Subject: EECS
Term: Fall 2019

EECS 132: Introduction to Programming in Java (600/4475)
MWF 02:15-03:05 PM Aug 26-Dec 06
Connamacher, H

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

EECS 132: Introduction to Programming in Java (610/4476)
W 03:20-04:10 PM Aug 26-Dec 06
Connamacher, H

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

EECS 132: Introduction to Programming in Java (611/4477)
W 04:25-05:15 PM Aug 26-Dec 06
Connamacher, H

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

EECS 132: Introduction to Programming in Java (613/4526)
R 10:00-10:50 AM Aug 26-Dec 06
Connamacher, H

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

EECS 132: Introduction to Programming in Java (614/4537)
R 11:30-12:20 PM Aug 26-Dec 06
Connamacher, H

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

EECS 132: Introduction to Programming in Java (615/4629)
R 01:00-01:50 PM Aug 26-Dec 06
Connamacher, H

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

EECS 132: Introduction to Programming in Java (612/4648)
R 08:45-09:35 AM Aug 26-Dec 06
Connamacher, H

An introduction to modern programming language features, computer programming and algorithmic problem solving with an emphasis on the Java language. Computers and code compilation; conditional statements, subprograms, loops, methods; object-oriented design, inheritance and polymorphism, abstract classes and interfaces; types, type systems, generic types, abstract data types, strings, arrays, linked lists; software development, modular code design, unit testing; strings, text and file I/O; GUI components, GUI event handling; threads; comparison of Java to C, C++, and C#.

EECS 132: Introduction to Programming in Java (616/4705)
F 10:35-11:25 AM Aug 26-Dec 06
Connamacher, H

An introduction to modern programming language features, computer programming and algorithmic problem solving with an emphasis on the Java language. Computers and code compilation; conditional statements, subprograms, loops, methods; object-oriented design, inheritance and polymorphism, abstract classes and interfaces; types, type systems, generic types, abstract data types, strings, arrays, linked lists; software development, modular code design, unit testing; strings, text and file I/O; GUI components, GUI event handling; threads; comparison of Java to C, C++, and C#.

EECS 132: Introduction to Programming in Java (617/4759)
W 05:30-06:20 PM Aug 26-Dec 06
Connamacher, H

An introduction to modern programming language features, computer programming and algorithmic problem solving with an emphasis on the Java language. Computers and code compilation; conditional statements, subprograms, loops, methods; object-oriented design, inheritance and polymorphism, abstract classes and interfaces; types, type systems, generic types, abstract data types, strings, arrays, linked lists; software development, modular code design, unit testing; strings, text and file I/O; GUI components, GUI event handling; threads; comparison of Java to C, C++, and C#.

EECS 132: Introduction to Programming in Java (618/5002)
R 02:30-03:20 PM Aug 26-Dec 06
Connamacher, H

An introduction to modern programming language features, computer programming and algorithmic problem solving with an emphasis on the Java language. Computers and code compilation; conditional statements, subprograms, loops, methods; object-oriented design, inheritance and polymorphism, abstract classes and interfaces; types, type systems, generic types, abstract data types, strings, arrays, linked lists; software development, modular code design, unit testing; strings, text and file I/O; GUI components, GUI event handling; threads; comparison of Java to C, C++, and C#.

EECS 233: Introduction to Data Structures (100/3984)
TR 01:00-02:15 PM Aug 26-Dec 06
Ayday, E

Different representations of data: lists, stacks and queues, trees, graphs, and files. Manipulation of data: searching and sorting, hashing, recursion and higher order functions. Abstract data types, templating, and the separation of interface and implementation. Introduction to asymptotic analysis. The Java language is used to illustrate the concepts and as an implementation vehicle throughout the course.

EECS 246: Signals and Systems (100/3985)
TR 02:30-03:45 PM Aug 26-Dec 06
Loparo, K

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

EECS 246: Signals and Systems (110/4346)
T 04:00-05:15 PM Aug 26-Dec 06
Loparo, K

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 281: Logic Design and Computer Organization (100/3986)
TR 10:00-11:15 AM Aug 26-Dec 06
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 (110/4233)
T 01:00-01:50 PM Aug 26-Dec 06
Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (111/4234)
W 10:35-11:25 AM Aug 26-Dec 06
Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (112/4235)
W 11:40-12:30 PM Aug 26-Dec 06
Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (114/4600)
W 11:40-12:30 PM Aug 26-Dec 06
Gurkan Cavusoglu, E

Recitation for EECS 281

EECS 281: Logic Design and Computer Organization (115/4711)
T 01:00-01:50 PM Aug 26-Dec 06
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 293: Software Craftsmanship (100/4487)
WF 11:40-12:30 PM Aug 26-Dec 06
Liberatore, V

"See also https://bit.ly/2GHjbeA."

