Credit Exclusions: Credit is granted for only one course among EECS 183 or ENGR 101.

Fundamental concepts and skills of programming in a high-level language. Flow of control: selection, iteration, subprograms. Data structures: strings, arrays, records, lists, tables. Algorithms using selection and iteration (decision making, finding maxima/minima, searching, sorting, simulation, etc.) Good program design, structure and style are emphasized. Testing and debugging. Not intended for Engineering students (who should take ENGR 101), nor for CS majors in LSA who qualify to enter EECS 280.

Credit Exclusions: Credit is granted for only one course among EECS 183 or ENGR 101.

Fundamental concepts and skills of programming in a high-level language. Flow of control: selection, iteration, subprograms. Data structures: strings, arrays, records, lists, tables. Algorithms using selection and iteration (decision making, finding maxima/minima, searching, sorting, simulation, etc.) Good program design, structure and style are emphasized. Testing and debugging. Not intended for Engineering students (who should take ENGR 101), nor for CS majors in LSA who qualify to enter EECS 280.

Introduction to the mathematical foundations of computer science. Topics covered include: propositional and predicate logic, set theory, function and relations, growth of functions and asymptotic notation, introduction to algorithms, elementary combinatorics and graph theory, and discrete probability theory.

Enforced Prerequisites: MATH 115 or 116 or 119 or 120 or 121 or 156 or 176 or 185 or 186 or 295 or 296 or 215 or 255 or 285 with a grade of at least C or better

Introduction to the mathematical foundations of computer science. Topics covered include: propositional and predicate logic, set theory, function and relations, growth of functions and asymptotic notation, introduction to algorithms, elementary combinatorics and graph theory, and discrete probability theory.

Enforced Prerequisites: MATH 115 or 116 or 119 or 120 or 121 or 156 or 176 or 185 or 186 or 295 or 296 or 215 or 255 or 285 with a grade of at least C or better

Introduction to the mathematical foundations of computer science. Topics covered include: propositional and predicate logic, set theory, function and relations, growth of functions and asymptotic notation, introduction to algorithms, elementary combinatorics and graph theory, and discrete probability theory.

Enforced Prerequisites: MATH 115 or 116 or 119 or 120 or 121 or 156 or 176 or 185 or 186 or 295 or 296 or 215 or 255 or 285 with a grade of at least C or better

Introduction to Logic Design Binary and non-binary systems, Boolean algebra digital design techniques, logic gates, logic minimization, standard combinational circuits, sequential circuits, flip-flops, synthesis of synchronous sequential circuits, PLA's, ROM's, RAM's, arithmetic circuits, computer-aided design. Laboratory includes hardware design and CAD experiments.

Enforced Prerequisites: ENGR 101 or EECS with a grade of at least C

Introduction to Logic Design Binary and non-binary systems, Boolean algebra digital design techniques, logic gates, logic minimization, standard combinational circuits, sequential circuits, flip-flops, synthesis of synchronous sequential circuits, PLA's, ROM's, RAM's, arithmetic circuits, computer-aided design. Laboratory includes hardware design and CAD experiments.

Enforced Prerequisites: ENGR 101 or EECS with a grade of at least C

Credit Exclusions: No credit granted to those who have completed or are enrolled in EECS 283.

Techniques and algorithm development and effective programming, top-down analysis, structured programming, testing, and program correctness. Program language syntax and static and runtime semantics. Scope, procedure instantiation, recursion, abstract data types, and parameter passing methods. Structured data types, pointers, linked data structures, stacks, queues, arrays, records, and trees.

Advisory Prerequisite: MATH 115

Credit Exclusions: No credit granted to those who have completed or are enrolled in EECS 283.

Techniques and algorithm development and effective programming, top-down analysis, structured programming, testing, and program correctness. Program language syntax and static and runtime semantics. Scope, procedure instantiation, recursion, abstract data types, and parameter passing methods. Structured data types, pointers, linked data structures, stacks, queues, arrays, records, and trees.

Advisory Prerequisite: MATH 115

Introduction to algorithm analysis and O-notation; Fundamental data structures including lists, stacks, queues, priority queues, hash tables, binary trees, search trees, balanced trees and graphs; searching and sorting algorithms; recursive algorithms; basic graph algorithms; introduction to greedy algorithms and divide and conquer strategy. Several programming assignments.

Enforced Prerequisites: EECS 280 and 203 with a grade of at least C

Basic concepts of computer organization and hardware. Instructions executed by a processor and how to use these instructions in simple assembly-language programs. Stored-program concept. Datapath and control for multiple implementations of a processor. Performance evaluation, pipelining, caches, virtual memory, input/output.

