Course listings | Case Western Reserve University

Subject: EECS

Term: Fall 2015

EECS 132: Introduction to Programming in Java (600/4529)

MWF 02:00-02:50 PM Aug 24-Dec 04

Connamacher, H

This Lecture and the following Recitations are recommended for Computer Science and Computer Engineering Majors.

EECS 132: Introduction to Programming in Java (610/4530)

W 03:00-03:50 PM Aug 24-Dec 04

Connamacher, H

This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.

EECS 132: Introduction to Programming in Java (611/4531)

W 04:00-04:50 PM Aug 24-Dec 04

Connamacher, H

This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.

EECS 132: Introduction to Programming in Java (613/4605)

R 10:30-11:20 AM Aug 24-Dec 04

Connamacher, H

This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.

EECS 132: Introduction to Programming in Java (614/4619)

R 03:45-04:35 PM Aug 24-Dec 04

Connamacher, H

This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.

EECS 132: Introduction to Programming in Java (615/4758)

R 01:15-02:05 PM Aug 24-Dec 04

Connamacher, H

This Recitation and the following Recitations are recommended for Computer Science and Computer Engineering Majors.

EECS 132: Introduction to Programming in Java (612/4792)

R 08:30-09:20 AM Aug 24-Dec 04

Connamacher, H

Introduction to computer programming and problem solving with the Java language. Computers, operating systems, and Java applications; software development; conditional statements; loops; methods; arrays; classes and objects; object-oriented design; unit testing; strings and text I/O; inheritance and polymorphism; GUI components; application testing; abstract classes and interfaces; exception handling; files and streams; GUI event handling; generics; collections; threads; comparison of Java to C, C++, and C#.

EECS 132: Introduction to Programming in Java (616/11226)

R 09:30-10:30 AM Aug 24-Dec 04

Connamacher, H

EECS 233: Introduction to Data Structures (100/3908)

TR 01:15-02:30 PM Aug 24-Dec 04

Lewicki, M

The programming language Java; pointers, files, and recursion. Representation and manipulation of data: one way and circular linked lists, doubly linked lists; the available space list. Different representations of stacks and queues. Representation of binary trees, trees and graphs. Hashing; searching and sorting.

EECS 246: Signals and Systems (100/3909)

MWF 02:00-02:50 PM Aug 24-Dec 04

Cavusoglu, C

Mechanical Engineering students should take this course in place of EECS 212/214.

EECS 246: Signals and Systems (110/4368)

T 04:30-05:45 PM Aug 24-Dec 04

Cavusoglu, C

Mathematical representation, characterization, and analysis of continuous-time signals and systems. Development of elementary mathematical models of continuous-time dynamic systems. Time domain and frequency domain analysis of linear time-invariant systems. Fourier series, Fourier transforms, and Laplace transforms. Sampling theorem. Filter design. Introduction to feedback control systems and feedback controller design.

EECS 246: Signals and Systems (111/4369)

T 04:30-05:45 PM Aug 24-Dec 04

Cavusoglu, C

EECS 246: Signals and Systems (112/4370)

T 06:00-07:15 PM Aug 24-Dec 04

Cavusoglu, C

EECS 246: Signals and Systems (113/4708)

R 04:30-05:45 PM Aug 24-Dec 04

Cavusoglu, C

EECS 246: Signals and Systems (114/4709)

R 06:00-07:15 PM Aug 24-Dec 04

Cavusoglu, C

EECS 281: Logic Design and Computer Organization (100/3910)

TR 10:00-11:15 AM Aug 24-Dec 04

Gurkan Cavusoglu, E

Fundamentals of digital systems in terms of both computer organization and logic level design. Organization of digital computers; information representation; boolean algebra; analysis and synthesis of combinational and sequential circuits; datapaths and register transfers; instruction sets and assembly language; input/output and communication; memory.

EECS 281: Logic Design and Computer Organization (110/4239)

T 01:15-02:05 PM Aug 24-Dec 04

Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (111/4240)

W 10:30-11:20 AM Aug 24-Dec 04

Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (112/4241)

W 11:30-12:20 PM Aug 24-Dec 04

Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (113/4690)

W 10:30-11:20 AM Aug 24-Dec 04

Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (114/4714)

W 11:30-12:20 PM Aug 24-Dec 04

Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (115/11301)

T 01:15-02:05 PM Aug 24-Dec 04

Gurkan Cavusoglu, E

EECS 293: Software Craftsmanship (100/4543)

WF 11:30-12:20 PM Aug 24-Dec 04

Liberatore, V

A course to improve programming skills, software quality, and the software development process. Software design; Version control; Control issues and routines; Pseudo-code programming process and developer testing; Defensive programming; Classes; Debugging; Self-documenting code; Refactoring.

EECS 293: Software Craftsmanship (111/4544)

W 02:00-03:50 PM Aug 24-Dec 04

Liberatore, V

Ruby section: prior knowledge of Ruby required in this section.

EECS 293: Software Craftsmanship (112/4545)

W 02:30-04:20 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (113/4578)

R 11:30-01:20 PM Aug 24-Dec 04

Liberatore, V

Ruby section: prior knowledge of Ruby required in this section.

EECS 293: Software Craftsmanship (115/4580)

R 11:30-01:20 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (116/4581)

R 12:40-02:30 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (118/4710)

R 01:15-03:05 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (119/4711)

R 02:35-04:25 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (120/4712)

R 02:35-04:25 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (121/4713)

F 02:00-03:50 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (122/4826)

F 02:00-03:50 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (126/11366)

T 12:30-02:20 PM Aug 24-Dec 04

Liberatore, V

Discussion will be rescheduled during Fall Break.