EECS 293: Software Craftsmanship (102/10958)
R 02:30-04:20 PM Aug 26-Dec 06
Liberatore, V

Swift and Java section

EECS 293: Software Craftsmanship (103/10959)
R 11:30-01:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293: Software Craftsmanship (104/10960)
R 02:30-04:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293: Software Craftsmanship (105/10961)
F 02:10-04:00 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293: Software Craftsmanship (106/11021)
F 03:20-05:10 PM Aug 26-Dec 06
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. Offered as EECS 293 and EECS 293N.

EECS 293: Software Craftsmanship (107/11131)
W 12:45-02:35 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293: Software Craftsmanship (108/11132)
R 11:30-01:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293: Software Craftsmanship (109/11133)
R 05:30-07:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293: Software Craftsmanship (111/11134)
F 02:15-04:05 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293: Software Craftsmanship (112/11682)
T 11:30-01:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (100/4765)
WF 11:40-12:30 PM Aug 26-Dec 06
Liberatore, V

"See also https://bit.ly/2GHjbeA."

EECS 293N: Software Craftsmanship (102/10962)
R 02:30-04:20 PM Aug 26-Dec 06
Liberatore, V

Swift and Java section

EECS 293N: Software Craftsmanship (103/10963)
R 11:30-01:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (104/10964)
R 02:30-04:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (105/10965)
F 02:10-04:00 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (106/11022)
F 03:20-05:10 PM Aug 26-Dec 06
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. Offered as EECS 293 and EECS 293N.

EECS 293N: Software Craftsmanship (107/11135)
W 12:45-02:35 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (108/11136)
R 11:30-01:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (109/11137)
R 05:30-07:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (111/11138)
F 02:15-04:05 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 293N: Software Craftsmanship (112/11683)
T 11:30-01:20 PM Aug 26-Dec 06
Liberatore, V

Java section

EECS 297: Introduction to Python (100/11391)
R 07:00-08:15 PM Aug 26-Oct 29
Sargent, M

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

EECS 297: AI in Healthcare (101/11564)
W 08:00-09:15 AM Sep 04-Nov 20
Nazha, A

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

EECS 301: Digital Logic Laboratory (100/3987)
F 03:20-04:10 PM Aug 26-Dec 06
Papachristou, C

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 302: Discrete Mathematics (100/4141)
MWF 09:30-10:20 AM Aug 26-Dec 06
Chankong, V

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 302: Discrete Mathematics (102/4812)
MWF 10:35-11:25 AM Aug 26-Dec 06
Xu, S

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 303: Embedded Systems Design and Laboratory (100/4855)
T 04:50-06:05 PM Aug 26-Dec 06
Papachristou, C

The purpose of this Course and Laboratory is to expose and train the students in modern embedded systems software and hardware design techniques and practices including networking and mobile connectivity. The rationale for the Course and Lab is based on the explosive growth of embedded systems in the industry, specifically industrial automation, aviation, surveillance, medical devices, but also common consumer products. The course topics cover a wide range of material as follows. Microcontroller systems based on the ARM processor. Essential components, memories, busses interfaces. Devices, peripherals, GPIOs, device drivers. Sensors and Actuators, A/D, D/A, DSP. Embedded Linux, kernels, kernel modules, compilers and assemblers. Libraries, and debugging facilities. The Lab will be based on common platforms such as Raspberry pi, Arduino, ARM embed, supported by a network of Linux workstations.

EECS 303: Embedded Systems Design and Laboratory (110/4968)
R 04:50-06:05 PM Aug 26-Dec 06
Papachristou, C

The purpose of this Course and Laboratory is to expose and train the students in modern embedded systems software and hardware design techniques and practices including networking and mobile connectivity. The rationale for the Course and Lab is based on the explosive growth of embedded systems in the industry, specifically industrial automation, aviation, surveillance, medical devices, but also common consumer products. The course topics cover a wide range of material as follows. Microcontroller systems based on the ARM processor. Essential components, memories, busses interfaces. Devices, peripherals, GPIOs, device drivers. Sensors and Actuators, A/D, D/A, DSP. Embedded Linux, kernels, kernel modules, compilers and assemblers. Libraries, and debugging facilities. The Lab will be based on common platforms such as Raspberry pi, Arduino, ARM embed, supported by a network of Linux workstations.

