LUE 701 Scientific Research Techniques and Ethics
This course focuses on scientific research
methods and ethical principles. It covers research design, data collection and
analysis techniques, literature review, hypothesis development, and
presentation of research findings. Academic integrity, plagiarism, and the
importance of ethical conduct in research are also emphasized.
ECE 700 Seminar
Before starting thesis work, each student is
assigned a topic by the thesis advisor in coordination with the seminar course
coordinator. The student reviews the topic and presents it during the early
stage of the thesis work.
ECE 791 Master's Thesis 1
The student carries out research under the
guidance of the advisor on a topic proposed by the advisor and approved by the
Institute.
ECE 792 Master's Thesis 2
The student carries out research under the
guidance of the advisor on a topic proposed by the advisor and approved by the
Institute.
ECE 702 Micro/Nano Fabrication Technologies
This course covers the fundamental
microfabrication technologies used to manufacture micro- and nanoscale devices.
Topics include photolithography, thin-film deposition techniques such as
sputtering, thermal evaporation, LPCVD and PECVD, dry and wet etching,
isotropic and anisotropic etching, wafer bonding, packaging, and metrology.
ECE 709 Advanced Control Systems
This course covers the dynamics of SISO/MIMO
and linear/nonlinear systems, controllability and observability analysis,
stability definitions and stability-analysis methods, state-feedback control
design, nonlinear-system control, observer design, optimal state-feedback
control, optimal state observers, and intelligent control systems.
ECE 711 Advanced Power Electronics and Applications
The course examines selected areas of power
electronics in greater depth, introduces recent developments in the field, and
discusses applications in detail. Theoretical concepts are verified through
MATLAB/SIMULINK simulations.
ECE 712 Photonic Materials and Devices
The course surveys the properties and
applications of photonic materials and devices, including semiconductors,
photon detectors, light-emitting diodes, noise in light-detection systems,
light propagation in anisotropic media, Gaussian-beam propagation, laser-resonator
design, optical waveguides, optical fibers, and photodetectors.
ECE 715 Principles and Applications of Nanotechnology
The course develops an understanding of
size-dependent material, device, and system properties and how these properties
can be tailored through controlled manipulation of microstructure down to
atomic or molecular scales. It also covers nanoscale materials, their
applications and fabrication methods, with emphasis on advanced
characterization methods for evaluating material and device properties.
ECE 731 Digital Image Processing
This graduate-level introductory course
covers core image-processing concepts, including image sampling and
quantization, point operations, histograms, color science, segmentation,
morphological image processing, filtering and correlation, deconvolution,
template matching, image transforms, eigenimages, Fisherfaces, edge and
keypoint detection, scale-space processing, noise reduction and restoration,
feature extraction and recognition, and image registration. Practical examples
and MATLAB implementations are used throughout.
ECE 732 Biometrics
The course introduces biometric recognition
based on physical or behavioral attributes. It covers fingerprint, face, and
iris recognition, together with emerging modalities such as gait, hand
geometry, and ear recognition. Additional topics include biometric security,
performance evaluation, spoofing, ethical issues, links to forensic science,
and the impact of biometric recognition on the judicial system.
ECE 737 Advanced Database Systems
This course discusses concepts and techniques
for modeling and managing data using database management systems. Topics
include the relational data model, entity-relationship model, object-oriented
data model, SQL, query optimization, integrity constraints, normalization,
transaction management, concurrency control, and recovery systems.
ECE 747 Advanced Machine Learning
Course
content for this course was not provided in the source files.
ECE 748 Convolutional Neural Networks for Visual Recognition
This course examines deep-learning
architectures for visual-recognition tasks such as image classification,
localization, and detection. Students learn to implement, train, debug, and
fine-tune neural networks, understand learning algorithms such as backpropagation,
and explore current research in computer vision through hands-on assignments
and a final course project.
ECE 749 Advanced Data Science
This course provides an advanced introduction
to data science with emphasis on machine learning, artificial intelligence, and
big data. It uses a top-down approach to data-science projects and follows the
CRISP-DM methodology, including business understanding, data understanding,
data preprocessing, machine learning, ensemble techniques using KNIME and
Python on big-data platforms, and evaluation.
ECE 751 Introduction to Computational Biology
This course shows how problems in molecular
biology can be solved using computational techniques. It first reviews basic
molecular-biology concepts for students without a prior biology background.
Topics include sequence analysis, motif finding, RNA folding, genome assembly,
comparative genomics, gene-expression analysis, and graph algorithms applied to
biological networks.