EECS 293: Software Craftsmanship (127/11367)

R 11:30-01:20 PM Aug 24-Dec 04

Liberatore, V

Scala section: prior knowledge of Scala required in this section.

EECS 293: Software Craftsmanship (128/11368)

R 02:35-04:25 PM Aug 24-Dec 04

Liberatore, V

EECS 293: Software Craftsmanship (129/11369)

R 04:40-06:30 PM Aug 24-Dec 04

Liberatore, V

EECS 301: Digital Logic Laboratory (100/3911)

F 03:00-03:50 PM Aug 24-Dec 04

Huang, M

This course is an introductory experimental laboratory for digital networks. The course introduces students to the process of design, analysis, synthesis and implementation of digital networks. The course covers the design of combinational circuits, sequential networks, registers, counters, synchronous/asynchronous Finite State Machines, register based design, and arithmetic computational blocks.

EECS 301: Digital Logic Laboratory (101/4691)

F 04:00-05:00 PM Aug 24-Dec 04

Huang, M

EECS 302: Discrete Mathematics (100/4111)

TR 08:30-09:45 AM Aug 24-Dec 04

Connamacher, H

A general introduction to basic mathematical terminology and the techniques of abstract mathematics in the context of discrete mathematics. Topics introduced are mathematical reasoning, Boolean connectives, deduction, mathematical induction, sets, functions and relations, algorithms, graphs, combinatorial reasoning. Offered as EECS 302 and MATH 304.

EECS 318: VLSI/CAD (100/3912)

TR 10:00-11:15 AM Aug 24-Dec 04

Saab, D

With Very Large Scale Integration (VLSI) technology there is an increased need for Computer-Aided Design (CAD) techniques and tools to help in the design of large digital systems that deliver both performance and functionality. Such high performance tools are of great importance in the VLSI design process, both to perform functional, logical, and behavioral modeling and verification to aid the testing process. This course discusses the fundamentals in behavioral languages, both VHDL and Verilog, with hands-on experience.

EECS 322: Integrated Circuits and Electronic Devices (100/3913)

MW 10:00-11:15 AM Aug 24-Dec 04

Zorman, C

Taught together with EECS 415.

EECS 324: Modeling and Simulation of Continuous Dynamical Systems (100/3914)

TR 01:15-02:30 PM Aug 24-Dec 04

Chankong, V

This course examines the computer-based modeling and simulation of continuous dynamical system behavior in a variety of systems including electric power systems, industrial control systems, and signal processing that are represented by a set of differential equations need to be solved numerically in order to compute and represent their behavior for study. In addition to these applications, there are many other important applications of these tools in computer games, virtual worlds, weather forecasting, and population models, to name a few examples. Numerical integration techniques are developed to perform these computations. Multiple computational engines such as Matlab, Simulink, Unity, and physics engines etc. are also examined as examples of commonly used software to solve for and visualize continuous-time system behavior. The course will incorporate the use of Grand Challenges in the areas of Energy Systems, Control Systems, and Data Analytics in order to provide motivation and a framework for problems to study in the development and application of the concepts and tools studied in the course. Various aspects of important engineering skills relating to leadership, teaming, emotional intelligence, and effective communication are integrated into the course.

EECS 325: Computer Networks I (100/3915)

WF 09:00-10:15 AM Aug 24-Dec 04

Rabinovich, M

Taught together with EECS 425.

EECS 329: Introduction to Nanomaterials: Material Synthesis, Properties and Device Applications (100/11232)

F 09:00-11:30 AM Aug 24-Dec 04

Zhao, H

The behavior of nanoscale materials is close, to atomic behavior rather than that of bulk materials. The growth of nanomaterials, such as quantum dots, has the tendency to be viewed as an art rather than science. These nanostructures have changed our view of Nature. This course is designed to provide an introduction to nanomaterials and devices to both senior undergraduate and graduate students in engineering. Topics covered include an introduction to growth issues, quantum mechanics, quantization of electronic energy levels in periodic potentials, tunneling, distribution functions and density of states, optical and electronic properties, and devices. Offered as EECS 329 and EECS 429.

EECS 338: Intro to Operating Systems and Concurrent Programming (100/10914)

TR 10:00-11:15 AM Aug 24-Dec 04

Ozsoyoglu, G

Intro to OS: OS Structures, processes, threads, CPU scheduling, deadlocks, memory management, file system implementations, virtual machines, cloud computing. Concurrent programming: fork, join, concurrent statement, critical section problem, safety and liveness properties of concurrent programs, process synchronization algorithms, semaphores, monitors. UNIX systems programming: system calls, UNIX System V IPCs, threads, RPCs, shell programming.

EECS 338: Intro to Operating Systems and Concurrent Programming (101/10949)

W 06:00-07:00 PM Aug 24-Dec 04

Ozsoyoglu, G

EECS 340: Algorithms (100/3917)

MW 12:30-01:45 PM Aug 24-Dec 04

Koyuturk, M

Fundamentals in algorithm design and analysis. Loop invariants, asymptotic notation, recurrence relations, sorting algorithms, divide-and-conquer, dynamic programming, greedy algorithms, basic graph algorithms.

