Course List and Descriptions

ECE 501 Introduction to MEMS Design 
ECE 502 Micro/Nano Fabrication Technologies
ECE 503 Modern Analog & Digital VLSI Design
ECE 504 Biological Microsystems and Microfluidics
ECE 505 Energy Conversion and Harvesting
ECE 506 Introduction to Solid State Physics
ECE 511 Lasers
ECE 512 Photonic Materials and Devices
ECE 513 Optics and Photonics
ECE 514 Ultrafast Optics
ECE 515 Nonlinear Optics
ECE 516 Applied Quantum and Statistical Physics
ECE 521 Radiation and Propagation of Electromagnetic Waves
ECE 522 RF Design, Microwave Engineering and Metamaterials
ECE 523 Antenna Engineering
ECE 524 Introduction to EMI/EMC
ECE 525 Advanced Topics in Electromagnetics
ECE 531 Digital Image Processing
ECE 532 Computer Vision
ECE 533 Remote Sensing Image Processing
ECE 535 Machine Learning
ECE 536 Pattern Recognition
ECE 537 Neural Networks
ECE 538 Data Mining
ECE 541 Approximation Algorithms
ECE 551 Introduction to Computational Biology
ECE 552 Advanced Topics in Computational Biology
ECE 561 Mobile and Wireless Computing
ECE 562 Cryptography and Network Security
ECE 563 Computer Networks
ECE 564 Networks and Systems
ECE 570 Probabilistic Models for Engineers
ECE 571 Coding Theory and Applications
ECE 572 Probability and Stochastic Processes for Engineering Applications
ECE 573 Wireless Communications
ECE 574 Information Theory
ECE 575 Signal Detection and Estimation
ECE 576 Advanced Digital Communications
ECE 578 Statistical Signal Processing
ECE 579 Optimization
ECE 590 Master's Thesis
ECE 591 Graduate Seminar

 

ECE 501 Introduction to MEMS Design: Physical phenomena behind general transduction principles will be covered. Specific topics will include electromagnetic induction, electromechanical energy conversion, piezoelectrics,piezoresistivity, thermoelectrics, photodetectors, and fluorescence at the micro and nano scale. At the end of this course students will be able to analyze and design sensors and actuators with electromagnetic, electrostatic, piezoelectric, thermal, and optical structures.

ECE 502 Micro/Nano Fabrication Technologies: This class will go over traditional and emerging techniques in micro and nano fabrication. The following subjects will be covered: photolithography, e-beam lithography, material deposition, thermal evaporation, sputtering, e-beam evaporation, PECVD, LPCVD, thermal oxidation, wet etching, ICP, reactive and deep reactive ion etching. Taking this course, students will be able to design and perform microfabrication sequences of a given micro/nano system.

ECE 503 Modern Analog & Digital VLSI Design: The design and analysis of VLSI will be covered. Specific topics include transistor circuit modeling, operational amplifiers, filters, analog to digital and digital to analog conversion, structured design, phase locked loops. At the end of this course, students will be able to analyze, design, and implement VLSI circuits.

ECE 504 Biological Microsystems and Microfluidics: The theory and fundamentals of microfluidics along with the fabrication techniques will be introduced. Subsequently, biological sensors and actuators, electrophoresis and magnetophoresis techniques and applications, flourescence imaging and cell counting devices, cell monitoring methods, and implantable sensors will be discussed. At the end of this course, students will have a comprehensive understanding of microfluidics design, biomedical micro/nano devices, and will have a solid background to perform research in BioMEMS field.

ECE 505 Energy Conversion and Harvesting: This class will equip students with the fundamentals of energy conversion and harvesting. The topics that will be covered in class include hydrocarbon fuels, fuel cells, batteries, thermoelectric generators, vibrational harvesters, human power, solar cells. Taking this course, students will be able to analyze, design, and optimize energy conversion devices aimed mostly for portable electronic systems.

