, large-scale system architectures, virtualization and hypervisors, data center management, energy awareness in computing systems, and system reliability/resiliency. The concepts will be reinforced with research paper readings and also with homework and project assignments that involve system design and analysis. The assignments will involve using microarchitectural and cluster simulators as well as experiments on commercial systems.

Prerequisites:

Programming experience (C, C++ or Python) One (or more) of the following classes: EC513, EC535, EC527

*4 credits TR 10am - 12pm*

**ENG EC 700 B1 - Computational Neuroscience (Schwartz)**

These three levels of computational neuroscience will be explored in the context of a reading seminar for advanced graduate students in the Dept. of Cognitive and Neural Systems, the College of Engineering, and the School of Medicine. The goal of the course is exposure to the literature of computational neuroscience. Original papers in the areas of the structure, function and modeling of primate visual cortex will provide one major area of coverage. Special emphasis will be placed on the columnar and topographic structure of visual cortex, and the computational and functional models that have been developed in the context of visual cortex. A second major area of emphasis will be on technological applications in the areas of active (computer) vision.

This material is by nature multidisciplinary: students will be expected to have a strong background in at least one of neuroscience, computer science or computer technology. A mathematical background which includes a working knowledge of applied linear algebra, fourier analysis, and advanced calculus will be assumed. However, some attempt will be made to provide a self-contained presentation: a brief review of all advanced material will be provided.

*4 credits R 2pm - 5pm*

**ENG ME 700 A1 - Inverse Problems in Mechanics (Barbone)**

Inverse problems are ubiquitous in science and engineering from data analysis to model identi- cation and validation. Pervasive as they are, however, their systematic study has only in recent years been undertaken. The main goal of this course is to provide a mathematical foundation for understanding the structure of inverse problems, a systematic approach to their formulation, and the tools required for their solution. Correspondingly, the course will be divided into three Parts.

*4 credits MW 10am-12pm*

**ENG ME 700 B1 - Multi-Robot Control, Communication and Sensing (Schwager)**

This course will survey the current research in multi-robot systems, including recent influential works on multi-agent consensus, coverage control and sensor deployment, information-driven control, distributed Kalman filtering, communication aware control, distributed construction and pattern formation, and more. We will see emerging unifying trends in this area in terms of underlying distributed optimization problems. One of the main goals of this course will be to develop skills in evaluating and critiquing research papers, and to gain a broad view of the research landscape in multi-robot systems. Familiarity with linear and nonlinear control, Lyapunov theory, and Kalman filtering will be expected. Some knowledge of nonlinear optimization and information theory will be helpful.

*4 credits TR 4-6 pm*

**Fall 2013**

**ENG BE 700 A1 - Advanced Biomedical Design and Development I (Rosenthal & Rosen)**

The course will teach the basic skills required to identify and develop a medical product from the early stages of ideation to pre manufacturing product commercialization.

*MW 1-3
4 credits
Note: ENG BE 700 A1 is restricted to BME M.Eng. students only. Students who register for ENG BE 700 A1 in Spring must have completed ENG BE 700 C1 in Fall .This is a 2-semester course, with each semester being 4 credits.*

**ENG BE 700 B1 – Mathematical Methods in Biomedical Engineering (Fan)**

The goals of this course are two-fold: To present pertinent mathematical concepts for graduate researchers in biomedical engineering, and moreover, to provide students with enough foundations to further explore advanced mathematical topics necessary for their research. The four main themes will be: Probability / statistics, linear algebra, partial differential equations / boundary value problems, and complex variables. Exemplary problems will be drawn from biomedical engineering topics. * Registration is limited to first year graduate students.

Selected topics include: Basic probability, hypothesis testing, regression, non-parametric tests, intro to multivariate methods (principle component analysis, clustering); linear algebra and vector spaces, Sturm-Liouville equations, PDEs and boundary-value problems, calculus of variations; integral transforms (Fourier / Laplace), complex variables, vector calculus, tensors.

*MW 2-4, F 2-3
4 credits
Note: Restricted to first year graduate students*

**ENG EC 500 A1 – Wireless Communication (Nazer)**

Fundamentals of wireless communication from a physical layer perspective. Multipath signal propagation and fading channel models. Design of constellations to exploit time, frequency, and spatial diversity. Reliable communication and single-user capacity. Interference management, multiple-access protocols, and multi-user capacity. Cellular uplink and downlink. Multiple-antenna systems and architectures. Connections to modern wireless systems and standards.”