EECS 340: Algorithms (101/11272)

MW 03:00-04:15 PM Aug 24-Dec 04

Liberatore, V

EECS 341: Introduction to Database Systems (100/3918)

MW 03:00-04:15 PM Aug 24-Dec 04

Zhang, X

Relational model, ER model, relational algebra and calculus, SQL, OBE, security, views, files and physical database structures, query processing and query optimization, normalization theory, concurrency control, object relational systems, multimedia databases, Oracle SQL server, Microsoft SQL server.

EECS 341: Introduction to Database Systems (101/11267)

MW 12:30-01:45 PM Aug 24-Dec 04

Ozsoyoglu, Z

EECS 342: Introduction to Global Issues (100/3919)

T 06:00-08:30 PM Aug 24-Dec 04

Sreenath, S

This systems course is based on the paradigm of the world as a complex system. Global issues such as population, world trade and financial markets, resources (energy, water, land), global climate change, and others are considered with particular emphasis put on their mutual interdependence. A reasoning support computer system which contains extensive data and a family of models is used for future assessment. Students are engaged in individual, custom-tailored, projects of creating conditions for a desirable or sustainable future based on data and scientific knowledge available. Students at CWRU will interact with students from fifteen universities that have been strategically selected in order to give global coverage to UNESCO'S Global-problematique Education Network Initiative (GENIe) in joint, participatory scenario analysis via the internet.

EECS 351: Communications and Signal Analysis (100/11039)

TR 01:15-02:30 PM Aug 24-Dec 04

Lin, W; Li, P

Fourier transform analysis and sampling of signals. AM, FM and SSB modulation and other modulation methods such as pulse code, delta, pulse position, PSK and FSK. Detection, multiplexing, performance evaluation in terms of signal-to-noise ratio and bandwidth requirements.

EECS 352: Engineering Economics and Decision Analysis (100/3920)

TR 02:45-04:00 PM Aug 24-Dec 04

Malakooti, B

Economic analysis of engineering projects, focusing on financial decisions concerning capital investments. Present worth, annual worth, internal rate of return, benefit/cost ratio. Replacement and abandonment policies, effects of taxes, and inflation. Decision making under risk and uncertainty. Decision trees. Value of information. The course will incorporate the use of Grand Challenges in the areas of Energy Systems, Control Systems, and Data Analytics in order to provide a framework for problems to study in the development and application of the concepts and tools studied in the course. Various aspects of important engineering skills relating to leadership, teaming, emotional intelligence, and effective communication are integrated into the course.

EECS 360: Manufacturing and Automated Systems (100/10930)

W 05:30-08:00 PM Aug 24-Dec 04

Malakooti, B

Formulation, modeling, planning, and control of manufacturing and automated systems with applications to computer science and engineering problems. Topics include, design of products and processes, location/spatial problems, transportation and assignment, product and process layout, group technology and clustering, cellular and network flow layouts, computer control systems, reliability and maintenance, and statistical quality control. Tools and analysis include: multi-objective optimization, artificial intelligence, and heuristics for combinatorial problems. Offered as EECS 360 and EECS 460.

EECS 366: Computer Graphics (100/11284)

MW 12:30-01:45 PM Aug 24-Dec 04

Cavusoglu, C

Theory and practice of computer graphics: Basic elements of a computer graphics rendering pipeline. Fundamentals of input and display devices. Geometrical transformations and their matrix representations. Homogeneous coordinates, projective and perspective transformations. Algorithms for clipping, hidden surface removal, and anti-aliasing. Rendering algorithms: introduction to local and global shading models, color, and lighting models for reflection, refraction, transparency. Real-time rendering methods and animation.

EECS 368: Power System Analysis I (100/4846)

M 02:00-04:30 PM Aug 24-Dec 04

Hong, M

This course introduces the steady-state modeling and analysis of electric power systems. The course discusses the modeling of essential power system network components such as transformers and transmission lines. The course also discusses important steady-state analysis of three-phase power system network, such as the power flow and economic operation studies. Through the use of PowerWorld Simulator education software, further understanding and knowledge can be gained on the operational characteristics of AC power systems. Special topics concerning new grid technologies will be discussed towards the semester end. The prerequisite requirements of the course include the concepts and computational techniques of Alternative Current (AC) circuit and electromagnetic field. Offered as EECS 368 and EECS 468.

EECS 371: Applied Circuit Design (100/4461)

TR 10:00-11:15 AM Aug 24-Dec 04

Sears, L

This course will consist of lectures and lab projects designed to provide students with an opportunity to consolidate their theoretical knowledge of electronics and to acquaint them with the art and practice of circuit and product design. The lectures will cover electrical and electronic circuits and many electronic and electrical devices and applications. Examples include mixed-signal circuits, power electronics, magnetic and piezo components, gas discharge devices, sensors, motors and generators, and power systems. In addition, there will be discussion of professional topics such as regulatory agencies, manufacturing, testing, reliability, and product cost. Weekly labs will be true "design" opportunities representing real-world applications. A specification or functional description will be provided, and the students will design the circuit, select all components, construct a breadboard, and test. The objective will be functional, pragmatic, cost-effective designs.

EECS 374: Advanced Control and Energy Systems (101/4536)

M 05:00-07:30 PM Aug 24-Dec 04

Garcia Sanz, M

This course introduces applied quantitative robust and nonlinear control engineering techniques to regulate automatically renewable energy systems in general and wind turbines in particular. The course also studies the fundamentals for dynamic multidisciplinary modeling and analysis of large multi-megawatt wind turbines (mechanics, aerodynamics, electrical systems, control concepts, etc.). The course combines lecture sessions and lab hours. The 400-level includes an experimental lab competition, where the object is to design, implement, and experimentally validate a control strategy to regulate a real system in the laboratory (helicopter control competition or similar); it will also include additional project design reports. Offered as EECS 374 and EECS 474.