Enforced Prerequisites: EECS 203 or 270 with a grade of at least C; and EECS 280 or 283 with a grade of at least C

Basic concepts of computer organization and hardware. Instructions executed by a processor and how to use these instructions in simple assembly-language programs. Stored-program concept. Datapath and control for multiple implementations of a processor. Performance evaluation, pipelining, caches, virtual memory, input/output.

Enforced Prerequisites: EECS 203 or 270 with a grade of at least C; and EECS 280 or 283 with a grade of at least C

Principles of hardware and software microcomputer interfacing; digital logic design and implementation. Experiments with specially designed laboratory facilities. Introduction to digital development equipment and logic analyzers. Assembly language programming. Lecture and laboratory.

Enforced Prerequisites: EECS 270 and 370 with a grade of at least C

An introduction to computation theory: finite automata, regular languages, pushdown automata, context-free languages, Turing machines, recursive languages and functions, and computational complexity.

Enforced Prerequisites: EECS 280 and 203 with a grade of at least C

Programming techniques in Standard C++ for large-scale, complex, or high-performance software. Encapsulation, automatic memory management, exceptions, generic programming with templates and function objects, Standard Library algorithms and containers. Using single and multiple inheritance and polymorphism for code reuse and extensibility; basic design idioms, patterns, and notation.

Enforced Prerequisites: EECS 281 with a grade of at least C

Topics of current interest selected by the faculty. Lecture, seminar, or laboratory.

Advisory Prerequisite: PER. INSTR.

Design techniques for rapid implementations of very large-scale integrated (VLSI) circuits, MOS technology and logic. Structured design. Design rules, layout procedures. Design aids: layout, design rule checking, logic, and circuit simulation. Timing. Testability. Architectures for VLSI. Projects to develop and lay out circuits.

Enforced Prerequisites: EECS 270 and 312 with a grade of at least C; or graduate standing

Basic concepts of computer architecture and organization. Computer evolution. Design methodology. Performance evaluation. Elementary queueing models. CPU architecture. Introduction sets. ALU design. Hardware and microprogrammed control. Nanoprogramming. Memory hierarchies. Virtual memory. Cache design. Input-output architectures. Interrupts and DMA. I/O processors. Parallel processing. Pipelined processors. Multiprocessors.

Enforced Prerequisites: EECS 270 and 370 with a grade of at least C; or graduate standing

Advisory Prerequisite: EECS 370, EECS 270 or Graduate Standing

Fundamental techniques for designing effi cient algorithms and basic mathematical methods for analyzing their performance. Paradigms for algorithm design: divide-and-conquer, greedy methods, graph search techniques, dynamic programming. Design of efficient data structures and analysis of the running time and space requirements of algorithms in the worst and average cases.

Enforced Prerequisites: EECS 281 with a grade of at least C; or graduate standing

Advisory Prerequisite: EECS 281 or EECS 398, Winter 2005, Section 001 or Graduate Standing

Advanced design of logic circuits. Technology constraints. Theoretical foundations. Computer-aided design algorithms. Two-level and multilevel optimization of combinational circuits. Optimization of finite-state machines. High-level synthesis techniques: modeling, scheduling, and binding. Verification and testing.

Enforced Prerequisites: EECS 270 and 203 with a grade of at least C; and senior or graduate standing

Advisory Prerequisite: EECS 203 and 270 and senior or graduate standing.

Pragmatic aspects of the production of software systems, dealing with structuring principles, design methodologies and informal analysis. Emphasis is given to development of large, complex software systems. A term project is usually required.

Enforced Prerequisites: EECS 281 with a grade of at least C; or graduate standing

Advisory Prerequisite: EECS 281 or EECS 398, Winter 2005, Section 001 or Graduate Standing

Operating system design and implementation: multi-tasking; concurrency and synchronization; inter-process communication; deadlock; scheduling; resource allocation; memory and storage management; input-output; file systems; protection and security. Students write several substantial programs dealing with concurrency and synchronization in a multi-task environment, with file systems, and with memory management.

Enforced Prerequisites: EECS 281 with a grade of at least C; or graduate standing

Advisory Prerequisite: (EECS 370 and EECS 281 or EECS 398, Winter 2005, Sec 001) or Graduate Standing

Concepts and methods for the design, creation, query and management of large enterprise databases. Functions and characteristics of the leading database management systems. Query languages such as SQL, forms, embedded SQL, and application development tools. Database design, integrity, normalization, access methods, query optimization, transaction management and concurrency control and recovery.