ECE 752 Advanced Artificial Intelligence
The course begins with the history and
philosophy of artificial intelligence and covers classical AI approaches such
as search, machine learning, constraint satisfaction, graphical models, and
logic. It also includes modeling real-world problems using classical AI
methods, Python programming for AI algorithms, development of real-world
applications with AI modules, neural computing, uncertainty, Bayesian networks,
and supervised and unsupervised learning.
ECE 759 Cloud Computing
This course surveys the main concepts of
cloud computing. Topics include cloud and data-center file systems,
virtualization, security and privacy, MapReduce, Amazon Web Services, and
interactive web-based applications.
ECE 761 Advanced Computer Networks
This course introduces advanced
computer-network concepts with emphasis on Internet of Things networks,
information-centric networks and the Future Internet, software-defined
networks, medium-access protocols such as TDMA, FDMA, CSMA/CD and CSMA/CA, synchronization,
network topology and fault tolerance, deployment and energy optimization,
wireless localization methods such as AoA and TDOA, and smart-environment
applications including traffic modeling and analysis.
ECE 773 Wireless Communications
This course covers the cellular concept,
physical and statistical modeling of wireless channels, channel input/output
models, time and frequency coherence, point-to-point communication and
detection, time, antenna, frequency and spatial diversity, multiple access and
interference management for wireless systems, GSM, CDMA and OFDM, and
fundamental limits of wireless channels.
ECE 774 Advanced 5G and Beyond Technologies
This course introduces 5G and Beyond
requirements, applications, use cases, and enabling technologies. Topics
include flexible waveforms, 5G numerology, delay-Doppler-domain waveforms and
their differences from OFDM, advanced multidimensional modulation, spatial and
index modulation, secure waveform concepts, NOMA, massive MIMO, mmWave
communication, VLC systems, UAVs in 5G systems, machine and deep learning for
communication systems, interference alignment, cognitive radio, SDR, and OFDM
for unlicensed access.
ECE 776 Advanced Digital Communications
This course provides a comprehensive and
advanced view of digital communication systems, including transmitter and
receiver design and wireless-channel models. Topics include real and complex
random vectors, signal-space representations, advanced digital modulation and
demodulation techniques such as OFDM, OFDM-IM, OFDM-SNM, OFDM-SPM and MIMO-SM,
transmission over noisy and fading channels, ideal transceiver design,
bit-error probability, data rate, and throughput.
ECE 778 Wireless Security
This course introduces security requirements,
vulnerabilities, and attacks in wireless networks such as Wi-Fi, LTE/4G, and
5G. It covers security-defense protocols and paradigms, physical-layer security
against eavesdropping, wireless jamming attacks and countermeasures, and
selected open challenges and recommendations.
ECE 782 Web Mining
The course introduces data-mining methods for
discovering patterns and relationships that support decision making, with
particular emphasis on web data. Topics include decision trees, pattern
discovery, clustering, text mining and analytics, data visualization,
web-content mining, web-structure mining, and web-usage mining using data
extracted from web documents, hyperlinks, and server logs.
ECE 786 Graph Theory and Algorithms
This course introduces fundamental concepts
in graph theory, including basic definitions, common graph classes, and major
theorems. It also covers important graph-theory problems and related
algorithms, including shortest paths, weighted graphs, Dijkstra's algorithm,
Floyd's algorithm, spanning-tree algorithms, and search algorithms.
LUE 703 Engineering Mathematics
This course covers mathematics widely used in
core engineering subjects. It introduces linear algebra and ordinary
differential equations, including numerical approaches for solving systems of
equations. Topics include linear systems, existence and uniqueness of
solutions, Gaussian elimination, initial-value problems, first- and
second-order systems, forward and backward Euler methods, Runge-Kutta methods,
eigenvalues and eigenvectors, complex numbers, functions, vectors, and
matrices. MATLAB is used in the course.
DS 701 Introduction to Data Science
This introductory course to data science
focuses on machine learning, artificial intelligence, and big data. It covers
techniques and tools for collecting, storing, cleaning, manipulating,
visualizing, modeling, and extracting information from large datasets, together
with data preprocessing, an overview of machine-learning algorithms, and
evaluation strategies.
DS 702 Applied Statistics for Data Science
This course provides the statistical
background required for data-science applications. Topics include descriptive
statistics, probability distributions, correlation versus causation, hypothesis
testing, confidence intervals, and linear regression.
DS 703 Machine Learning
This course introduces fundamental principles
and techniques in machine learning, including supervised and unsupervised
learning, regression, regularization, nonparametric approaches, decision trees,
kernels and support-vector machines, clustering, neural networks, and an
introduction to deep learning. Applications to real-world datasets and methods
for evaluating and comparing algorithms are also covered.