*TR 4-6pm
4 credits*

**ENG EC 500 B1 – Introduction to Computational Neuroscience (Schwartz)**

Formerly taught as CAS CN 580

This introductory level course focuses on building a background in neuroscience, but with emphasis on computational approaches. Topics include basic biophysics of ion channels, Hodgkin-Huxley theory, use of stimulators such as NEURON and GENESIS, recent applications of the compartmental modeling technique, and a survey of neuronal architectures of the retina, cerebellum, basal ganglia, and neocortex.

*TR 4-6 pm
4 cr
Prereq: senior standing or consent of instructor.*

**ENG EC 500 C1 – Audio and Physiological Sensing (Nawab)**

Introduction to artificial intelligence methods specialized to audio (environmental, musical and speech related) and physiological sensing (cardiac, neuromuscular, and movement related). Conceptual emphasis is on signal to symbol transformations, blackboard systems, approximate processing, and machine learning. Application topics include spatial audio, spatial EKG, spatial speech, auditory scene analysis, neuromuscular decoding, movements decoding, environmental audio, and music recognition.

*TR 12-2 pm
4 cr
Prereq: EC401*

**Spring 2013**

**ENG BE 500 A1 - Systems Biology of Human Disease (Kasif)**

This course will train students to apply or develop new computational network and machine learning concepts to probe into the systems biology of disease.

The course will cover computational frameworks such as biological networks (including metabolic, regulatory and signal transduction networks), microarray analysis, proteomic analysis, next. generation sequencing, imaging, machine learning, genetics, pathway analysis and other technologies to medical diseases initially focusing on clinical problems such as cancer, diabetes, inflammation and aging.

The course is aimed at seniors and graduate students in biomedical engineering or bioinformatics. However, students from other disciplines ranging from medicine and biology to physics or computer science can attend the class with some prerequisites.

*4 credits MW 6-8 pm*

NOTE: This course satisfies the Professional elective requirement only

**ENG BE 700 B1 - Brain Machine Interfaces (Ritt)**

***CANCELLED*** This course will be offered in Spring 2013 as ENG BE 780 A1

Brain Machine Interfaces will be a graduate level course emphasizing major approaches and central challenges in BMI applications. Topics range from interfacing with neural tissue, including electrode designs, types of neural signals, and issues of biocompatibility and signal degradation; decoding approaches, including motor control applications, signal to noise requirements, and effects of training and plasticity; and neural stimulation, including choice of peripheral vs. central targets, consequences of topographic organization, types of perceptual responses, and limits to control of distributed systems. To follow rapid changes in the field, course materials will be drawn primarily from research literature. In addition to readings, discussions and computational exercises, students will complete a final project.

*4 credits TR 2-4*

**ENG BE 700 C1 - Advanced Product Design and Development (Rosenthal & Rosen)**

The course will teach the basic skills required to identify and develop a medical product from the early stages of ideation to pre manufacturing product commercialization.

*W 6-8 2 credits*

*Note: ENG BE 700 C1 is restricted to BME M.Eng. students only. Students who register for ENG BE 700 C1 in Spring must have completed ENG BE 700 C1 in Fall .This is a 2-semester course, with each semester being 2 credits.*

**ENG EC 500 A1 - Design of Secure and Reliable Computer Systems (Karpovsky)**

Fundamentals of design of secure and reliable computer systems. Attack models. Security and reliability measures. Introduction to finite fields. Linear error detecting codes and design of fault-tolerant hardware. Self checking checkers. Error detecting codes for design of secure hardware. Robust codes for prevention of fault injection attacks. Algebraic manipulation detection codes for design of hardware resistant to strong fault injection attacks. Design of secure and reliable communication links, memories, multipliers and cryptographic hardware.

*4 credits TR 4-6
Prerequisite: ENG EC 311*

**ENG EC 700 A1 – Statistical Inference and Learning (Ishwar)**

Probabilistic framework and algorithms for inference and learning using models and data with engineering applications. Risk functions, optimum inference rules, and learning paradigms. Exponential families, graphical models, latent models, mixture models, dynamical models. Model selection. Belief propagation, expectation maximization, and related inference algorithms. Simulation methods. Hypothesis testing, classification, estimation, regression, filtering, dimensionality reduction, clustering. Performance analysis and fundamental limits.

