Qualifying Examination
The qualifying examination is designed to assess a PhD student’s readiness to undertake dissertation research in electrical and computer engineering.
This page is designed to provide specific information about the qualifying exam for current ECE doctoral students. If you have any questions about the exam that are not answered by the content on this page, please contact your faculty advisor or the student affairs office.
About the Qualifying Examination
PhD students must pass two topic areas on the qualifying examination to complete this requirement. (See the accordions below for information on each topic area.) Students have two hours to complete each area of the exam, which are based on material from upperlevel undergraduate and beginning graduate coursework. The areaspecific questions on the exam are based on a publicly announced list of required topics and suggested reading materials, rather than on specific ECE courses.
You can find PDF samples of qualifying exams from past years here: 2018, 2019, 2020.
Requirements and Registration for the Qualifying Exam
The registration form for the qualifying examination is available for download.
Students seeking to take the qualifying examination must have fullstanding status with the UIC Graduate College in the ECE master’s or doctoral program. They must be registered for coursework during the semester in which the exam is taken.
Students who are pursuing a PhD fulltime must make their first attempt at the qualifying examination in the first April after their initial semester of enrollment.
Students who are pursuing a PhD parttime are required to take the qualifying exam in the semester following registration for a total of 24 PhD semester credit hours, including independentstudy courses and ECE 599. In other words, they will take the exam after completing the equivalent of two semesters of fulltime coursework.
Master’s students in ECE may petition to take the qualifying examination if they have completed at least one calendar year of residence and have a GPA of 3.5 or higher.
Students must register for the examination in Room 1020 SEO by the registration deadline, which is communicated in each semester by the student affairs office.
When students register for the exam, they must specify the areas in which they plan to take the exam.
First and Second Attempts
Students may sit for the qualifying exam a maximum of two times. Second attempts must be made at the time of the next consecutive offering of the examination. Students who pass any area of the examination during the first attempt are not required to retake that area in the subsequent examination.
Students may elect to take one or two area examinations during the first attempt. Students who require a second attempt are not allowed to register for extra areas beyond the number required. (In other words, students who pass one area and fail one area on the first attempt may only take one area on the second attempt.)
Students who fail to pass two areas after their second attempt at the qualifying exam will be expelled from the graduate program. Fulltime PhD students who fail to appear for the exam in the first April after their initial semester of enrollment will be expelled from the program.
Examination Procedure and Rules
Each student is assigned a code number for the qualifying examination. Students must not write their names or social security numbers anywhere on the examination papers, answer books, or other papers used in the examination. The code number is the only form of identification that should appear on any testing materials.
Students must remain in the examination room during the 15minute intervals between examination periods. Before the start of the examination, students must leave their notes and other reading material in a place in the examination room designated by the proctor. Students will not have access to this material during breaks. Any student who leaves the examination room unescorted will not be allowed to return and complete the remainder of the examination.
Qualifying examinations are closedbook. Students may bring a scientific calculator, but no programmable calculators are allowed. Cell phone use in the examination room is not allowed.
Students are required to return their examination papers, answer books, and scratch paper at the end of each examination period.
Appeals related to the grading or results of the exam should be made by the student’s advisor to the director of graduate studies. The director of graduate studies will present the appeal to the Graduate Committee for reconsideration and possible reevaluation.
Qualifying Examination Topic Areas

Algorithms and data structures
Major topics:
Algorithms analysis techniques: Correctness and complexity, proving techniques, NPcompleteness.
Algorithm design approaches: Recursion, divideandconquer, dynamic programming, greedy methods, and solution searching methods.
Applied algorithms: Sorting, searching, graph computations, and string matching.
Complex data structures: Lists, stacks, queues, sets, hash tables, trees, heaps, and graphs.
Courses helpful in this exam area:
 CS 401: Computer Algorithms I
 ECE 566: Parallel Processing
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as CS 201 and CS 202.
Typical references:
H. Cormen, C. E. Leiserson, and R. L. Rivest, Introduction to Algorithms, McGrawHill, 1990.
A. Weiss, Data Structures & Algorithm Analysis in C , 2nd Edition, Addison Wesley, 1999.
Grama, G. Karypis, V. Kumar, and A. Gupta, Introduction to Parallel Computing, 2nd Edition, Addison Wesley, 2003.

