Program Overview

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Master of Engineering in Electrical Engineering

The Master of Engineering in Electrical Engineering is a 30-credit online master's degree program that focuses on practical, hands-on coursework developed by experts in the field. This program does not require GRE scores or a thesis.

Program Summary

Prepare for a broad range of electrical engineering careers by focusing on practical, hands-on coursework developed by experts in the field. This online master's degree program does not require GRE scores or a thesis.

100% Online

Complete your Penn State coursework at your own pace and 100% online.

Application Deadline

Apply by December 20 to start January 12.

Credits and Costs

• 30 credits
• $1,037 per credit

Nationally Recognized

Our graduate engineering programs are highly ranked by U.S. News & World Report.

Gain Skills in the Theory and Application of Electrical Engineering

• Become a problem-solver who is well-versed in designing, analyzing, and operating the various electrical systems that power our world.
• Design a range of applications through AI, programming, and electrical engineering.
• Implement infrastructure of any scale, from the largest industrial complexes to the most intricate of applications.
• Use effective strategies to lead projects and innovation within an engineering context.

Courses That Prepare You for a Rapidly Evolving Field

You will study topics such as electronic communication systems, control systems, signal processing, power systems, electronic and integrated circuits, electromagnetics, and microelectronics. This highly interactive electrical engineering degree program is engaging and collaborative, but still convenient for working professionals.

Prescribed Core Courses (9 credits)

• EE 480: Linear Systems: Time Domain and Transform Analysis (3 credits)
  • The major topics covered in this course include Signals and Systems representations, classifications, and analysis using; Difference and Differential Equations, Laplace Transform, Z-Transform, Fourier series, Fourier Transform, Fast Fourier Transform (FFT), Discrete-Time Fourier Transform (DTFT) and Discrete Fourier Transform (DFT).
• EE 560: Probability, Random Variables, and Stochastic Processes (3 credits)
  • Review of probability theory and random variables; mathematical description of random signals; linear system response; Wiener, Kalman, and other filtering.
• EE 594: Research Projects (3 credits)
  • Supervision of individual research projects leading to MS or MEng papers. Written and oral reports are required.

Electives (select 21 credits)

Enrollment approval may be required for some courses on the electives list.