EECS 374: Advanced Control and Energy Systems (110/4539)

Garcia Sanz, M

EECS 375: Applied Control (101/4832)

W 02:00-04:30 PM Aug 24-Dec 04

Garcia Sanz, M

This course provides a practical treatment of the study of control engineering systems. It emphasizes best practices in industry so that students learn what aspects of plant and control system design are critical. The course develops theory and practice for digital computer control systems; PID controller design (modes, forms and tuning methods); Control structure design (feed-forward, cascade control, predictive control, disturbance observers, multi-loop configurations, multivariable control); Actuators, sensors and common loops; Dynamic performance evaluation; and some advanced control techniques (quantitative robust control, gain-scheduling and adaptive control) to achieve a good performance over a range of operating conditions. Recommended preparation: EECS 374 or EECS 474. Offered as EECS 375 and EECS 475.

EECS 375: Applied Control (110/10937)

Garcia Sanz, M

EECS 390: Advanced Game Development Project (100/3921)

T 08:30-09:45 AM Aug 24-Dec 04, R 08:30-09:45 AM Aug 24-Dec 04

Buchner, M

This game development project course will bring together an interdisciplinary group of advanced undergraduate students in the fields of Electrical Engineering and Computer Science, Art, Music, and English to focus on the design and development of a complete, fully-functioning computer game (as an interdisciplinary team). The student teams are given complete liberty to design their own fully functional games from their original concept to a playable finished product, i.e., from the initial idea through to the wrapped box. The student teams will experience the entire game development cycle as they execute their projects. Responsibilities include creating a game idea, writing a story, developing the artwork, designing characters, implementing music and sound effects, programming and testing the game, and documenting the entire project. Recommended preparation: Junior or Senior standing and consent of instructor.

EECS 393: Software Engineering (100/3931)

MWF 11:30-12:20 PM Aug 24-Dec 04

Podgurski, H

Taught together with EECS 493

EECS 395: Senior Project in Computer Science (101/4595)

TR 01:15-02:30 PM Aug 24-Dec 04

Ozsoyoglu, G

Class meets with EECS 398 and will only be offered to students who will graduate in Fall 2013, require 395 for graduation, and will have all other requirements fulfilled. Contact instructor if you intend to enroll (mb@case.edu).

EECS 396: Independent Projects (100/4775)

Koyuturk, M

Independent projects in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering. Limited to juniors and seniors.

EECS 396: Independent Projects (101/4776)

Rabinovich, M

Independent projects in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering. Limited to juniors and seniors.

EECS 396: Independent Projects (103/4784)

Garcia Sanz, M

Independent projects in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering. Limited to juniors and seniors.

EECS 396: Independent Projects (104/12145)

Ray, S

Independent projects in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering. Limited to juniors and seniors.

EECS 397: Relay Protection (114/4534)

W 02:30-05:00 PM Aug 24-Dec 04

Prica, M

EECS390 is a pre-requisite

EECS 397: Mobile Computg/Sensor Network (115/4715)

MW 01:00-02:30 PM Aug 24-Dec 04

Huang, M

Special topics in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering.

EECS 397: Hardware Security (116/4799)

MW 03:00-04:15 PM Aug 24-Dec 04

Mandal, S

Security of computer hardware, in the domain of both general purpose and embedded systems, has emerged as a major concern. New generation of attacks by the hardware hackers and countermeasures to these attacks are rapidly emerging. To enable secure, trustworthy operation of computer hardware, it is important to understand the security issues and incorporate appropriate security measures during design, verification, test, and deployment. This course aims at providing comprehensive coverage on security issues in computer hardware covering topics such as cryptography, hardware Trojan, side-channel information leakage, hardware intellectual property protection against piracy and reverse-engineering, and security in embedded systems including software infection or bus snooping. After completing this course, students will be able to analyze and validate computer hardware for security and build secure hardware for trustworthy computing.

EECS 397: Modern Robotic Pro (118/4859)

MW 10:00-11:15 AM Aug 24-Dec 04

Newman, W

Special topics in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering.

EECS 397: Instrumentation & Measurement (119/10907)

TR 02:45-04:00 PM Aug 24-Dec 04

Mandal, S

Special topics in Computer Engineering, Computer Science, Electrical Engineering, and Systems and Control Engineering.

EECS 397: Connected Devices Workshop (120/11059)

M 03:00-05:30 PM Aug 24-Dec 04

Barendt, N

This course will be project-oriented and expose students to the current technologies, trends, and design patterns in building Internet of Things (connected devices and systems)and will include hands-on experience with several relevant technical platforms (Web/cloud, Mobile, and Embedded).

EECS 398: Engineering Projects I (100/3922)

MW 12:30-01:45 PM Aug 24-Dec 04

Merat, F

Capstone course for electrical, computer and systems and control engineering seniors. Material from previous and concurrent courses used to solve engineering design problems. Professional engineering topics such as project management, engineering design, communications, and professional ethics. Requirements include periodic reporting of progress, plus a final oral presentation and written report. Scheduled formal project presentations during last week of classes.