Communications
Major topics:
Probability and random processes: Basic probability, random variables, expectations, momentgenerating functions, transformation of random variables, random processes, Gaussian random process, stationarity (widesense, strictly, and cyclo stationary processes), correlation, power spectral density, representation of bandpass processes, ergodicity, MMSE (Wiener) filtering.
Fourier analysis and analog communication: Fourier series, Fourier transforms, time averages, amplitude modulation, frequency modulation, reception in noise in analog communication systems.
Digital communication systems: Sampling, pulse code modulation, binary and Mary modulation, signal space representations, optimum reception of signals, probability of error calculation.
Source coding and basic information theory: Quantization, Huffman coding, entropy of discrete sources, discrete channel mutual information, channel capacity.
Courses helpful in the exam area:
 ECE 432: Digital Communications
 ECE 530: Random Signal Analysis
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as ECE 311 and ECE 341.
Typical references:
G. Proakis, Digital Communications, 4th Edition, McGrawHill, 2001.
Papoulis and S. U. Pillai, Probability, Random Variables and Stochastic Processes, 4th Edition, McGrawHill, 2002.
P. Lathi, Modern Digital and Analog Communications, 3rd Edition, Oxford University Press, 1998.
Haykin, Communication Systems, 4th Edition, Wiley, 2000.
G. Proakis and M. Salehi, Communication Systems Engineering, 2nd Edition, Prentice Hall, 2002.

Computer architecture
Major topics:
Instruction set designs: ISA classification, addressing modes, operands and operations.
Pipelining and superscalar designs: Basic issues in pipelining, outoforder execution techniques including scoreboarding and Tomasulo algorithms, branch prediction techniques, and multithreading techniques.
Memory hierarchy designs: Cache organizations, cache performance, DRAM memory, and virtual memory systems.
Multiprocessor architecture: Taxonomy of parallel architectures, cache coherence.
Interconnection networks.
I/O devices and peripherals: Basic I/O issues such as DMA and interrupts, RAID systems.
Performance evaluation metrics: Execution time, CPI, throughput, and speedup.
Courses helpful in this exam area:
 ECE 466: Advanced Computer Architecture
 ECE 569: High Performance Processors and Systems
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as ECE 267 and ECE 366.
Typical references:
Hennessy and D. Patterson, Computer Architecture: A Quantitative Approach, 3rd Edition, Morgan Kaufmann, 2002.
Culler, J. P. Singh, and A. Gupta, Parallel Computer Architecture: A Hardware/Software Approach, Morgan Kaufmann, 1998.

Controls
Major topics:
Causality; time invariance; linearity; superposition principle; Laplace transform; transfer function; block diagrams; impulse response; frequency response; steady state response; transient response; convolution; BIBO stability; RouthHurwitz criterion; Nyquist criterion; rootlocus methods; Bode plots; feedback control.
ztransform; ztransform analysis of discretetime control systems; sampleddata systems; zeroorder hold and firstorder hold.
Stability analysis; state variable description of continuous and discrete time systems; matrix algebra; statespace representation of systems; state variable description; linear operators; impulse response matrix; time domain solution of linear matrix differential and difference equations.
Controllability; observability; reducible and irreducible realizations; state feedback; state observers; Lyapunov stability.
Courses helpful in this exam area:
 ECE 451: Control Engineering
 ECE 550: Linear Systems Theory and Design
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as ECE 310 and ECE 350.
Typical references:
C. Kuo and F. Golnaraghi, Automatic Control Systems, 8th Edition, John Wiley, 2002.
C. Dorf and R. H. Bishop, Modern Control Systems, 10th Edition, Prentice Hall, 2005.
F. Franklin, J. D. Powell, and M. L. Workman, Digital Control of Dynamic Systems, 3rd Edition, Prentice Hall, 1998.
J. Antsaklis and A. N. Michel, Linear Systems, McGrawHill, 1997.
T. Chen, Linear System Theory and Design, 3rd Edition, Oxford University Press, 1998.
Ogata, Discrete Time Control Systems, 2nd Edition, Prentice Hall, 1995.

data science
Major topics:
Statistical inference: hypothesis testing, maximum likelihood estimation, Bayesian inference, least squares, Fisher information, CramerRao bound, central limit theorem
Information: entropy, Kraft’s inequality, compression, KL divergence, crossentropy, universal compression, mutual information, Fano’s inequality
Learning: Chernoff bound, concentration of the empirical distribution, PAC learning, classification, clustering, uniform concentration and generalization, complexity and VC dimension, biasvariance dilemma, regularization
Neural networks: mathematical models of a neuron, perceptrons, optimization, the backpropagation algorithm, associative memory, Hopfield networks, support vector machines, vector quantization, PCA, convolutional networks, deep learning
Courses helpful in this exam area:
 ECE 491 Information and Learning
 ECE 559 Neural Networks
Other courses such as ECE 407 Pattern Recognition I, ECE 418 Statistical Digital Signal Processing, or ECE 534 Elements of Information Theory also can be useful. Students are expected to be proficient in the prerequisite areas, in particular probability and statistics (ECE 341), calculus (MATH 210), and linear algebra (MATH 310).
Typical references:
Information Theory, Inference and Learning Algorithms, by MacKay
Elements of Information Theory, by Cover and Thomas
Understanding Machine Learning: From Theory to Algorithms, by ShalevShwartz and BenDavid
Foundations of Data Science by Blum, Hopcroft, and Kannan
All of Statistics, by Wasserman
Deep Learning, by Goodfellow, Bengio, and Courville