EECS 318: VLSI/CAD (100/3988)
TR 01:00-02:15 PM Aug 26-Dec 06
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 (100/3989)
TR 08:30-09:45 AM Aug 26-Dec 06
Mehregany, M

Taught together with EECS 415.

EECS 324: Modeling and Simulation of Continuous Dynamical Systems (100/3990)
TR 01:00-02:15 PM Aug 26-Dec 06
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 (100/3991)
MW 12:45-02:00 PM Aug 26-Dec 06
Rabinovich, M

An introduction to computer networks and the Internet. Applications: http, ftp, e-mail, DNS, socket programming. Transport: UDP, TCP, reliable data transfer, and congestion control. Network layer: IP, routing, and NAT. Link layer: taxonomy, Ethernet, 802.11. Offered as EECS 325 and EECS 325N.

EECS 325N: Computer Networks I (100/4766)
MW 12:45-02:00 PM Aug 26-Dec 06
Rabinovich, M

An introduction to computer networks and the Internet. Applications: http, ftp, e-mail, DNS, socket programming. Transport: UDP, TCP, reliable data transfer, and congestion control. Network layer: IP, routing, and NAT. Link layer: taxonomy, Ethernet, 802.11. Offered as EECS 325 and EECS 325N.

EECS 326: Instrumentation Electronics (100/4910)
TR 02:30-03:45 PM Aug 26-Dec 06
Mandal, S

A second course in instrumentation with emphasis on sensor interface electronics. General concepts in measurement systems, including accuracy, precision, sensitivity, linearity, and resolution. The physics and modeling of resistive, reactive, self-generating, and direct-digital sensors. Signal conditioning for same, including bridge circuits, coherent detectors, and a variety of amplifier topologies: differential, instrumentation, charge, and transimpedance. Noise and drift in amplifiers and resistors. Practical issues of interference, including grounding, shielding, supply/return, and isolation amplifiers.

EECS 338: Intro to Operating Systems and Concurrent Programming (100/4682)
TR 04:00-05:15 PM Aug 26-Dec 06
Loui, R

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. Offered as EECS 338 and EECS 338N.

EECS 338: Intro to Operating Systems and Concurrent Programming (101/4685)
W 04:50-06:05 PM Aug 26-Dec 06
Loui, R

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. Offered as EECS 338 and EECS 338N.

EECS 338N: Intro to Operating Systems and Concurrent Programming (100/4767)
TR 04:00-05:15 PM Aug 26-Dec 06
Loui, R

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. Offered as EECS 338 and EECS 338N.

EECS 338N: Intro to Operating Systems and Concurrent Programming (101/4771)
W 04:50-06:05 PM Aug 26-Dec 06
Loui, R

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. Offered as EECS 338 and EECS 338N.

EECS 340: Algorithms (100/3992)
MWF 03:20-04:10 PM Aug 26-Dec 06
Connamacher, H

Fundamentals in algorithm design and analysis. Loop invariants, asymptotic notation, recurrence relations, sorting algorithms, divide-and-conquer, dynamic programming, greedy algorithms, basic graph algorithms. Offered as EECS 340 and EECS 340N.

EECS 340N: Algorithms (100/4768)
MWF 03:20-04:10 PM Aug 26-Dec 06
Connamacher, H

Fundamentals in algorithm design and analysis. Loop invariants, asymptotic notation, recurrence relations, sorting algorithms, divide-and-conquer, dynamic programming, greedy algorithms, basic graph algorithms. Offered as EECS 340 and EECS 340N.

EECS 341: Introduction to Database Systems (100/4709)
TR 02:30-03:45 PM Aug 26-Dec 06
Xiao, 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. Offered as EECS 341 and EECS 341N.

EECS 341N: Introduction to Database Systems (100/4769)
TR 02:30-03:45 PM Aug 26-Dec 06
Xiao, 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. Offered as EECS 341 and EECS 341N.