Prerequisite: ENG EC 505 - Stochastic Processes

*4 credits TR 12-2*

**ENG ME 500 A1 – Viscous Flow (Grace)**

Brief review of the fundamental conservation and constitutive equations, exact solutions of the viscous Navier-Stokes equations, similarity solutions, boundary layer theory; creeping flows, flow in Hele-Shaw cells, lubrication theory, thin shear layer approximations, jets and wakes, hydrodynamic instability and transition to turbulence, Reynolds-averaged Navier-Stokes equations.

*4 credits MW 2-4*

**Fall 2012**

**ENG BE 500 A1 - Epigenomics: Off the Information Highway (C. Smith)**

The Human Genome Project provided robust genetic approaches for finding the cause(s) of rare single gene diseases, but not complex common diseases or even normal phenotypes in eukaryotes. Complex characteristics have strong genetic and environmental components that interact. This course focuses on epigenomics and complexity - the interactions between the genome and the environment, and the methods used to study these interactions at the DNA, RNA, and protein level. The course will cover types, biochemical basis, biological consequences, and approaches to discovery, measurements and understanding, and integrating environmental and gene interactions.

*4 credits TR 10am-12pm*

**ENG BE 700 A1 - The Cell as a Machine (Zaman)**

The goals of this course are to provide a working understanding of the basic cell functions and the physical and chemical principles underlying them. In practical terms, we will attempt to solve a number of important problems relevant to replication, transcription, translation, translocation, motility, and other important functions using a quantitative engineering approach. For each section in the course, we will merge fundamental physical and mechanical framework with relevant biological information with a particular physiological processes at those length-scales.

*Permission of Instructor required
4 credits TR 10:30 am -12:00 pm
Course meets at MIT*

**ENG BE 700 C1 - Advanced Product Design and Development (Rosenthal & Rosen)**

*W 6-8 2 credits*

*Note: ENG BE 700 C1 is restricted to BME M.Eng. students only. Students who register for ENG BE 700 C1 in Fall must also register for ENG BE 700 C1 in Spring .This is a 2-semester course, with each semester being 2 credits.*

**Spring 2012**

**ENG BE 500 A1 - Systems Biology of Human Disease (Kasif)**

This course will train students to apply or develop new computational network and machine learning concepts to probe into the systems biology of disease.

The course will cover computational frameworks such as biological networks (including metabolic, regulatory and signal transduction networks), microarray analysis, proteomic analysis, next. generation sequencing, imaging, machine learning, genetics, pathway analysis and other technologies to medical diseases initially focusing on clinical problems such as cancer, diabetes, inflammation and aging.

The course is aimed at seniors and graduate students in biomedical engineering or bioinformatics. However, students from other disciplines ranging from medicine and biology to physics or computer science can attend the class with some prerequisites.

*4 credits MW 2-4 pm*

NOTE: This course satisfies the Professional elective requirement only

**ENG BE 500 A3 - Structure and Function of the Extracellular Matrix (Suki)**

This is an introductory course dealing with the detailed structure of the basic units of the extracellular matrix including collagen, elastin, microfibrils and proteoglycans as well as the functional properties of these molecules. The focus is mostly on how the structure of these components determine the functional properties such as elasticity at different scales from molecule to fibrils to organ level behavior. The biological role of these components and their interaction with cells is also covered. Interaction of enzymes and the matrix in the presence of mechanical forces is discussed. Mathematical modeling is applied at various length scales of the extracellular matrix that provides quantitative understanding of the structure and function relationship. Special topics include how diseases affect extracellular matrix in the lung, cartilage and vasculature. The relevance of the properties of native extracellular matrix for tissue engineering is also discussed.

4 credits MW 2-4 pm

NOTE: This course satisfies the Professional/Engineering/Biomedical Elective requirements.

**ENG EC 500 A1 - Introduction to Computational Computer Vision (Tannenbaum)**

We will introduce the students to the area of computer vision with an emphasis on computations and problem solving. Applications will be given to autonomous vehicles, tracking, robotics, and image-guided surgery. The Project is an essential part of the course. The students will be required to choose a topic in computer vision, and work out a computer implementation of their idea. This may involve the implementation of a smoothing filter, segmentation method, and edge detector. This will allow students to have hands-on experience in understanding and implementing a given computer vision algorithm.