Digital systems and VLSI design
Major topics:
Combinational logic minimization techniques.
Finite state machine (FSM) synthesis (Moore, Mealy).
Synthesis and analysis of synchronous and asynchronous sequential circuits.
State minimization and state assignment techniques.
Logic design using MUXs, decoders, registers, shift registers, and PLAs.
Clocking issues: Clock methods, period determination, skew and jitter, and types of timing – edge triggered, two phase timing, and pulsed timing.
Introduction to IC building blocks: Semiconductor devices, and CMOS inverter.
Static and dynamic circuit implementation techniques.
VLSI circuit design issues of latches, flipflops, and registers.
Basic concepts of integrated circuits implementation strategies: Custom, semicustom, cellbased, and arraybased design approaches.
Courses helpful in this exam area:
 ECE 465: Digital Systems Design
 ECE 467: Introduction to VLSI Design
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as ECE 265.
Typical references:
P. Nelson, H. T. Nagle, B. D. Carroll, and J. D. Irwin, Digital Logic Circuit Analysis and Design, Prentice Hall, 1995.
Wakerly, Digital Design: Principles and Practices, 4th Edition, Prentice Hall, 2006.
M. Rabaey, A. Chandrakasan, and B. Nikolic, Digital Integrated Circuits: A Design Perspective, 2nd Edition, Prentice Hall, 2003.
H. E. Weste and D. Harris, CMOS VLSI Design: A Circuits and Systems Perspective, 3rd Edition, Addison Wesley, 2005.

Electromagnetics
Major topics:
Static and dynamic fields, Poisson’s and Laplace equations, Maxwell’s equations in time and frequency domains, potentials, and solutions to Helmholtz equation.
Waves and wave propagation, scattering and diffraction, power and energy.
Microwave circuits, transmission lines, simple waveguide structures, impedance matching, and microwave circuit elements.
Antennas radiation, antenna parameters, simple antennas and radiating elements, and antenna arrays.
Courses helpful in this exam area:
 ECE 421: Introduction to Antenna Engineering
 ECE 520: Electromagnetic Field Theory
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as ECE 322.
Typical references:
L. Stutzman, Antenna Theory and Design, 2nd Edition, Wiley, 1997.
A. Balanis, Advanced Engineering Electromagnetics, Wiley, 1989.
Ishimaru, Electromagnetic Wave Propagation, Radiation and Scattering, Prentice Hall, 1991.
F. Harrington, TimeHarmonic Electromagnetic Fields, Wiley, 2001.
E. Collin, Foundations of Microwave Engineering, 2nd Edition, WileyIEEE, 2000.
P. A. Rizzi, Microwave Engineering: Passive Circuits, Prentice Hall, 1988.

Power electronics and electronic circuits
Major topics:
Electrical Circuit Characterization and Synthesis: Characterization of active networks in frequency and time domains, fundamentals of network synthesis, Sdomain transfer functions, frequency response, and elementary filter mathematics.
Filter Synthesis: Filtering; filter types and specifications – ideal filters, magnitudephase representation, lowpass filters, bandpass filters, highpass filters, etc.
Filter approximation: Passive and active filter designs
Active amplifier: Fundamentals of operational and differential amplifiers, different types of transistor amplifiers
Power Electronic Topologies: Basic isolated and nonisolated dcdc converters
Powerconverter dynamics and control: averaged modeling, stability analysis, voltage and currentmodel controls, feedbackcontrol realizations, modulation
Power Electronic Devices
Magnetics: basic highfrequency inductors and transformers, basic magnetics theory for inductor and transformer leading to modeling and equivalent circuit realizations, and design
Power semiconductor switches: switch realizations, device structure and operating principles of power diodes, power MOSFETs, and IGBTs, switchingloss calculations, and snubber design and safe operating area
Courses helpful in this exam area:
 ECE 412: Introduction to Filter Synthesis
 ECE 445: Analysis and Design of Power Electronic Circuits
Typical references:
W.K. Chen, Active Network Analysis, Teaneck, N.J.: World Scientific, 1991.
W.K. Chen, Passive and Active Filters: Theory and Implementations, New York: John Wiley, 1986.
E. Van Valkenburg, Analog Filter Design, New York: Holt, Rinehart and Winston, 1982.
R.W. Erickson and D. Maksimovic, Fundamentals of Power Electronics, Kluwer Academic Publishers, 2001.
P.T. Krein, Elements of Power Electronics, Oxford University Press, 1998.
B.J. Baliga, Power Semiconductor Devices, PWS Publishing Company, 1995.