EECS 342: Introduction to Global Issues (100/3993)
T 07:00-09:30 PM Aug 26-Dec 06
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 349: Computer Security (100/10737)
TR 10:00-11:15 AM Aug 26-Dec 06
Ye, F

General types of security attacks; approaches to prevention; secret key and public key cryptography; message authentication and hash functions; digital signatures and authentication protocols; information gathering; password cracking; spoofing; session hijacking; denial of service attacks; buffer overruns; viruses, worms, etc., principles of secure software design, threat modeling; access control; least privilege; storing secrets; socket security; firewalls; intrusions; auditing; mobile security. Recommended preparation: EECS 132, EECS 293, EECS 325 and EECS 338. Offered as EECS 349 and EECS 444.

EECS 351: Communications and Signal Analysis (100/7775)
TR 04:00-05:15 PM Aug 26-Dec 06
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 (100/3994)
TR 02:30-03:45 PM Aug 26-Dec 06
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 (100/10923)
TR 05:30-06:45 PM Aug 26-Dec 06
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 (100/7776)
MW 12:45-02:00 PM Aug 26-Dec 06
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. Offered as EECS 366 and EECS 466.

EECS 368: Power System Analysis I (100/7777)
MW 05:30-06:45 PM Aug 26-Dec 06
Prica, 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 (100/4421)
TR 10:00-11:15 AM Aug 26-Dec 06
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 373: Modern Robot Programming (100/10826)
TR 01:00-02:15 PM Aug 26-Dec 06
Lee, G

The goal of this course is to learn modern methods for building up robot capabilities using the Robot Operating System (ROS). Through a sequence of assignments, students learn how to write software to control both simulated and physical robots. Material includes: interfacing software to robot I/O; path and trajectory planning for robot arms; object identification and localization from 3-D sensing; manipulation planning; and development of graphical interfaces for supervisory robot control. Laboratory assignments are scheduled in small groups to explore implementations on specific robots. Graduate students will also perform an independent project. Offered as EECS 373 and EECS 473.

EECS 373L: Modern Robot Programming Lab (100/11098)
Lee, G

Lab to accompany EECS 373, Modern Robot Programming.

EECS 390: Advanced Game Development Project (100/3995)
R 08:30-09:45 AM Aug 26-Dec 06, T 08:30-09:45 AM Aug 26-Dec 06
Fu, 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 391: Introduction to Artificial Intelligence (100/4753)
TR 10:00-11:15 AM Aug 26-Dec 06
Lewicki, M

This course is an introduction to artificial intelligence. We will study the concepts that underlie intelligent systems. Topics covered include problem solving with search, constraint satisfaction, adversarial games, knowledge representation and reasoning using propositional and first order logic, reasoning under uncertainty, introduction to machine learning, automated planning, reinforcement learning and natural language processing. Recommended: basic knowledge of probability and statistics.

EECS 393: Software Engineering (100/4004)
MWF 11:40-12:30 PM Aug 26-Dec 06
Podgurski, H

Taught together with EECS 493

EECS 393N: Software Engineering (100/4770)
MWF 11:40-12:30 PM Aug 26-Dec 06
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, EECS 393N, and EECS 493.

EECS 395: Senior Project in Computer Science (101/4524)
TR 01:00-02:15 PM Aug 26-Dec 06
Xu, S

Capstone course for computer science seniors. Material from previous and concurrent courses used to solve computer programming problems and to develop software systems. 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 396: Independent Projects (100/11189)
Mandal, S

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

EECS 396: Independent Projects (102/11661)
Miri Lavasani, S

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

EECS 396: Independent Projects (103/11701)
Papachristou, C

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

EECS 397: Introduction to Python (100/11392)
R 07:00-08:15 PM Aug 29-Oct 29
Sargent, M

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

EECS 397: AI in Healthcare (102/11563)
W 08:00-09:15 AM Sep 04-Nov 20
Nazha, A

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

EECS 398: Engineering Projects I (100/3996)
MW 12:45-02:00 PM Aug 26-Dec 06
Lee, G

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, multidisciplinary teaming, 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 (100/3997)
MW 12:45-02:00 PM Aug 26-Dec 06
Lee, G

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 (100/3998)
Mohseni, P

EE, CE ANDSY STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 400T: Graduate Teaching I (101/3999)
Ray, S

CS STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 401: Digital Signal Processing (500/10980)
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 407: Engineering Economics and Financial Analysis (500/4899)
Chankong, V

In this course, money and profit as measures of "goodness" in engineering design are studied. Methods for economic analysis of capital investments are developed and the financial evaluation of machinery, manufacturing processes, buildings, R&D, personnel development, and other long-lived investments is emphasized. Optimization methods and decision analysis techniques are examined to identify economically attractive alternatives. Basic concepts of cost accounting are also covered. Topics include: economics criteria for comparing projects: present worth, annual worth analysis; depreciation and taxation; retirement and replacement; effect of inflation and escalation on economic evaluations; case studies; use of optimization methods to evaluate many alternatives; decision analysis; accounting fundamentals: income and balance sheets; cost accounting. Offered as EECS 407 and EPOM 407.