• A-I 570: Deep Learning (3 credits)
  • This course will cover the foundations on neural networks and deep learning networks. It covers the core concepts of deep neural networks, including the convolutional neural networks for image recognition, recurrent neural networks for sequence generation, and generative adversarial networks for image generation.
  • Prerequisite: STAT 500
• A-I 574: Natural Language Processing (3 credits)
  • This course covers basic as well as advanced concepts to gain a detailed understanding of Natural Language Processing tasks such as language modeling, text to speech generation, natural language understanding, and natural language generation. Students can learn the necessary skills to design a range of applications, including sentiment analysis, translating between languages, and answering questions. The practical implementation of these applications with deep neural networks is also discussed.
  • Prerequisite: STAT 500 and A-I 570 or DAAN 570
• A-I 801: Foundations of Artificial Intelligence (3 credits)
  • This course will teach the foundations of AI and give students a practical understanding of the field. This course gives an overview of the core concepts of AI, including the intelligent agents, knowledge and reasoning, reinforcement learning, planning and acting, belief networks, computational learning, Markov decision process, and more.
• A-I 879: Machine Vision (3 credits)
  • This course focuses on the design of computer-based, machine vision systems using appropriate algorithms and best practices. Students will learn image representation and structuring; feature extraction and segmentation; and information extraction, filtering, and analysis.
• AE 868: Commercial Solar Electric Systems (3 credits)
  • Theories and practices of solar electric systems, including component selection, performance simulation, grid interconnection, codes, and design documentation.
• AMD 527: Additive Manufacturing Processes (4 credits)
  • Comprehensive study of the fundamentals, process characteristics, economics, and practical applications of various additive manufacturing processes.
• AMD 545: Engineering and Scientific Principles of Additive Manufacturing (4 credits)
  • Explores processes with a focus on the fundamentals of sintering and fusion of metals, ceramics, and polymers.
• AMD 562: Design for Additive Manufacturing (4 credits)
  • Explore design methods and tools for additive manufacturing, including opportunistic and restrictive aspects of different additive manufacturing processes and their related industry applications.
• DAAN 862: Analytics Programming in Python (3 credits)
  • This course will explore the development of analytics systems and the application of best practices and established software design principles using the Python programming language and its several toolkits.
• EE 410: Linear Electronic Design (3 credits)
  • The course emphasizes integrated circuit process-compatible circuit design techniques in recognition of the amazing synergy that has characterized the relationship between modern circuits and integrated circuit processing technology.
• EE 416: Digital Integrated Circuits (3 credits)
  • Analyses and design of digital integrated circuit building blocks, including logic gates, flip-flops, memory elements, analog switches, multiplexers, and converters.
• EE 417: Digital Design Using Field Programmable Devices (3 credits)
  • This course delves into the utilization of Programmable Logic Devices (PLDs), specifically Field Programmable Gate Arrays (FPGAs), renowned for their application in rapid prototyping and real-time designs.
• EE 443: Introduction to Heterogeneous Integration and Packaging of Electronic Systems (3 credits)
  • In this course, you will learn how heterogeneous integration and packaging with chiplets is revolutionizing the semiconductor industry. This course introduces the history, challenges, and opportunities arising in the packaging of electronic systems.
• EE 460: Communication Systems II (3 credits)
  • Provides detailed performance analysis of communications systems first studied in introductory communications courses such as EE 360 or EE 461.
• EE 488: Power Systems Analysis I (3 credits)
  • Fundamentals, power transformers, transmission lines, power flow, fault calculations, power system controls.
• EE 531: Engineering Electromagnetics (3 credits)
  • Electromagnetic field theory fundamentals with application to transmission lines, waveguides, cavities, antennas, radar, and radio propagation.
• EE 553: Topics in Digital Signal Processing (3 credits)
  • Parametric modeling, spectral estimation, efficient transforms and convolution algorithms, multirate processing, and selected applications involving non-linear and time-variant filters.
• EE 556: Graphs, Algorithms, and Neural Networks (3 credits)
  • Examine neural networks by exploiting graph theory for offering alternate solutions to classical problems in signal processing and control.
• EE 580: Linear Control Systems (3 credits)
  • Continuous and discrete-time linear control systems; state variable models; analytical design for deterministic and random inputs; time-varying systems and stability.
• EE 581: Optimal Control (3 credits)
  • Variational methods in control system design; classical calculus of variations, dynamic programming, maximum principle; optimal digital control systems; state estimation.
  • Prerequisite: EE 580
• EE 588: Power System Control and Operation (3 credits)
  • Steady-state and dynamic model of synchronous machines, excitation systems, unit commitment, control of generation, optimal power flow.
  • Prerequisite: EE 488
• EE 589: Smart Grid Control and Dynamics (3 credits)
  • Covers the application of advanced power electronics in power apparatus.
• EE 597: Special Topics: Linear Discrete-Time Control Systems (3 credits)
  • Tools to analyze and design discrete time (digital) control hardware and software systems; advantages of discrete time control, including increased flexibility in control modification and tuning, improved system reliability, easier system integration, and reduced design time.
• EME 802: Renewable and Sustainable Energy Systems (3 credits)
  • An overview of renewable energy technologies and energy system analysis.
• EME 812: Utility Solar Power and Concentration (3 credits)
  • Technical and theoretical background for utility-scale solar energy conversion technologies to generate electric power.
  • Prerequisite: EME 810
• ENGR 801: Engineering Leadership for Corporate Innovation (3 credits)
  • Traditional and contemporary leadership theory is analyzed to determine effective strategies for leading projects and innovation within an engineering context.
• ME 452: Vehicle Road Dynamics (3 credits)
  • This course conducts investigations of one-dimensional, two-dimensional, and three-dimensional dynamics, kinematics and design integrated into the study of vehicle dynamics.
• ME 544: Engineering Mathematics (3 credits)
  • This course covers ordinary and partial differential equations, linear algebra, numerical methods, special functions, vector calculus, Fourier methods, and complex analysis.
• ME 552: Optimal Control of Energy Systems (3 credits)
  • This course provides an overview of the fundamental principles and methods of optimal control, dynamic programming, and extremum-seeking control, with a focus on the application of these tools to a variety of problems in the energy generation, storage, and management domain.
• ME 556: Robotic Concepts (3 credits)
  • Analysis of robotic systems; end effectors, vision systems, sensors, stability and control, off-line programming, simulation of robotic systems.
• STAT 500: Applied Statistics (3 credits)
  • Descriptive statistics, hypothesis testing, power, estimation, confidence intervals, regression, one- and two-way ANOVA, chi-square tests, diagnostics.
  • Prerequisite: one undergraduate course in statistics
• STAT 505: Applied Multivariate Statistical Analysis (3 credits)
  • Analysis of multivariate data; T-squared tests; partial correlation; discrimination; MANOVA; cluster analysis; regression; growth curves; factor analysis; principal components; canonical correlations.
  • Prerequisite: STAT 501 and STAT 502; matrix algebra