EECS 399: Engineering Projects II (100/3923)

MW 12:30-01:45 PM Aug 24-Dec 04

Merat, F

Continuation of EECS 398. Material from previous and concurrent courses applied to engineering design and research. Requirements include periodic reporting of progress, plus a final oral presentation and written report.

EECS 400T: Graduate Teaching I (100/3924)

Mohseni, P

EE, CE ANDSY STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 400T: Graduate Teaching I (101/3925)

Ray, S

CS STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 401: Digital Signal Processing (500/11467)

Buchner, M

Characterization of discrete-time signals and systems. Fourier analysis: the Discrete-time Fourier Transform, the Discrete-time Fourier series, the Discrete Fourier Transform and the Fast Fourier Transform. Continuous-time signal sampling and signal reconstruction. Digital filter design: infinite impulse response filters, finite impulse response filters, filter realization and quantization effects. Random signals: discrete correlation sequences and power density spectra, response of linear systems. Recommended preparation: EECS 313.

EECS 408: Introduction to Linear Systems (100/3926)

T 04:30-07:00 PM Aug 24-Dec 04

Lin, W

Analysis and design of linear feedback systems using state-space techniques. Review of matrix theory, linearization, transition maps and variations of constants formula, structural properties of state-space models, controllability and observability, realization theory, pole assignment and stabilization, linear quadratic regulator problems, observers, and the separation theorem. Recommended preparation: EECS 304.

EECS 408: Introduction to Linear Systems (500/11470)

Sreenath, S

EECS 415: Integrated Circuit Technology I (100/3927)

MW 10:00-11:15 AM Aug 24-Dec 04

Zorman, C

Taught together with EECS 322.

EECS 419: Computer System Architecture (100/3928)

M 06:00-08:00 PM Aug 24-Dec 04

Papachristou, C

Interaction between computer systems hardware and software. Pipeline techniques - instruction pipelines - arithmetic pipelines. Instruction level parallelism. Cache mechanism. I/O structures. Examples taken from existing computer systems.

EECS 419: Computer System Architecture (800/4633)

Papachristou, C

EECS 425: Computer Networks I (100/3929)

WF 09:00-10:15 AM Aug 24-Dec 04

Rabinovich, M

Taught together with EECS 325.

EECS 426: MOS Integrated Circuit Design (100/3930)

TR 01:15-02:30 PM Aug 24-Dec 04

Mohseni, P

Design of digital and analog MOS integrated circuits. IC fabrication and device models. Logic, memory, and clock generation. Amplifiers, comparators, references, and switched-capacitor circuits. Characterization of circuit performance with/without parasitics using hand analysis and SPICE circuit simulation. Recommended preparation: EECS 344 and EECS 321.

EECS 429: Introduction to Nanomaterials: Material Synthesis, Properties and Device Applications (100/11233)

F 09:00-11:30 AM Aug 24-Dec 04

Zhao, H

EECS 433: Database Systems (100/4795)

MW 03:00-04:15 PM Aug 24-Dec 04

Ozsoyoglu, Z

Basic issues in file processing and database management systems. Physical data organization. Relational databases. Database design. Relational Query Languages, SQL. Query languages. Query optimization. Database integrity and security. Object-oriented databases. Object-oriented Query Languages, OQL. Recommended preparation: EECS 341 and MATH 304.

EECS 440: Machine Learning (100/4378)

TR 10:00-11:15 AM Aug 24-Dec 04

Ray, S

Machine learning is a subfield of Artificial Intelligence that is concerned with the design and analysis of algorithms that "learn" and improve with experience, While the broad aim behind research in this area is to build systems that can simulate or even improve on certain aspects of human intelligence, algorithms developed in this area have become very useful in analyzing and predicting the behavior of complex systems. Machine learning algorithms have been used to guide diagnostic systems in medicine, recommend interesting products to customers in e-commerce, play games at human championship levels, and solve many other very complex problems. This course is focused on algorithms for machine learning: their design, analysis and implementation. We will study different learning settings, including supervised, semi-supervised and unsupervised learning. We will study different ways of representing the learning problem, using propositional, multiple-instance and relational representations. We will study the different algorithms that have been developed for these settings, such as decision trees, neural networks, support vector machines, k-means, harmonic functions and Bayesian methods. We will learn about the theoretical tradeoffs in the design of these algorithms, and how to evaluate their behavior in practice. At the end of the course, you should be able to: --Recognize situations where machine learning algorithms are applicable; --Understand, represent and formulate the learning problem; --Apply the appropriate algorithm(s), or if necessary, design your own, with an understanding of the tradeoffs involved; --Correctly evaluate the behavior of the algorithm when solving the problem.

EECS 452: Random Signals (100/4797)

W 04:30-07:00 PM Aug 24-Dec 04

Loparo, K

Fundamental concepts in probability. Probability distribution and density functions. Random variables, functions of random variables, mean, variance, higher moments, Gaussian random variables, random processes, stationary random processes, and ergodicity. Correlation functions and power spectral density. Orthogonal series representation of colored noise. Representation of bandpass noise and application to communication systems. Application to signals and noise in linear systems. Introduction to estimation, sampling, and prediction. Discussion of Poisson, Gaussian, and Markov processes.

EECS 458: Introduction to Bioinformatics (100/4721)

TR 10:00-11:15 AM Aug 24-Dec 04

Li, J

Fundamental algorithmic methods in computational molecular biology and bioinformatics discussed. Sequence analysis, pairwise and multiple alignment, probabilistic models, phylogenetic analysis, folding and structure prediction emphasized. Recommended preparation: EECS 340, EECS 233.