EECS 408: Introduction to Linear Systems (100/4839)
TR 04:00-05:15 PM Aug 26-Dec 06
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 (500/4900)
Sreenath, S

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 410: Mobile Health (mHealth) Technology (100/10979)
MW 12:45-02:00 PM Aug 26-Dec 06
Huang, M

Advances in communications, computer, and medical technology have facilitated the practice of personalized health, which utilizes sensory computational communication systems to support improved and more personalized healthcare and healthy lifestyle choices. The current proliferation of broadband wireless services, along with more powerful and convenient handheld devices, is helping to introduce real-time monitoring and guidance for a wide array of patients. Indeed, a large research community and a nascent industry is beginning to connect medical care with technology developers, vendors of wireless and sensing hardware systems, network service providers, and enterprise data management communities. Students in the course and labs will explore cutting-edge technologies in 1) information technologies and 2) healthcare/medical applications, through lectures, lab assignments, exams, presentations, and final projects. The overall course objectives are to introduce electrical engineering, computer engineering, and computer science students the fundamentals of wearable sensors, mobile health informatics, big data analysis, telehealthcare security & privacy, and human computer interaction considerations.

EECS 415: Integrated Circuit Technology I (100/11181)
TR 08:30-09:45 AM Aug 26-Dec 06
Mehregany, M

Review of semiconductor technology. Device fabrication processing, material evaluation, oxide passivation, pattern transfer technique, diffusion, ion implantation, metallization, probing, packaging, and testing. Design and fabrication of passive and active semi-conductor devices. Recommended preparation: EECS 322.

EECS 419: Computer System Architecture (100/10925)
M 06:30-09:00 PM Aug 26-Dec 06
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 (800/11504)
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 425: Computer Networks I (100/8014)
MW 12:45-02:00 PM Aug 26-Dec 06
Rabinovich, M

An introduction to computer networks and the Internet. Applications: http, ftp, e-mail, DNS, socket programming. Transport: UDP, TCP, reliable data transfer, and congestion control. Network layer: IP, routing and NAT. Link layer: taxonomy, Ethernet, 802.11. Recommended preparation: EECS 338 or consent of instructor.

EECS 426: MOS Integrated Circuit Design (100/10834)
TR 01:00-02:15 PM Aug 26-Dec 06
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 428: Computer Communications Networks II (100/10736)
TR 08:30-09:45 AM Aug 26-Dec 06
Wang, A

Introduction to topics and methodology in computer networks and middleware research. Traffic characterization, stochastic models, and self-similarity. Congestion control (Tahoe, Reno, Sack). Active Queue Management (RED, FQ) and explicit QoS. The Web: overview and components, HTTP, its interaction with TCP, caching. Overlay networks and CDN. Expected work includes a course-long project on network simulation, a final project, a paper presentation, midterm, and final test. Recommended preparation: EECS 425 or permission of instructor.

EECS 440: Machine Learning (100/4352)
TR 10:00-11:15 AM Aug 26-Dec 06
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 444: Computer Security (100/4911)
TR 10:00-11:15 AM Aug 26-Dec 06
Ye, F

General types of security attacks; approaches to prevention; secret key and public key cryptography; message authentication and hash functions; digital signatures and authentication protocols; information gathering; password cracking; spoofing; session hijacking; denial of service attacks; buffer overruns; viruses, worms, etc., principles of secure software design, threat modeling; access control; least privilege; storing secrets; socket security; firewalls; intrusions; auditing; mobile security. Recommended preparation: EECS 132, EECS 293, EECS 325 and EECS 338. Offered as EECS 349 and EECS 444.

EECS 458: Introduction to Bioinformatics (100/4603)
TR 01:00-02:15 PM Aug 26-Dec 06
Li, J

Fundamental algorithmic and statistical methods in computational molecular biology and bioinformatics will be discussed. Topics include introduction to molecular biology and genetics, DNA sequence analysis, polymorphisms and personal genomics, structural variation analysis, gene mapping and haplotyping algorithms, phylogenetic analysis, biological network analysis, and computational drug discovery. Much of the course will focus on the algorithmic techniques, including but not limited to, dynamic programming, hidden Markov models, string algorithms, graph theories and algorithms, and some representative data mining algorithms. Paper presentations and course projects are also required.