Requirements: Basic course in signal processing.

Knowledge of some programming language (Matlab or C/C++ or FORTRAN).

4 credits TR 10 am -12 pm

**ENG ME 500 A1 - Principles of Biological Physics (Schneider)**

Did Albert Einstein contribute to the understanding of life?

Applying physical concepts and technologies to "living matter" is still at is beginning. However, many exciting discoveries have been made. From Single Molecules Mechanics, Biomembranes to the Swimming of individual Bacteria or the design of NMR-PET tubes to image the entire human body and our brain in action.

In this course I raise the question: Where do we stand in understanding the laws of the living using the laws of physics? Each part of the course will not only consist of the facts to the particular topic, but also on a critical discussion on the major flaws of the common textbook explanations of life.

Major topics will be: The physics of nerves, life in a shell (membrane biophysics), cell mechanics, cell adhesion, life under flow, microfluidics, blood clotting etc. A thorough introduction to polymer physics and classical thermodynamics including the role of A. Einstein in biological physics will be given.

*4 credits MW 2 pm - 4 pm*

**ENG EC 700 C3 - Sensor Networks and Cooperative Control (Cassandras)**

This is a course for graduate students interested in the state of the art in the theory and applications of sensor networks and cooperative control, emphasizing the interconnection between the two. The purpose is to learn about advanced methodologies used in these areas and about open research problems and to critically review and present papers from the very recent literature. Students will develop the ability to conceptualize cutting-edge research issues in the sensor network and cooperative control domain, and to formulate problems for potential research projects.

Prerequisites: EK 500 or equivalent, SE 501 or equivalent, SE 524 or equivalent

Students undertake a course project and deliver a final report.

4 credits MW 12 pm -2 pm

Meets with ENG SE 700 C3

**ENG SE 700 C3 - Sensor Networks and Cooperative Control (Cassandras)**

This is a course for graduate students interested in the state of the art in the theory and applications of sensor networks and cooperative control, emphasizing the interconnection between the two. The purpose is to learn about advanced methodologies used in these areas and about open research problems and to critically review and present papers from the very recent literature. Students will develop the ability to conceptualize cutting-edge research issues in the sensor network and cooperative control domain, and to formulate problems for potential research projects.

Prerequisites: EK 500 or equivalent, SE 501 or equivalent, SE 524 or equivalent

VAR (2 or 4) credits: 2 credits normally awarded. 4 credits awarded to students interested in undertaking a course project and delivering a final report.
First-year SE students may enroll in this course under the Division’s Research Rotation system. The course will count as one rotation.

VAR credits MW 12 pm -2 pm

**Fall 2011**

**ENG BE 500 A1 - Epigenomics: Off the Information Highway (C. Smith) **

The Human Genome Project provided robust genetic approaches for finding the cause(s) of rare single gene diseases, but not complex common diseases or even normal phenotypes in eukaryotes. Complex characteristics have strong genetic and environmental components that interact. This course focuses on epigenomics and complexity - the interactions between the genome and the environment, and the methods used to study these interactions at the DNA, RNA, and protein level. The course will cover types, biochemical basis, biological consequences, and approaches to discovery, measurements and understanding, and integrating environmental and gene interactions.

*4 credits TR 10am-12pm*

**ENG BE 500 A3 - Mechanics and Thermodynamics of Cell Structure and Chemical Interactions (Evans)**

An engineering foundation course in chemical thermodynamics applied to molecular structures and processes important in the biology, physiology, and mechanics of living organisms.

Meets with ENG ME/MS 505

*4 credits MW 12-2 pm *

**ENG BE 500 A4 - Next Generation Sequencing (Kasif/Meller)**

Sequencing and comparative analyses of human genome sequences, as well as other genomes form the basis to address questions such as: what makes us human? what specific genomic markers make cancer cells resistant to specific drugs? what are the causes of anti-biotic resistance in microbes? what portion of the genome is transcribed in a disease population vs normal populations? Next Generation Sequencing (NGS) is driving personalized medicine and other applications in biomedical science and engineering. In this course we will review the foundations of the field, current and emerging single molecule DNA sequencing techniques, through an introduction to the analytical tools to analyze NGS Data, and finally discussing clinical applications focusing on cancer.The course will involve bi-weekly homework assignments that include theoretical analysis and modeling, working with multiple analysis tools for NGS data including assembly, re-sequencing, alignments, RNA-seq, ChIP-seq, DNA methylation, mutation analysis and detection, copy number variation detection, and their applications to cancer.