Enforced Prerequisites: EECS 281 with a grade of at least C; or graduate standing

Advisory Prerequisite: EECS 281 or EECS 398, Winter 2005, Section 001 or Graduate Standing

Design and use of databases in the Web context; data models, database design, replication issues, client/server systems, information retrieval, web server design; substantial project involving the development of a databasebacked web site.

Enforced Prerequisites: EECS 484 with a grade of at least C, or graduate standing

Computer graphics hardware, line drawing, rasterization, anti-aliasing, graphical user interface (GUI), affine geometry, projective geometry, geometric transformation, polygons, curves, splines, solid models, lighting and shading, image rendering, ray tracing, radiosity, hidden surface removal, texture mapping, animation, virtual reality, and scientific visualization.

Enforced Prerequisites: EECS 281 with a grade of at least C; or graduate standing

Advisory Prerequisite: EECS 281 or Graduate Standing

Protocols and architectures of computer networks. Topics include client-server computing, socket programming, naming and addressing, media access protocols, routing and transport protocols, flow and congestion control, and other application-specific protocols. Emphasis is placed on understanding protocol design principles. Programming problems to explore design choices and actual implementation issues assigned.

Enforced Prerequisites: EECS 482 with a grade of at least C; or graduate standing

Fundamental concepts of AI, organized around the task of building computational agents. Core topics include search, logic, representation and reasoning, automated planning, decision making under uncertainty, and machine learning.

Enforced Prerequisites: EECS 281 with a grade of at least C, or graduate standing

Advisory Prerequisite: EECS 281 or EECS 398, Winter 2005, Section 001 or Graduate Standing

Concepts and techniques for designing computer system user interfaces to be easy to learn and use, with an introduction to their implementation. Task analysis, design of functionality, display and interaction design, and usability evaluation. Interface programming using an object-oriented application framework. Fluency in a standard object-oriented programming language is assumed.

Enforced Prerequisites: EECS 281 or CMPTRSC 281 or EECS 380 or CMPTRSC 380 with a grade of at least C; or graduate standing

Advisory Prerequisite: EECS 281 or EECS 398, Winter 2005, Section 001 or Graduate Standing

Design principles for multidisciplinary team projects, team strategies, entrepreneurial skills, ethics, social and environmental awareness, and life long learning. Each student must take (simultaneously) TCHNCLCM 496 (2 cr.) and one of the approved 400-level team project courses in computing (4 cr.).

Enforced Prerequisites: Senior or Above

Professional problem-solving methods developed through intensive group studies. Normally one significant design project is chosen for entire class requiring multiple EECS disciplines and teams. Use of analytic, computer, design, and experimental techniques where applicable are used. Projects are often interdisciplinary allowing non-EECS seniors to also take the course (consult with instructor).

Enforced Prerequisites: Senior or Above

Advisory Prerequisite: Successful completion of at least two-thirds of the credit hours required for the program subjects and Sr. Standing.

Topics of current interest selected by the faculty. Lecture, seminar or laboratory.

Advisory Prerequisite: Permission of instructor.

Course Texts:Will be provided Course Format:Two 90-min lectures per week Course Grading:Two individual assignments: 30% Term group paper: 30% Final group presentation: 30% Class attendance and participation: 10% Final Examination: Term group paper and final presentation.

Homework's:Two device analysis assignments Goals:This course is intended for senior undergraduate and graduate students interested in the basic interdisciplinary science of the organic semiconductors and their application to different device structures. The fundamental science and technology to be addressed in this class are inherently interdisciplinary; they fall at the intersection of three disciplines: chemistry, physics and engineering. The fundamental optical, opto-electrical and electronic, and carrier transport properties of the organic macromolecules used in practical organic and molecular devices will be discussed. Comprehensive analysis of the operating principles of thin-film organic semiconductor devices such as light-emitting and photovoltaic devices, thin-film transistors, optical, chemical and biological sensors, and molecular rectifiers will be addressed in details during this class. Finally storage and electrical stability of the devices and their possible applications to future printed plastic electronics will be discussed.

Advisory Prerequisite: Permission of instructor.