EECS 460: Manufacturing and Automated Systems (100/10924)
TR 05:30-06:45 PM Aug 26-Dec 06
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 466: Computer Graphics (100/8013)
MW 12:45-02:00 PM Aug 26-Dec 06
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. Offered as EECS 366 and EECS 466.

EECS 467: Commercialization and Intellectual Property Management (100/4656)
TR 04:00-05:20 PM Aug 26-Nov 29
Jankowski, J; Nard, C; 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 (500/5025)
Prica, 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 473: Modern Robot Programming (100/4952)
TR 01:00-02:15 PM Aug 26-Dec 06
Lee, G

The goal of this course is to learn modern methods for building up robot capabilities using the Robot Operating System (ROS). Through a sequence of assignments, students learn how to write software to control both simulated and physical robots. Material includes: interfacing software to robot I/O; path and trajectory planning for robot arms; object identification and localization from 3-D sensing; manipulation planning; and development of graphical interfaces for supervisory robot control. Laboratory assignments are scheduled in small groups to explore implementations on specific robots. Graduate students will also perform an independent project. Offered as EECS 373 and EECS 473.

EECS 477: Advanced Algorithms (100/4757)
MWF 10:35-11:25 AM Aug 26-Dec 06
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 480F: Physicians, Hospitals and Clinics (100/11593)
Mehregany, M; Saldivar, E

The class times listed are PST (Pacific Standard Time).

EECS 480F: Physicians, Hospitals and Clinics (800/11594)
Mehregany, M; Saldivar, E

Rotation through one or more health care provider facilities for a first-hand understanding of care delivery practice, coordination, and management issues. First-hand exposure to clinical personnel, patients, medical devices and instruments, and organizational workflow. Familiarity with provider protocols, physician referral practices, electronic records, clinical decision support systems, acute and chronic care, and inpatient and ambulatory care. Offered as EECS 480F and EBME 480F.

EECS 485: VLSI Systems (100/10926)
W 06:30-09:00 PM Aug 26-Dec 06
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 489: Robotics I (100/4754)
MW 03:20-04:35 PM Aug 26-Dec 06
Cavusoglu, C

Orientation and configuration coordinate transformations, forward and inverse kinematics and Newton-Euler and Lagrange-Euler dynamic analysis. Planning of manipulator trajectories. Force, position, and hybrid control of robot manipulators. Analytical techniques applied to select industrial robots. Recommended preparation: EMAE 181. Offered as EECS 489 and EMAE 489.

EECS 493: Software Engineering (100/4429)
MWF 11:40-12:30 PM Aug 26-Dec 06
Podgurski, H

Taught together with EECS 393

EECS 496: Artificial Intelligence: Sequential Decision Making (100/10978)
TR 02:30-03:45 PM Aug 26-Dec 06
Ray, S

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. Recommended preparation: EECS 491 (Probabilistic Graphical Models).

EECS 500: EECS Colloquium (100/4006)
TR 11:30-12:30 PM Aug 26-Dec 06
Lin, W; Podgurski, H

Seminars on current topics in Electrical Engineering and Computer Science.

EECS 500T: Graduate Teaching II (100/4007)
Mohseni, P

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

EECS 500T: Graduate Teaching II (101/4008)
Ray, S

CS STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 600: RFIC Design (100/10753)
TR 10:00-11:15 AM Aug 26-Dec 06
Miri Lavasani, S

Offered as EECS 600 and SYBB 600.

EECS 600: Deep Learning (101/10835)
T 07:00-09:30 PM Aug 26-Dec 06
Plassard, A

Offered as EECS 600 and SYBB 600.

EECS 600: Instrumentation Electronics (102/10957)
TR 02:30-03:45 PM Aug 26-Dec 06
Mandal, S

Offered as EECS 600 and SYBB 600.

EECS 600: Applied Circuit Design (103/10981)
TR 10:00-11:15 AM Aug 26-Dec 06
Sears, L

Offered as EECS 600 and SYBB 600.

EECS 600T: Graduate Teaching III (100/4009)
Mohseni, P

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

EECS 600T: Graduate Teaching III (101/4010)
Ray, S

CS STUDENTS SHOULD REGISTER FOR THIS SECTION.