ECE 511 Lasers: Review of electromagnetism; electromagnetic nature of light, radiation, geometrical optics, Gaussian beams, transformation of Gaussian beams; electromagnetic modes of an optical resonator, interaction of light with matter, classical theory of absorption and dispersion, broadening processes, Rayleigh scattering, quantum theory of spontaneous and stimulated emission, optical amplification, theory of laser oscillation, examples of laser systems, Q switching and mode locking of lasers.

ECE 512 Photonic Materials and Devices: Survey of the properties and applications of photonic materials and devices; semiconductors; photon detectors, light emitting diodes, noise in light detection systems; light propagation in anisotropic media, Pockels and Kerr effects, light modulators, electromagnetic wave propagation in dielectric waveguides, waveguide dispersion; nonlinear optical materials, second harmonic generation, Raman converters.

ECE 513 Optics and Photonics: Introduction to fundamental concepts and techniques of optics, photonics, and fiber optics. Review of Maxwell’s equations, light propagation, and reflection from dielectrics mirrors and filters. Interferometers, filters, and optical imaging systems. Fresnel and Fraunhoffer diffraction theory. Propagation of Gaussian beams and laser resonator design. Optical waveguides and optical fibers. Optical waveguide and photonic devices.

ECE 514 Ultrafast Optics: Introduction to ultrafast optics, principles of mode-locking, advanced topics in mode-locking, dispersion and dispersion compensation, ultrafast nonlinear optics, manipulation of ultrashort pulses, ultrafast time-resolved spectroscopy.

ECE 515 Nonlinear Optics: Techniques of nonlinear optics with emphasis on fundamentals for research and engineering in optics, photonics, and spectroscopy. Electro optic modulators, harmonic generation, and frequency conversion devices. Nonlinear effects in optical fibers including self-phase modulation, nonlinear wave propagation, and solitons. Interaction of light with matter, laser operation, density matrix techniques, nonlinear spectroscopies, and femtosecond optics.

ECE 516 Applied Quantum and Statistical Physics: Elementary quantum mechanics and statistical physics. Introduces applied quantum physics. Emphasizes experimental basis for quantum mechanics. Applies Schrodinger’s equation to the free particle, tunneling, the harmonic oscillator, and hydrogen atom. Variational methods. Elementary statistical physics; Fermi-Dirac, Bose- Einstein, and Boltzmann distribution functions. Simple models for metals, semiconductors, and devices such as electron microscopes, scanning tunneling microscope, thermonic emitters, atomic force microscope, and more.

ECE 521 Radiation and Propagation of Electromagnetic Waves: Mathematics of time varying electromagnetic fields, linear antennas self and mutual impedance, aperture antenna, wave diffraction theory, geometrical theory of diffraction. Spherical and cylindrical waves.

ECE 522 RF Design, Microwave Engineering and Metamaterials: Review of electromagnetic and transmission line theories. Microwave network analysis: impedance and admittance matrices, S matrix. ABCD matrix. Analysis of microstrip circuits. Microwave resonators. Power dividers and couplers. Microwave filters. RF amplifiers. RF oscillators. Electrodynamics of left handed media. Synthesis of bulk materials. Transmission line based metamaterials. Microwave filters and diplexers. Miniaturization of components by metamaterials. Metamaterials in antenna and sensing technologies.

ECE 523 Antenna Engineering: Concept of electromagnetic radiation. Antenna parameters. Radiation integrals and vector potentials. Wire antennas. Loop antennas. Array antennas. Horn antennas. Microstrip antennas. Reflector antennas.

ECE 524 Introduction to EMI/EMC: EMC Requirements for Electronic Systems, Relationship between the Time Domain and the Frequency Domain, Nonideal Behavior of Components, Conducted Emissions and Susceptibility, Radiated Emissions and Susceptibility, Crosstalk and Shielding.

ECE 531 Digital Image Processing: This course covers the basic theories and methodologies of digital image processing. The course

topics include image representation, image formation, image enhancement, intensity transformations, Fourier transform, image sampling, image restoration, morphological operations, image filtering, edge detection, image segmentation, and basics of digital video processing.