EECS 460: Manufacturing and Automated Systems (100/10931)

W 05:30-08:00 PM Aug 24-Dec 04

Malakooti, B

EECS 466: Computer Graphics (100/11285)

MW 12:30-01:45 PM Aug 24-Dec 04

Cavusoglu, C

Theory and practice of computer graphics: object and environment representation including coordinate transformations image extraction including perspective, hidden surface, and shading algorithms; and interaction. Covers a wide range of graphic display devices and systems with emphasis in interactive shaded graphics. Laboratory. Recommended preparation: EECS 233.

EECS 467: Commercialization and Intellectual Property Management (100/4824)

TR 04:10-05:25 PM Aug 24-Dec 04

Jankowski, J; Theofrastous, T

This interdisciplinary course covers a variety of topics, including principles of intellectual property and intellectual property management, business strategies and modeling relevant to the creation of start-up companies and exploitation of IP rights as they relate to biomedical-related inventions. The goal of this course is to address issues relating to the commercialization of biomedical-related inventions by exposing law students, MBA students, and Ph.D. candidates (in genetics and proteomics) to the challenges and opportunities encountered when attempting to develop biomedical intellectual property from the point of early discovery to the clinic and market. Specifically, this course seeks to provide students with the ability to value a given technological advance or invention holistically, focusing on issues that extend beyond scientific efficacy and include patient and practitioner value propositions, legal and intellectual property protection, business modeling, potential market impacts, market competition, and ethical, social, and healthcare practitioner acceptance. During this course, law students, MBA students, and Ph.D. candidates in genomics and proteomics will work in teams of five (two laws students, two MBA students and one Ph.D. candidate), focusing on issues of commercialization and IP management of biomedical-related inventions. The instructors will be drawn from the law school, business school, and technology-transfer office. Please visit the following website for more information: fusioninnovate.com. Offered as LAWS 5341, MGMT 467, GENE 367, GENE 467, EBME 467 and EECS 467.

EECS 468: Power System Analysis I (100/4847)

M 02:00-04:30 PM Aug 24-Dec 04

Hong, M

EECS 474: Advanced Control and Energy Systems (101/4537)

M 05:00-07:30 PM Aug 24-Dec 04

Garcia Sanz, M

EECS 474: Advanced Control and Energy Systems (110/4540)

Garcia Sanz, M

EECS 475: Applied Control (100/4833)

W 02:00-04:30 PM Aug 24-Dec 04

Garcia Sanz, M

EECS 475: Applied Control (110/10938)

Garcia Sanz, M

EECS 477: Advanced Algorithms (100/4811)

MWF 10:30-11:20 AM Aug 24-Dec 04

Liberatore, V

Design and analysis of efficient algorithms, with emphasis on network flow, combinatorial optimization, and randomized algorithms. Linear programming: duality, complementary slackness, total unimodularity. Minimum cost flow: optimality conditions, algorithms, applications. Game theory: two-person zero-sum games, minimax theorems. Probabilistic analysis and randomized algorithms: examples and lower bounds. Approximation algorithms for NP-hard problems: examples, randomized rounding of linear programs.

EECS 480Q: Regulatory Policy and Regulations (100/4828)

T 06:00-07:00 PM Aug 24-Dec 04

Mehregany, M; Saldivar, E

The class times listed are PST (Pacific Standard Time)

EECS 480Q: Regulatory Policy and Regulations (800/4829)

Mehregany, M; Saldivar, E

Introduction of wireless health technologies: spectrum, licensed versus unlicensed; personal area networks; body area networks; ultra-wideband low energy level short-range radios; wireless local area networks; wide area networks. The Federal system: separation of powers; the executive branch and its departments; the House of Representatives and its committees; the Senate and its committees; the FCC; policy versus regulatory versus legislative. What is a medical device: FDA; classification system; radiation-emitting products; software; RF in medical devices; converged medical devices; international aspects. Regulation of health information technology and wireless health: American Recovery and Reinvestment Act; Patient Protection and Affordable Care Act; FCC/FDA MoU; CMS and Reimbursement; privacy and security. Offered as EECS 480Q and EBME 480Q.

EECS 484: Computational Intelligence I: Basic Principles (100/10932)

TR 02:45-04:00 PM Aug 24-Dec 04

Newman, W

This course is concerned with learning the fundamentals of a number of computational methodologies which are used in adaptive parallel distributed information processing. Such methodologies include neural net computing, evolutionary programming, genetic algorithms, fuzzy set theory, and "artificial life." These computational paradigms complement and supplement the traditional practices of pattern recognition and artificial intelligence. Functionalities covered include self-organization, learning a model or supervised learning, optimization, and memorization.

EECS 485: VLSI Systems (100/3932)

W 06:00-08:30 PM Aug 24-Dec 04

Saab, D

Basic MOSFET models, inverters, steering logic, the silicon gate, nMOS process, design rules, basic design structures (e.g., NAND and NOR gates, PLA, ROM, RAM), design methodology and tools (spice, N.mpc, Caesar, mkpla), VLSI technology and system architecture. Requires project and student presentation, laboratory.