DS 704 Exploratory Data Analysis and Visualization
This course covers major
exploratory-data-analysis methods and visualization tools. Topics include data
cleaning, selection of appropriate analysis methods, exploration of
relationships among variables, marks and channels, use of color, effective
visualization of multivariate data, networks and text, and hands-on work with
modern visualization systems.
DS 705 Deep Learning
This course covers the fundamentals of deep
learning, neural-network design, and application to specific problems. Topics
include artificial neural networks, convolutional neural networks, recurrent
neural networks, deep generative models, deep reinforcement learning, and
recent research and applications in audiovisual and language understanding.
DS 706 Machine Learning for Natural Language Processing
This course introduces machine-learning
approaches to natural language processing. Students learn how to transform text
into features for machine-learning methods and study n-gram language models,
part-of-speech tagging, vector-space models, locality-sensitive hashing,
attention models, Siamese networks, transformers, and other deep-learning
models used in NLP tasks.
DS 707 Fairness, Transparency and Privacy in Artificial Intelligence
Course
content for this course was not provided in the source files.
DS 708 Network Science
This course introduces network science as the
study of the topology and dynamics of complex networks. It focuses on
algorithmic, computational, and statistical methods and applications in areas
such as communications, biology, ecology, brain science, and sociology. Topics
include empirical network analysis, structure and function of complex networks,
epidemics, and models of information diffusion.
DS 709 Optimization
This course covers the foundations of
combinatorial optimization with emphasis on structure, algorithms, and proofs.
Topics include linear programming, the simplex method, duality, primal-dual
algorithms, network flows, matching, the traveling-salesman problem, cuts,
NP-hardness, and an introduction to approximation algorithms.
DS 711 Fundamental Algorithms
This course introduces the main concepts of
algorithm analysis and design. Topics include asymptotic approximation,
bounding sums, solving recurrences, divide-and-conquer, randomization, dynamic
programming, amortized analysis, greedy algorithms, and applications to
sequences, strings, graphs, and computational geometry.
DS 712 Business Analytics
This course introduces quantitative analysis
of business data using statistical models to support fact-based decision
making. Topics include descriptive analysis and visualization, customer
segmentation, customer lifecycle management, cross-sell and up-sell
recommendations, A/B testing in marketing, financial forecasting, link
analysis, social-media analysis, and business-process mining.
DS 713 Big Data Engineering
This course introduces design and
architecture techniques for building big-data applications. Topics include
distributed file systems, data streams, event streams, real-time data
processing, machine-learning pipelines, and automation of data flow.
MSCS 711 Computer Security
This multidisciplinary foundation course
provides an overview of computer-security fundamentals. Topics include risk
management, basic cryptography, user authentication including passwords and
biometrics, authentication protocols, operating-system security and access
control, software security, malware such as viruses, worms and Trojan horses,
and public-key certificates.
MSCS 712 Network Security
This course covers network fundamentals,
wireless LAN security, Cisco WLAN security measures, virtual private networks,
IPsec, network-security protocols such as HTTPS, SSL and TCP/IP, firewalls and
tunneling, intrusion detection and prevention systems, network-based attacks,
e-mail security, penetration testing, DDoS attacks, and other attack types.
MSCS 713 Cryptology
This course introduces the principles and
applications of modern cryptology, beginning with a brief review of classical
cryptographic techniques. Topics include symmetric block ciphers such as DES
and AES, stream ciphers, public-key cryptosystems, digital signatures,
authentication codes, cryptographic hash functions, key generation, and PKI
certificates.
MSCS 714 Data Privacy Seminar
This course introduces the foundations of
data privacy, current privacy issues and selected privacy laws,
privacy-by-design strategies, formal privacy definitions including k-anonymity,
l-diversity, t-closeness and m-invariance, differential privacy, and
homomorphic encryption. Students work in small groups to prepare a term paper
and presentation on an assigned or related topic.
MSCS 715 Coding Theory
This course introduces coding theory. Topics
include a review of probability theory, entropy, mutual information,
differential entropy, data compression, Huffman coding, the asymptotic
equipartition property, universal source coding, channel capacity, maximum-distance
codes, linear codes, generator and parity-check matrices, cyclic codes, block
codes, BCH codes, and Reed-Solomon codes.
MSCS 716 Ethical Hacking
The primary aim of this course is to help
students understand how vulnerable systems can be attacked as a means of
learning how to defend them more effectively. Topics include footprinting and
reconnaissance, network scanning and enumeration, system hacking, malware
threats, sniffing, social engineering, denial of service, session hijacking,
web-server and web-application attacks, SQL injection, wireless-network
attacks, and mobile-platform attacks.