It is inevitable that all computing will be mobile. Jeff Hawkins, Inventor of the Palm Pilot, 1991The Wii's controller is the new mouse. Somebody said that. In this seminar we will explore the emerging space of mobile computing efforts, from cellphones to portable gaming consoles, from PDA's to smart appliances. We will analyze existing systems in order to develop a framework for the design of new systems. In 498, then, we will form teams of three, to design and prototype mobile computing systems. Projects will be developed by the student teams or projects will be provided by the instructor. Following the discipline developed in 481 and 497, teams will develop SRS and SDS documents. Class presentations will also be made.

Advisory Prerequisite: Permission of instructor.

Individual study of selected topics in Electrical Engineering and Computer Science. May include experimental investigation or library research. Primarily for undergraduates.

Enforced Prerequisites: Senior or Above

Advisory Prerequisite: Senior standing in EECS.

Theory of circuit partitioning, floor planning and placement algorithms. Techniques for routing and clock tree design. Timing analysis and cycles time optimization. Topics in low-power design. Large-scale optimization heuristics, simulated annealing and Al techniques in CAD. Modern physical design methodologies and CAD software development.

Advisory Prerequisite: EECS 281 or EECS 478 or Graduate Standing.

Theory of circuit partitioning, floor planning and placement algorithms. Techniques for routing and clock tree design. Timing analysis and cycles time optimization. Topics in low-power design. Large-scale optimization heuristics, simulated annealing and Al techniques in CAD. Modern physical design methodologies and CAD software development.

Advisory Prerequisite: EECS 281 or EECS 478 or Graduate Standing.

Continuation of nonrelativistic quantum mechanics. Advanced angular momentum theory, second quantization, non-relativistic quantum electrodynamics, advanced scattering theory, density matrix formalism, reservoir theory.

Advisory Prerequisite: APPPHYS 540.

The Internet is rapidly changing the way we trade with one another, conduct businesses, and organize financial institutions. This course covers a range of important principles — drawn from computer science, economics, and other disciplines — that influence the design and analysis of Internet commerce systems. The goal is to develop a mastery of the fundamental concepts and approaches through examples, rather than an exhaustive survey of the field. The course is loosely organized as two half-semester modules — "Foundations of E-commerce" and "Online Auctions and Pricing."

The general outline of material breaks trading into three topics — locating buyers and sellers (search), setting terms of trade (negotiation), and verifying and consummating the deal (exchange). The first half-semester will cover search and exchange systems and introduce students to design and analysis methods to make online commerce robust against failures, malicious attackers, and strategic manipulation. The second half-semester will cover negotiation through an in-depth study of online auctions, exchanges, and pricing schemes. Students study the theory and practice of incentive engineering for business or social goals in this rapidly growing area.

Advisory Prerequisite: SI 502 or taken concurrently or Instructor permission

Principles of fiber optical communications and networks. Point-to-point systems and shared medium networks. Fiber propagation including attenuation, dispersion and nonlinearities. Topics covered include erbium-doped amplifiers, Bragg and ong period gratings, fiber transmission based on solitons and non-return-to-zero, and time- and wavelength-division-multiplexed networks.

Advisory Prerequisite: EECS 434 or 538. Permission of instructor.

Graduate-level introduction to the foundations of high performance microprocessor implementation. Problems involving instruction supply, data supply, and instruction processing. Compile-time vs. run-time tradeoffs. Aggressive branch prediction. Wide-issue processors, in-order vs. out-of-order execution, instruction retirement. Case studies taken from current microprocessors.

Advisory Prerequisite: EECS 470, or permission of instructor.

A rigorous introduction to the design of cryptosystems and to cryptanalysis. Topics include cryptanalysis of classical cryptosystems; theoretical analysis of one-way functions; DES and differential cryptanalysis; the RSA cryptosystem; ElGamal, elliptic, hyperelliptic and hidden mononomial cryptosystems; attacks on signature schemes, identifi cation schemes and authentication codes; secret sharing; and zero knowledge.

Advisory Prerequisite: ECCS 203 or equivalent. EECS 574 recommended

Geometric modeling: spline curves and surfaces, subdivision surfaces, polygonal meshes, point-based and implicit surfaces. Real-time rendering: fixed and programmable pipeline, shadows. Acceleration algorithms: culling and level-of-detail. Collision detection. Delaunay triangulations and Voronoi diagrams. Non-photorealistic rendering. Pattern synthesis. Image-based rendering.

Advisory Prerequisite: EECS 487 (or equivalence) or Graduate standing

Course discusses advanced topics and research issues in operating systems. Topics will be drawn from a variety of operating systems areas such as distributed systems and languages, networking, security, and protection, realtime systems, modeling and analysis, etc.