ECE 532 Computer Vision: This course will give an introduction to basic concepts in computer vision. Topics include linear filtering, image formation and segmentation, image transformations, camera models and calibration, object recognition, object classification and detection, objects in scenes.

ECE 533 Remote Sensing Image Processing: This course will cover basics of image analysis tailored for remote sensing applications. The course topics include theory of remote sensing imagery, image formation, image registration, image enhancement, morphological operations, supervised and unsupervised classification methods for remote sensing images, image segmentation, change detection, and analysis of big images.

ECE 535 Machine Learning: This course covers the theory and practical algorithms for machine learning. The topics include regression, decision trees, neural networks, mixture models and the EM algorithm, support vector machines, and combining trees with bagging or boosting.

ECE 536 Pattern Recognition: This course covers the theory of pattern recognition and presents common applications. Pattern recognition approaches to be covered in this course are Bayesian decision theory, parametric and nonparametric methods, decision trees, unsupervised learning and clustering, support vector machines, artificial neural networks, hidden Markov models, and reinforcement learning. Applications on biometrics and character recognition will be covered too.

ECE 537 Neural Networks: This will be an introductory course to neural networks. Topics to be covered are biological information processing and an overview of the most important networks such as perceptrons, backpropagation, Hopfield and Boltzmann networks, self-organizing maps, adaptive resonance theory, and reinforcement learning. Advantages of each neural network will be discussed or different applications will be studied through course projects.

ECE 538 Data Mining: This course covers the basics for knowledge extraction from large data sets. The course topics include data preparation, task identification, feature selection, association rule mining, classification, prediction, and clustering. Evaluation, validation and scalability will be discussed as well. In addition spatial and sequence mining will be covered together with some data mining applications.

ECE 551 Introduction to Computational Biology: This course will show how problems in molecular biology can be solved with computational techniques. The course first reviews the basic concepts in molecular biology for students with no prior biology background. Topics include sequence analysis, motif finding, RNA folding, genome assembly, comparative genomics, gene expression analysis, graph algorithms applied to networks.

ECE 552 Advanced Topics in Computational Biology: This course addresses a specific hot topic in the area of computational biology. Students are expected to read recent relevant papers in the chosen topic and work on a research project about this topic. Possible topics are post-transcriptional regulation, microbiome analysis, population genomics.

ECE 561 Mobile and Wireless Computing: This course is an introduction to the concepts of mobile and wireless systems. It first gives a background on networking concepts and then explains the wireless communications at all layers of networking protocol stack. These concepts include but not limited to different protocols for Wireless Networks and Wireless LAN, Mobile IP, Routing and MAC Protocols for Mobile Ad hoc and Sensor Networks. Due to time constraints the course will mainly focus on link and routing layers of mobile ad hoc and sensor networks.

ECE 562 Cryptography and Network Security: This course is designed to introduce a broad overview of the principles, mechanisms, and implementations of computer security. Topics include cryptography (symmetric and asymmetric cryptography), access control, software security and malicious code, trusted systems, network and wireless security, intrusion detection.

ECE 563 Computer Networks: Topics will be covered but not limited to Circuit Switching, Packet Switching, OSI and TCP/IP architectures. Application Layer (HTTP, SMTP, FTP, DNS etc), Transport Layer (TCP, UDP), Flow and Congestion Control (Sliding Window Protocols), Network Layer (IPv4, IPv6, IP Fragmentation, Link state and Distance vector routing algorithms, OSPF, RIP, BGP), Data Link Layer (Medium Access Protocols like Slotted ALOHA, TDMA, FDMA, CSMA/CD, error correction)

ECE 564 Networks and Systems: Everything is connected; people, places, event, information and devices. This course introduces the basic concepts of networks such as how social or technological world are connected, and how network analysis techniques can be used to explain and extract information from these connections. Some of the questions that will be answered in this course are: What are the most important nodes in a network? Is there a hidden community? How does the structure of the network affects the processes?