EECS 601: Independent Study (101/11165)
Ray, S

EECS 601: Independent Study (102/11637)
Saab, D

EECS 601: Independent Study (103/11685)
Fu, M

EECS 601: Independent Study (104/11769)
Wang, A

EECS 601: Independent Study (105/11781)
Loparo, K

EECS 601: Independent Study (106/12012)
French, R

EECS 649: Project M.S. (102/4012)
Buchner, M

EECS 649: Project M.S. (116/4013)
Cavusoglu, C

EECS 649: Project M.S. (104/4014)
Chankong, V

EECS 649: Project M.S. (107/4204)
Koyuturk, M

EECS 649: Project M.S. (108/4205)
Li, J

EECS 649: Project M.S. (109/4206)
Liberatore, V

EECS 649: Project M.S. (110/4207)
Lin, W

EECS 649: Project M.S. (111/4208)
Loparo, K

EECS 649: Project M.S. (112/4209)
Malakooti, B

EECS 649: Project M.S. (114/4210)
Mehregany, M

EECS 649: Project M.S. (115/4211)
Merat, F

EECS 649: Project M.S. (117/4212)
Mohseni, P

EECS 649: Project M.S. (118/4213)
Newman, W

EECS 649: Project M.S. (121/4214)
Papachristou, C

EECS 649: Project M.S. (122/4215)
Podgurski, H

EECS 649: Project M.S. (123/4216)
Rabinovich, M

EECS 649: Project M.S. (124/4217)
Saab, D

EECS 649: Project M.S. (125/4218)
Sreenath, S

EECS 649: Project M.S. (130/4219)
Staff

EECS 649: Project M.S. (132/4220)
Zorman, C

EECS 649: Project M.S. (134/4511)
Staff

EECS 649: Project M.S. (135/4552)
Quinn, R

EECS 649: Project M.S. (136/4733)
Prica, M

EECS 649: Project M.S. (137/4827)
Li, P

EECS 651: Thesis M.S. (100/4015)
Li, P

(Credit as arranged.)

EECS 651: Thesis M.S. (102/4016)
Buchner, M

(Credit as arranged.)

EECS 651: Thesis M.S. (103/4017)
Cavusoglu, C

(Credit as arranged.)

EECS 651: Thesis M.S. (104/4018)
Chankong, V

(Credit as arranged.)

EECS 651: Thesis M.S. (107/4019)
Koyuturk, M

(Credit as arranged.)

EECS 651: Thesis M.S. (108/4020)
Li, J

(Credit as arranged.)

EECS 651: Thesis M.S. (109/4021)
Liberatore, V

(Credit as arranged.)

EECS 651: Thesis M.S. (110/4022)
Lin, W

(Credit as arranged.)

EECS 651: Thesis M.S. (111/4023)
Loparo, K

(Credit as arranged.)

EECS 651: Thesis M.S. (112/4024)
Malakooti, B

(Credit as arranged.)

EECS 651: Thesis M.S. (114/4025)
Mehregany, M

(Credit as arranged.)

EECS 651: Thesis M.S. (115/4026)
Merat, F

(Credit as arranged.)

EECS 651: Thesis M.S. (117/4027)
Mohseni, P

(Credit as arranged.)

EECS 651: Thesis M.S. (118/4028)
Newman, W

(Credit as arranged.)

EECS 651: Thesis M.S. (121/4029)
Papachristou, C

(Credit as arranged.)

EECS 651: Thesis M.S. (122/4030)
Podgurski, H

(Credit as arranged.)

EECS 651: Thesis M.S. (123/4031)
Rabinovich, M

(Credit as arranged.)

EECS 651: Thesis M.S. (124/4032)
Saab, D

(Credit as arranged.)

EECS 651: Thesis M.S. (125/4033)
Sreenath, S

(Credit as arranged.)

EECS 651: Thesis M.S. (132/4222)
Zorman, C

(Credit as arranged.)

EECS 651: Thesis M.S. (134/4355)
Ray, S

(Credit as arranged.)

EECS 651: Thesis M.S. (135/4397)
Garcia Sanz, M

(Credit as arranged.)

EECS 651: Thesis M.S. (136/4398)
Lewicki, M

(Credit as arranged.)

EECS 651: Thesis M.S. (137/4434)
Quinn, R

(Credit as arranged.)