EECS 493: Software Engineering (100/4469)

MWF 11:30-12:20 PM Aug 24-Dec 04

Podgurski, H

Taught together with EECS 393

EECS 493: Software Engineering (800/4525)

Podgurski, H

Topics: Introduction to software engineering; software lifecycle models; development team organization and project management; requirements analysis and specification techniques; software design techniques; programming practices; software validation techniques; software maintenance practices; software engineering ethics. Undergraduates work in teams to complete a significant software development project. Graduate students are required to complete a research project. Offered as EECS 393 and EECS 493.

EECS 497: Artificial Intelligence: Statistical Natural Language Processing (100/11075)

TR 03:00-04:15 PM Aug 24-Dec 04

Ray, S

This course gives students an overview of the stat of the art in natural language processing. We will discuss computational aspects of language modeling through probabilistic models, computational approaches to syntax (parsing) and semantic representations, discourse and dialog. We will study the applications of these techniques to a variety of problems including information extraction, translation and summarization. At the end of the course a student should be able to (i) understand the various statistical models and algorithms for NLP (ii) modify them as needed or design novel approaches for specific NLP tasks and (iii) understand how to evaluate the performance of these models and compare them to alternatives.

EECS 500: EECS Colloquium (100/3933)

TR 11:30-12:30 PM Aug 24-Dec 04

Hong, M

Seminars on current topics in Electrical Engineering and Computer Science.

EECS 500T: Graduate Teaching II (100/3934)

Mohseni, P

EE, CE, AND SY STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 500T: Graduate Teaching II (101/3935)

Ray, S

CS STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 600: Relay Protection (108/4848)

W 02:30-05:00 PM Aug 24-Dec 04

Prica, M

"This course will study the formulation and solution of decision making problems by automated agents. Topics covered include one-shot decision making (decision trees and influence diagrams), Markov decision processes (MDPs) , automated classical and probabilistic planning, reinforcement learning (RL), hierarchical planning and RL, partially observable MDPs, Bayesian RL, collaborative multi-agent systems. Pre-requisite: EECS 391 (Introduction to AI) or consent of instructor."

EECS 600: Modern Robotic Prog (110/4860)

MW 10:00-11:15 AM Aug 24-Dec 04

Newman, W

Offered as EECS 600 and SYBB 600.

EECS 600: Instrumentation & Measurement (111/4869)

TR 02:45-04:00 PM Aug 24-Dec 04

Mandal, S

Offered as EECS 600 and SYBB 600.

EECS 600: Mobile Computg/Sensor Network (114/10967)

MW 01:00-02:30 PM Aug 24-Dec 04

Huang, M

Offered as EECS 600 and SYBB 600.

EECS 600T: Graduate Teaching III (100/3936)

Mohseni, P

EE, CE, AND SY STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 600T: Graduate Teaching III (101/3937)

Ray, S

CS STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 601: Independent Study (100/4759)

Bhunia, S

EECS 601: Independent Study (101/4771)

Zhao, H

EECS 601: Independent Study (102/4864)

Mohseni, P

EECS 601: Independent Study (103/4872)

Ray, S

EECS 601: Independent Study (104/11907)

Bebek, G

EECS 601: Independent Study (105/11922)

Mandal, S

EECS 601: Independent Study (106/12053)

Podgurski, H

EECS 649: Project M.S. (100/3938)

Bhunia, S

M.S. Project for EE Plan B students.

EECS 649: Project M.S. (102/3939)

Buchner, M

EECS 649: Project M.S. (116/3940)

Cavusoglu, C

EECS 649: Project M.S. (104/3941)

Chankong, V

EECS 649: Project M.S. (107/4203)

Koyuturk, M

EECS 649: Project M.S. (108/4204)

Li, J

EECS 649: Project M.S. (109/4205)

Liberatore, V

EECS 649: Project M.S. (110/4206)

Lin, W

EECS 649: Project M.S. (111/4207)

Loparo, K

EECS 649: Project M.S. (112/4208)

Malakooti, B

EECS 649: Project M.S. (114/4209)

Mehregany, M

EECS 649: Project M.S. (115/4210)

Merat, F

EECS 649: Project M.S. (117/4211)

Mohseni, P

EECS 649: Project M.S. (118/4212)

Newman, W

EECS 649: Project M.S. (119/4213)

Ozsoyoglu, G

EECS 649: Project M.S. (120/4214)

Ozsoyoglu, Z

EECS 649: Project M.S. (121/4215)

Papachristou, C

EECS 649: Project M.S. (122/4216)

Podgurski, H

EECS 649: Project M.S. (123/4217)

Rabinovich, M

EECS 649: Project M.S. (124/4218)

Saab, D

EECS 649: Project M.S. (125/4219)

Sreenath, S

EECS 649: Project M.S. (130/4220)

Zhang, G

EECS 649: Project M.S. (132/4222)

Zorman, C

EECS 649: Project M.S. (133/4573)

Zhao, H

EECS 649: Project M.S. (134/4574)

Zhang, X

EECS 649: Project M.S. (135/4637)

Quinn, R

EECS 649: Project M.S. (136/11937)

Prica, M

EECS 651: Thesis M.S. (100/3942)

Bhunia, S

EECS 651: Thesis M.S. (102/3943)

Buchner, M

EECS 651: Thesis M.S. (103/3944)

Cavusoglu, C

EECS 651: Thesis M.S. (104/3945)

Chankong, V

EECS 651: Thesis M.S. (107/3946)

Koyuturk, M

EECS 651: Thesis M.S. (108/3947)

Li, J

EECS 651: Thesis M.S. (109/3948)