Signal processing
Major topics:
Signals and systems: Continuoustime and discretetime signals and systems, linearity, timeinvariance, stability, causality, frequency domain description, continuoustime and discretetime Fourier transform (CTFT and DTFT), discrete Fourier transform (DFT) and its applications, fast Fourier transform (FFT), linear and circular convolution, sampling of continuoustime signals, sampling theorem and relation between CTFT and DTFT, sampling rate conversion – interpolation and decimation.
ztransform and filter design: ztransform and properties, system function, stability analysis, digital filter design and realization, infiniteduration and finiteduration impulse response (IIR and FIR) filter properties and design, linear convolution using DFT in FIR filter implementation.
Random signals: Random variables, expectations, random vectors, discretetime random signals (random sequences) and application to discretetime systems, stationarity of random sequences, autocorrelation and power spectral density of random sequences, spectral factorization.
Optimum processing of signals: Optimum signal estimation, minimum mean squared error estimation, discretetime Wiener filters, linear prediction and algorithms.
Courses helpful in this exam area:
 ECE 417: Digital Signal Processing II
 ECE 418: Statistical Digital Signal Processing
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as ECE 310, ECE 317, and ECE 341.
Typical references:
V. Oppenheim, R. W. Schafer, and J. R. Buck, DiscreteTime Signal Processing, 2nd Edition, Prentice Hall, 1999.
G. Proakis and D. Manolakis, Digital Signal Processing: Principles, Algorithms and Applications, 3rd Edition, Prentice Hall, 1996.
V. Oppenheim, A. S. Willsky, and S. H. Nawab, Signals and Systems, 2nd Edition, Prentice Hall, 1997.
Graupe, Time Series Analysis, Identification and Adaptive Filtering, 2nd Edition, Kreiger Publishing, 1989.
Kay, Fundamentals of Statistical Signal Processing, Vol. 1: Estimation Theory, Prentice Hall, 1993.
K. Mitra, Digital Signal Processing: A ComputerBased Approach, 3rd Edition, McGrawHill, 2006.

Solidstate electronics
Major topics:
Quantum Mechanics: Schrodinger’s equation; Heisenberg’s principle; solving Schrodinger’s equation in quantum wells with finite and infinite barrier heights (1dimensional solution); Fermi distribution; typical bandstructures for direct and indirect bandgap materials.
Semiconductors: Crystal structures; lattice parameter; bandgap; density of states; effective density of states; carrier distribution; resistivity; conductance; Hall effect; mobility; intrinsic and extrinsic carrier concentration; Fermi level; equilibrium and nonequilibrium; generationrecombination processes; continuity equation; Poisson’s equation; optical processes in semiconductors; radiative and nonradiative recombination; steady state and transient; drift current; diffusion current.
PN Junctions: Step junctions; graded junctions; band profile; depletion width; depletion approximation; built in potential; forward and reverse bias; diffusion length; lifetime; diffusion coefficient; drift and diffusion currents; currentvoltage relationship; quasi Fermi levels; depletion and diffusion capacitance.
Bipolar Junction Transistors: Concept of emitter, base and collector; band profile; uniform and graded doping in base region; base transit time; emitter injection efficiency; base transport factor; DC current gain (common emitter mode); device configurations (common base, common emitter, common collector); EbersMoll model; currentvoltage relationship; active, cutoff, reverse active and saturation regions of operation; small signal model.
MOSFETs: Fundamentals of MOS capacitor; accumulation, depletion and inversion regions; capacitancevoltage characteristics (CV); high frequency and low frequency CV characteristics; threshold voltage; effects of oxide charges (fixed, interface, mobile) on MOS characteristics, MOSFET, currentvoltage relationship, saturation and linear regions of operation; transconductance gain; small signal model; short channel effects.
Courses helpful in this exam area:
 ECE 448: Transistors
 ECE 540: Semiconductor Device Physics
In addition, students are expected to be familiar with basic material covered in prerequisite courses such as ECE 346.
Typical references:
Streetman and S. Banerjee, Solid State Electronic Devices, 7th Edition, Prentice Hall, 2014.
Pierret, Semiconductor Device Fundamentals, Prentice Hall, 1996.
S. M. Sze, Physics of Semiconductor Devices, 3rd Edition, Wiley, 2007.