EECS 651: Thesis M.S. (138/4502)
Griswold, M

(Credit as arranged.)

EECS 651: Thesis M.S. (141/4539)
Connamacher, H

(Credit as arranged.)

EECS 651: Thesis M.S. (142/4541)
Feng, P

(Credit as arranged.)

EECS 651: Thesis M.S. (143/4542)
Lee, G

(Credit as arranged.)

EECS 651: Thesis M.S. (144/4544)
Staff

(Credit as arranged.)

EECS 651: Thesis M.S. (145/4669)
Hong, M

(Credit as arranged.)

EECS 651: Thesis M.S. (146/4674)
Gurkan Cavusoglu, E

(Credit as arranged.)

EECS 651: Thesis M.S. (147/4726)
Huang, M

(Credit as arranged.)

EECS 651: Thesis M.S. (148/4731)
Mandal, S

(Credit as arranged.)

EECS 651: Thesis M.S. (149/4735)
Prica, M

(Credit as arranged.)

EECS 651: Thesis M.S. (150/4736)
Sahoo, S

(Credit as arranged.)

EECS 651: Thesis M.S. (151/4826)
Li, P

(Credit as arranged.)

EECS 651: Thesis M.S. (101/4860)
Xiao, X

(Credit as arranged.)

EECS 651: Thesis M.S. (152/4883)
Galan, R

(Credit as arranged.)

EECS 651: Thesis M.S. (106/4970)
Ayday, E

(Credit as arranged.)

EECS 651: Thesis M.S. (113/4975)
Fu, M

(Credit as arranged.)

EECS 651: Thesis M.S. (116/5036)
Wang, A

(Credit as arranged.)

EECS 651: Thesis M.S. (119/11092)
French, R

(Credit as arranged.)

EECS 651: Thesis M.S. (105/11618)
Ye, F

(Credit as arranged.)

EECS 651: Thesis M.S. (120/11619)
Wu, Y

(Credit as arranged.)

EECS 651: Thesis M.S. (126/11620)
Xu, S

(Credit as arranged.)

EECS 695: Project M.S. (100/4885)
Newman, W

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (102/5032)
Xiao, X

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (103/5039)
Prica, M

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (104/5065)
Liberatore, V

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (105/11622)
Ye, F

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (106/11623)
Wu, Y

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (107/11624)
Xu, S

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (108/11675)
Li, P

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (109/11676)
Loparo, K

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (110/11702)
Li, J

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (111/11747)
Zorman, C

Research course taken by Plan B M.S. students.

EECS 695: Project M.S. (112/11973)
Papachristou, C

Research course taken by Plan B M.S. students.

EECS 701: Dissertation Ph.D. (102/4034)
Buchner, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (103/4035)
Cavusoglu, C

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (104/4036)
Chankong, V

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (107/4037)
Koyuturk, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (108/4038)
Li, J

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (109/4039)
Liberatore, V

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (110/4040)
Lin, W

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (111/4041)
Loparo, K

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (112/4042)
Malakooti, B

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (113/4043)
Quinn, R

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (114/4044)
Mehregany, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (115/4045)
Merat, F

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (117/4046)
Mohseni, P

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (118/4047)
Newman, W

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (121/4048)
Papachristou, C

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (122/4049)
Podgurski, H

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (123/4050)
Rabinovich, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (124/4051)
Saab, D

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (125/4052)
Sreenath, S

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (130/4202)
Staff

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (132/4203)
Zorman, C

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (136/4356)
Ray, S

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (137/4399)
Garcia Sanz, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (138/4400)
Lewicki, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (139/4491)
Allman, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (140/4492)
Yu, X

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (142/4501)
Feng, P

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (144/4670)
Hong, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (145/4704)
Prica, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (146/4715)
Mandal, S

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (147/4720)
Griswold, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (148/4729)
Huang, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (149/4737)
Li, P

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (105/4863)
Abramson, A

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (106/4876)
Gurkan Cavusoglu, E

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (116/4976)
Fu, M

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (119/4997)
Ayday, E

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (120/5037)
Galan, R

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (126/11502)
Wang, A

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (127/11579)
Xiao, X

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (100/11625)
Ye, F

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (101/11627)
Wu, Y

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (128/11628)
Xu, S

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (129/11662)
Ye, F

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (131/11663)
Xu, S

(Credit as arranged.)

EECS 701: Dissertation Ph.D. (133/11664)
Wu, Y

(Credit as arranged.)