Liberatore, V

EECS 651: Thesis M.S. (110/3949)

Lin, W

EECS 651: Thesis M.S. (111/3950)

Loparo, K

EECS 651: Thesis M.S. (112/3951)

Malakooti, B

EECS 651: Thesis M.S. (114/3952)

Mehregany, M

EECS 651: Thesis M.S. (115/3953)

Merat, F

EECS 651: Thesis M.S. (117/3954)

Mohseni, P

EECS 651: Thesis M.S. (118/3955)

Newman, W

EECS 651: Thesis M.S. (119/3956)

Ozsoyoglu, G

EECS 651: Thesis M.S. (120/3957)

Ozsoyoglu, Z

EECS 651: Thesis M.S. (121/3958)

Papachristou, C

EECS 651: Thesis M.S. (122/3959)

Podgurski, H

EECS 651: Thesis M.S. (123/3960)

Rabinovich, M

EECS 651: Thesis M.S. (124/3961)

Saab, D

EECS 651: Thesis M.S. (125/3962)

Sreenath, S

EECS 651: Thesis M.S. (130/4223)

Zhang, G

EECS 651: Thesis M.S. (132/4225)

Zorman, C

EECS 651: Thesis M.S. (134/4381)

Ray, S

EECS 651: Thesis M.S. (135/4431)

Garcia Sanz, M

EECS 651: Thesis M.S. (136/4432)

Lewicki, M

EECS 651: Thesis M.S. (137/4475)

Quinn, R

EECS 651: Thesis M.S. (138/4563)

Griswold, M

EECS 651: Thesis M.S. (139/4575)

Zhang, X

EECS 651: Thesis M.S. (140/4576)

Zhao, H

EECS 651: Thesis M.S. (141/4621)

Connamacher, H

EECS 651: Thesis M.S. (142/4623)

Feng, P

EECS 651: Thesis M.S. (143/4625)

Lee, G

EECS 651: Thesis M.S. (144/4627)

Ko, W

EECS 651: Thesis M.S. (145/4865)

Hong, M

EECS 651: Thesis M.S. (146/4873)

Gurkan Cavusoglu, E

EECS 651: Thesis M.S. (147/11888)

Huang, M

EECS 651: Thesis M.S. (148/11900)

Mandal, S

EECS 651: Thesis M.S. (149/11983)

Prica, M

EECS 651: Thesis M.S. (150/12025)

Sahoo, S

EECS 701: Dissertation Ph.D. (100/3963)

Bhunia, S

EECS 701: Dissertation Ph.D. (102/3964)

Buchner, M

EECS 701: Dissertation Ph.D. (103/3965)

Cavusoglu, C

EECS 701: Dissertation Ph.D. (104/3966)

Chankong, V

EECS 701: Dissertation Ph.D. (107/3967)

Koyuturk, M

EECS 701: Dissertation Ph.D. (108/3968)

Li, J

EECS 701: Dissertation Ph.D. (109/3969)

Liberatore, V

EECS 701: Dissertation Ph.D. (110/3970)

Lin, W

EECS 701: Dissertation Ph.D. (111/3971)

Loparo, K

EECS 701: Dissertation Ph.D. (112/3972)

Malakooti, B

EECS 701: Dissertation Ph.D. (113/3973)

Quinn, R

EECS 701: Dissertation Ph.D. (114/3974)

Mehregany, M

EECS 701: Dissertation Ph.D. (115/3975)

Merat, F

EECS 701: Dissertation Ph.D. (117/3976)

Mohseni, P

EECS 701: Dissertation Ph.D. (118/3977)

Newman, W

EECS 701: Dissertation Ph.D. (119/3978)

Ozsoyoglu, G

EECS 701: Dissertation Ph.D. (120/3979)

Ozsoyoglu, Z

EECS 701: Dissertation Ph.D. (121/3980)

Papachristou, C

EECS 701: Dissertation Ph.D. (122/3981)

Podgurski, H

EECS 701: Dissertation Ph.D. (123/3982)

Rabinovich, M

EECS 701: Dissertation Ph.D. (124/3983)

Saab, D

EECS 701: Dissertation Ph.D. (125/3984)

Sreenath, S

EECS 701: Dissertation Ph.D. (130/4200)

Zhang, G

EECS 701: Dissertation Ph.D. (132/4202)

Zorman, C

EECS 701: Dissertation Ph.D. (134/4362)

Ko, W

EECS 701: Dissertation Ph.D. (136/4382)

Ray, S

EECS 701: Dissertation Ph.D. (137/4433)

Garcia Sanz, M

EECS 701: Dissertation Ph.D. (138/4434)

Lewicki, M

EECS 701: Dissertation Ph.D. (139/4549)

Allman, M

EECS 701: Dissertation Ph.D. (140/4550)

Yu, X

EECS 701: Dissertation Ph.D. (141/4559)

Zhao, H

EECS 701: Dissertation Ph.D. (142/4562)

Feng, P

EECS 701: Dissertation Ph.D. (143/4577)

Zhang, X

EECS 701: Dissertation Ph.D. (144/4866)

Hong, M

EECS 701: Dissertation Ph.D. (145/11173)

Prica, M

EECS 701: Dissertation Ph.D. (146/11616)

Mandal, S

EECS 701: Dissertation Ph.D. (147/11834)

Griswold, M

EECS 701: Dissertation Ph.D. (148/11894)

Huang, M

EECS 701: Dissertation Ph.D. (149/12043)

Li, P