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 508 Thin Film Growth Techniques and Device Applications: It is aimed to investigate the growth techniques of the thin films and methods of determining the structural, optical and electrical properties of grown thin films. In this scope; the growth of the thin film by metal organic vapor phase epitaxy (MOVPE), molecular beam epitaxy (MBE), magnetron sputtering (MS) and atomic layer deposition (ALD) techniques and the determination methods of the crystal structure (xrd measurement), surface morphology (AFM imaging) and optical properties (PL measurement) of films will be examined. The investigation of growth techniques and the electrical properties of multi-layered thin films such as heterojunctions, quantum wells and determination of the electrical properties of two dimensional carriers in heterojunction and quantum well structures is among the targeted studies according to this course. In addition, it is planned to study the device applications of the heterostructures and quantum well in the LED and transistor devices within this course.

ECE 511 Lasers And Photonics: 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, propagation of Gaussian beams and laser resonator design, optical waveguides and optical fibers, photodetectors. 

ECE 513 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 522 Microprocessors: Introduction to microprocessors, including their basic architecture and operation. Bus organization, addressing modes, instruction set, analysis of clocks and timing, interrupt handling, serial and parallel communication, memory. Assembly language programming.

ECE 541 Artificial Intelligence: Knowledge representation. Search algorithms and heuristic programming. Logic and logic programming. Problem solving, games and puzzles, expert systems, vision, machine learning, natural language understanding and neural networks.

ECE 544 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 545 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 547 Advanced Machine Learning : Overview of basic machine learning methods. Graphical models. Deep Learning. Analysis of machine learning techniques that are applied on various real-life applications and their implementations.

ECE 561 Computer Networks: This course introduces the basic concepts of computer networks. 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 Cloud Computing: This course will survey main concepts of cloud computing. Topics include cloud and datacenter file systems, virtualization, security and privacy, MapReduce and Amazon Web services and interactive web-based applications.

ECE 572 Cryptography: This course spans the following topics: block ciphers (DES, AES, triple-DES), stream ciphers, cryptographic hash functions (MD5, SHA), public key encryption, digital signatures, key distribution protocols, key management, authentication systems, strong password protocols, Kerberos, Internet cryptography, IPsec, SSL/TLS, e-mail security, firewalls.

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 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 581 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 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.