Advisory Prerequisite: EECS 482/EQ.

Design of algorithms for nonnumeric problems involving sorting, searching, scheduling, graph theory, and geometry. Design techniques such as approximation, branch-and-bound, divide-and-conquer, dynamic programming, greed, and randomization applied to polynomial and NP-hard problems. Analysis of time and space utilization.

Advisory Prerequisite: EECS 281

This is a 4-credit course that covers basic and advanced topics in programming languages, and shows how good programming languages can significantly improve the reliability of software systems. This course has three objectives: 1) To understand fundamental concepts in programming languages, 2) To study some recent topics andtrends in PL research, and 3) To gain experience planning and carrying out a semester long individual PL research project. This course counts as a software kernel course and towards software area qualification for CSE graduate students. This course also counts as an upper-level CS technical elective for CS-ENGR and CS-LSA undergraduate students. Please see the course web page for further information.

Advisory Prerequisite: EECS 281 or equivalent

Principles and practice of distributed system design. Computations, consistency semantics, and failure models. Programming paradigms including group communication, RPC, distributed shared memory, and distributed objects. Operating system kernel support; distributed system services including replication, caching, file system management, naming, clock synchronization, and multicast communication. Case studies.

Advisory Prerequisite: EECS 482 and graduate standing.

Prerequisites: Either familiarity with programming (no particular language required), or a course in finite mathematics. All technical topics will be defined in class.

Course Organization: This is a highly interactive class with students from all over campus. You will be expected to contribute to the class discussion and will be graded accordingly. There will be a final paper which you will present to the class.

Topics: Much of our investigation will center on complex adaptive systems (cas). A cas consists of adaptive (learning) agents with conditional interactions. Typical examples are the central nervous system, a market, the immune system, and the internet. Because of evolution and adaptation, cas exhibit perpetual novelty in their structure and behavior.

"Complexity" and "emergence" are difficult topics with different meanings in different areas. Rather than trying to provide precise definitions of these terms, we will develop a range of ideas, examples, and intuitions that provide a deeper understanding.

The order of topics will depend partly upon particular interests of the class, but the following topics, at least, will be covered

1. Performance systems [sets of condition/action rules].
2. Signal-passing systems — their pervasiveness from cell biology to language.
3. Parallelism — systems with many rules active simultaneously.
4. Agent-based models (models with multiple interacting agents).
5. Credit assignment — strengthening stage-setting and predictive rules.
6. Rule discovery — genetic algorithms.
7. Building blocks — their role in everything from perception to invention.

Advisory Prerequisite: EECS 203 and Math./Stat. 425.

This is a one-time seminar course focusing on some of the problems I have been interested in over time. We look at mathematical models of language, natural and computer, and think about complexity and conciseness. We also look at logics, broadly construed, and some issues in concurrency and control.

Advisory Prerequisite: Permission of instructor or counselor.

Topics of current interest in electrical engineering and computer science. Lectures, seminar, or laboratory. Can be taken more than once for credit.

Advisory Prerequisite: Permission of instructor or counselor.

Topics of current interest in electrical engineering and computer science. Lectures, seminar, or laboratory. Can be taken more than once for credit.

Advisory Prerequisite: Permission of instructor or counselor.

Do you know that we can reduce 25% of the electricity consumption and 10% of the total energy need by replacing the old-fashioned light bulbs with highly efficient solid-state devices? Do you know solar cells with efficiency as high as 87% can be achieved if we properly engineer the compound semiconductor materials? Come and join us in discovering new applications of compound semiconductor materials in the saving and generation of energy. In this course, we will discuss the science and technology behind these increasingly important research fields. We will give an in-depth overview of the physics, materials engineering, device structures, fabrication, and circuit integration. We will put special emphasis on the design and optimization of the technology. We will focus primarily on solid-state lighting and solar cells technologies using compound semiconductor materials such as GaN, InGaP, GaAs and etc. We will mention very little on the organic materials but students who are interested in organic devices will probably still find part of this course interesting. Students who have taken EECS 529 are welcome to enroll in this class too as the overlap will be minimal. This will be the first dedicated entry-level graduate course focusing on optoelectronic technologies in energy applications. Motivated undergraduate students are highly encouraged to join us too. This course will be targeted for senior undergraduate students and graduate students. We will review relevant basics at the beginning of the class but prior background in the level of EECS 429 or equivalent is highly recommended.Please feel free to contact me if you have any question or comment.For EECS/SSEL graduate students: This course can be claimed to fulfill the Solid State Kernel requirement under both Solid State Technology/Circuits and Solid State Devices categories.Textbooks:Primary — 1.E. F. Schubert, Light-Emitting Diodes, 2nd edition, Cambridge (2006)2.M. A. Green, Third Generation Photovoltaics: Advanced Solar Conversions, Springer (2006)Reference — 1.S. Nakamura et al., The Blue Laser Diode, 2nd edition, Springer (2000)

Advisory Prerequisite: Permission of instructor or counselor.