ECE 570 Probabilistic Models for Engineers: Review of basic probability concepts, probability axioms and random variables. Transform techniques. Law of large numbers, convergence of random variables, limit theorems in probability and Borel-Cantelli lemmas. The Bernoulli and Poisson processes. Markov chains, steady-state distributions, absorption probabilities and expected time to absorption. Bayesian statistical inference, point estimation, least mean square estimation and MAP rule.

ECE 571 Coding Theory and Applications: This course includes the following topics: Small signal constellations, performance analysis, coding gain, hard-decision decoding, soft-decision decoding. Binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, Viterbi algorithm. Trellis-based decoding, codes on graphs, the sum-product and min-sum algorithms, turbo codes, LDPC codes, RA codes, performance of LDPC codes with iterative decoding.

ECE 572 Probability and Stochastic Processes for Engineering Applications: This course includes the following topics: Gaussian random variables, law of large numbers, central limit theorems and estimation. Random processes, stationarity, ergodicity, correlation, covariance and power spectral densities. Response of linear systems to random signals. Markov chains, Poisson process and queuing processes.

ECE 573 Wireless Communications: This course includes the following topics: The cellular concept, physical modeling of wireless channels, input/output models of the wireless channel, time and frequency coherence, statistical wireless channel models. Point-to-point communication, detection, and time, antenna, frequency and space diversity. Multiple access and interference management for wireless systems, GSM, CDMA and OFDM. Fundamental limits of wireless channels.

ECE 574 Information Theory: This course includes the following topics: Entropy, relative entropy, mutual information and asymptotic equipartition property. Data compression, Karft inequality, optimal codes and Huffman codes. Channel capacity, differential entropy, AWGN channels, band-limited channels, parallel Gaussian channels, channels with colored Gaussian noise.

ECE 575 Signal Detection and Estimation: This course includes the following topics: Elements of hypothesis testing, likelihood function, sufficient statistics, Bayesian detection, minimax detection, Neyman-Pearson detection and performance bounds. Signal detection in discrete time, Chernoff bound, sequential detection and nonparametric detection. Parameter estimation, Bayesian parameter estimation, maximum likelihood estimation and Cramer-Rao bound.

ECE 576 Advanced Digital Communications: This course includes the following topics: Building blocks of digital communication systems, real

and complex vectors, baseband and passband random processes, signal space representation, MAP and ML detectors. Waveform channels, linear modulations over AWGN channels, discrete memoryless channels, error probability analysis, coherent and noncoherent detection for fading channels, code division multiple access (CDMA). Maximum likelihood sequence estimation, linear and nonlinear equalizations: zero-forcing, MMSE and decision feedback equalizes. Multicarrier transmission and receivers. Channel capacity, error exponent, channel coding theorems.

ECE 578 Statistical Signal Processing: This course includes the following topics: Review of probability theory, stochastic processes and linear vector spaces. Signal parameter estimation, linear MMSE estimators, maximum likelihood estimators and time-delay estimation. Wiener filters, dynamic adaptive filtering and Kalman filters. Particle filtering, spectral estimation and probability density estimation.

ECE 579 Optimization: This course includes the following topics: Review of linear algebra, convex sets and convex functions. Linear and convex optimization problems. Lagrange duality theory. Entropy maximization, water-filling algorithm and power control. Minimum mean-squared-error receivers, least-norm approximations, MAP and ML detectors. Network utility maximization, network flow problems, shortest path problems, scheduling and Internet congestion control.

ECE 590 Master’s Thesis: The student carries out research work under the guidance of his/her advisor, on a topic proposed by the advisor and approved by the Institute.

ECE 591 Graduate Seminar: Each student, before starting his/her thesis work, is assigned a topic by his/her thesis advisor in coordination with the coordinator of the seminar course. The student surveys the topic and presents it in the early stage of the thesis work.

Application Procedures

Tuition Fees and Payment

Financial Benefits