4 credits TR 4-6 pm

NOTE: This course satisfies the Professional/Engineering/Biomedical elective requirements

**ENG BE 700 A1 - The Cell as a Machine (Zaman)**

The goals of this course are to provide a working understanding of the basic cell functions and the physical and chemical principles underlying them. In practical terms, we will attempt to solve a number of important problems relevant to replication, transcription, translation, translocation, motility, and other important functions using a quantitative engineering approach. For each section in the course, we will merge fundamental physical and mechanical framework with relevant biological information with a particular physiological processes at those length-scales.

Permission of Instructor required

4 credits TR 5-7 pm

**ENG EC 500 A1 - Cybersecurity (Starobinski)**

Fundamentals of security related to computers and computer networks. Social engineering, including ethics, identity and authentication, privacy, biometrics, and attacks based on psychology. Hardware and operating system security related to access control, exploits and disk forensics. Wireless and wire network security at the physical, network and application layers. Theoretical lessons are augmented with case studies and demonstrative experimental labs.

4 cr MW 10am - 12pm

**Spring 2011**

**ENG BE 500 A1 - Systems Biology of Human Disease (Kasif)**

*4 credits M 1-5 pm *

NOTE: This course satisfies the Professional elective requirement only

**ENG BE 500 A2 - Epigenomics: Off the Information Highway (C. Smith) **

******CANCELLED******

The Human Genome Project provided robust genetic approaches for finding the cause(s) of rare single gene diseases, but not complex common diseases or even normal phenotypes in eukaryotes. Complex characteristics have strong genetic and environmental components that interact. This course focuses on epigenomics and complexity - the interactions between the genome and the environment, and the methods used to study these interactions at the DNA, RNA, and protein level. The course will cover types, biochemical basis, biological consequences, and approaches to discovery, measurements and understanding, and integrating environmental and gene interactions.

*4 credits ARR *

**ENG BE 700 A1 - Nanomedicine: Principles and Applications (Cabodi)**

Nanomedicine is a rapidly growing field that exploits the novel properties at the nanoscale to advance the study of human biology and the practice of medicine. This course develops understanding of fundamental nanoscience and the synthesis and characterization of nanomaterials, coupled with applications for detection and treatment of pathogenic, cancerous, and cardiovascular diseases. Students analyze and develop research ideas, hypotheses and experimental designs through proposal writing and literature review. Lectures are led by rotating faculty with expertise in core subject areas: nanoparticle drug delivery and imaging; microfluidic diagnostics; label-free sensing and mass spectrometry for biomarker discovery; and nanofabricated substrates and porous media for cellular studies.

*2 credits R 4-6 pm*

**ENG ME 500 A1 - Principles of Biological Physics (Schneider) **

Did Albert Einstein contribute to the understanding of life?

Applying physical concepts and technologies to „living matter“ is still at is beginning. However, many exciting discoveries have been made. From Single Molecules Mechanics, Biomembranes to the Swimming of individual Bacteria or the design of NMR-PET tubes to image the entire human body and our brain in action.

In this course I raise the question: Where do we stand in understanding the laws of the living using the laws of physics? Each part of the course will not only consist of the facts to the particular topic, but also on a critical discussion on the major flaws of the common textbook explanations of life.

Major topics will be: The physics of nerves, life in a shell (membrane biophysics), cell mechanics, cell adhesion, life under flow, microfluidics, blood clotting etc. A thorough introduction to polymer physics and classical thermodynamics including the role of A. Einstein in biological physics will be given.

*4 credits MW 10 am - 12 pm *

**ENG ME 500 A2 - Viscous Flow (Grace)**

This course begins with a review of the fundamental conservation and constitutive equations governing fluid mechanics. Solutions methods including exact solutions of the viscous Navier-Stokes equations, similarity solutions, and thin shear layer approximations will be covered. Topics that will be explored include boundary layer theory, creeping flows, jets and wakes, hydrodynamic instability and transition to turbulence, microfluidics and the Reynolds-averaged Navier-Stokes equations and turbulence modeling.

*4 credits TR 12-2 pm*

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