Topics of current interest in electrical engineering and computer science. Lectures, seminar, or laboratory. Can be taken more than once for credit.

Advisory Prerequisite: Permission of instructor or counselor.

Course Texts:Will be provided Course Format:Two 90-min lectures per week Course Grading:Two individual assignments: 30% Term group paper: 30% Final group presentation: 30% Class attendance and participation: 10% Final Examination: Term group paper and final presentation.

Homework's:Two device analysis assignments Goals:This course is intended for senior undergraduate and graduate students interested in the basic interdisciplinary science of the organic semiconductors and their application to different device structures. The fundamental science and technology to be addressed in this class are inherently interdisciplinary; they fall at the intersection of three disciplines: chemistry, physics and engineering. The fundamental optical, opto-electrical and electronic, and carrier transport properties of the organic macromolecules used in practical organic and molecular devices will be discussed. Comprehensive analysis of the operating principles of thin-film organic semiconductor devices such as light-emitting and photovoltaic devices, thin-film transistors, optical, chemical and biological sensors, and molecular rectifiers will be addressed in details during this class. Finally storage and electrical stability of the devices and their possible applications to future printed plastic electronics will be discussed.

Advisory Prerequisite: Permission of instructor or counselor.

Advanced very large scale integrated (VLSI) circuit design. Design methodologies (architectural simulation, hardware description language design entry, silicon compilation, and verification), microarchitectures, interconnect, packaging, noise sources, circuit techniques, design for testability, design rules, VLSI technologies, and yield. Projects in chip design.

Advisory Prerequisite: EECS 427 advised.

Formalism of wave propagation in nonlinear media; susceptibility tensor; second harmonic generation and three-wave mixing; phase matching; third order nonlinearities and four-wave mixing processes; stimulated Raman and Brillouin scattering. Special topics: nonlinear optics in fibers, including solitons and self-phase modulation.

Advisory Prerequisite: EECS 537 or 538 or 530. Graduate standing.

This course is an advanced course in the interaction of radiation with matter. Students are assumed to have a good background in quantum mechanics and electrodynamics.

Course requirements. There will weekly homework assignments that will be collected and graded. There will also be a short research paper required. Your grade will be based 80% on homework and 20% on the research paper.

Course Outline: The course is divided into four parts as follows:

1. Interaction of classical fields with atoms
   • Two-level problem
   • Density matrix
   • Bloch vector
   • Absorption, free-induction decay, photon echoes
   • A.C. Stark effect
2. Properties of the electromagnetic field
   • Classical fields with and without noise
   • Quantization of the field
   • Correlation functions
   • Fock states, coherent states
   • Photon statistics, bunching and anti-bunching
   • Squeezed states
3. Interaction of quantized fields with atoms
   • Spontaneous emission
   • "Dressed" atoms
   • Resonance fluorescence in strong fields
4. Selected topics (as time permits)
   • Quantum computing
   • Laser cooling of neutral atoms
   • Atom interferometers

Advisory Prerequisite: PHYSICS,Quantum mechanics, electrodynamic and atomic physics.

This is a conceptually (as opposed to computationally) oriented course that focuses on the learning process. Unlike many psychological processes, understanding learning is difficult without some familiarity with the behind-the-scenes activities of neurons that make learning possible. The purpose of this course is to explore a set of possible mechanisms that underlie the interaction of mind and environment in the integration, storage and efficient retrieval of adaptively useful information.

Advisory Prerequisite: Graduate standing and permission of instructor.

Dissertation work by doctoral student not yet admitted to status as candidate. The defense of the dissertation, that is, the final oral examination, must be held under a full-term candidacy enrollment.

Advisory Prerequisite: Election for dissertation work by doctoral student not yet admitted as a Candidate.

Election for dissertation work by a doctoral student who has been admitted to candidate status. The defense of the dissertation, that is, the final oral examination, must be held under a full-term candidacy enrollment.

Enforced Prerequisites: Graduate School authorization for admission as a doctoral Candidate