Course Availability

If you're ready to see when your courses will be offered, visit our public LionPATH course search to start planning ahead.

Complete Your Engineering Degree in Two Years

You can pursue the program on a part-time basis and complete the program within two years, based on completion of two courses a semester. You must maintain a 3.00 grade-point average in both prescribed and supporting courses approved by the program to graduate.

You must successfully complete the following program requirements:

• At least 21 credits must be in Engineering courses.
• At least 15 credits must be in Electrical Engineering (EE) courses.
• At least 18 credits must be at the 500 level.
• All students must complete three credits of EE 594, Research Projects.

As part of the program, you will write a non-thesis scholarly report or engineering paper that you and your faculty adviser have mutually agreed upon, which is suitable for publication at a national or international conference, such as the IEEE's (Institute of Electrical and Electronics Engineers), or in a professional journal, in order to obtain this degree.

Advance Your Career

With technology constantly evolving and playing a more prominent role in our lives, electrical engineers with advanced technical proficiencies are in high demand. As a graduate of this program, you can leverage your acquired knowledge and Penn State career resources to pursue careers in a variety of engineering fields.

Job Titles Related to This Degree

You could work in any number of industries, including automotive, telecommunications, chemical, electronics manufacturing, consumer electronics, bioengineering, power generation and distribution, scientific research, military and defense, aerospace, transportation, and many more.

The following roles are often held by people with this type of degree:

• Electrical Controls Engineer
• Electrical Design Engineer
• Electrical Engineering Manager
• Electrical Project Engineer
• Power Systems Engineer

Employment Outlook for Occupational Fields Related to This Degree

Estimates of employment growth and total employment are provided by the U.S. Bureau of Labor Statistics and are subject to change. While these occupations are often pursued by graduates with this degree, individual outcomes may vary depending on a variety of factors.

Electrical Engineers

• 9.1% employment growth (10 years)
• 188,790 total employment

Architectural and Engineering Managers

• 5.5% employment growth (10 years)
• 210,340 total employment

Career Services to Set You Up for Success

From the day you're accepted as a student, you can access resources and tools provided by Penn State World Campus Career Services to further your career. These resources are beneficial whether you're searching for a job or advancing in an established career.

• Opportunities to connect with employers
• Career counselor/coach support
• Occupation and salary information
• Internships
• Graduate school resources

Costs and Financial Aid

Learn about this program's tuition, fees, scholarship opportunities, grants, payment options, and military benefits.

Graduate Tuition

Graduate tuition is calculated based on the number of credits for which you register. Tuition is due shortly after each semester begins and rates are assessed every semester of enrollment.

2025–26 Academic Year Rates

Tuition Rates for the Fall 2025, Spring 2026, and Summer 2026 Semesters

Number of Credits	Cost
11 or fewer	$1,037 per credit
12 or more	$12,448 per semester

2026–27 Academic Year Rates

Tuition Rates for the Fall 2026, Spring 2027, and Summer 2027 Semesters

Number of Credits	Cost
11 or fewer	$1,048 per credit
12 or more	$12,572 per semester

Financial Aid and Military Benefits

Some students may qualify for financial aid. Take the time to research financial aid, scholarships, and payment options as you prepare to apply. Federal financial aid may only be used to pay for credits used to satisfy program requirements.

Military service members, veterans, and their spouses or dependents should explore these potential military education benefits and financial aid opportunities, as well.

Additional Cost of Attendance Details

To view the detailed list of cost of attendance elements:

• Visit the Tuition Information site
• Click the plus sign to expand the table
• Select a semester from the World Campus row

Technical Requirements

Review the technical requirements for this program.

Earn a Valuable Credential along the Way

Show mastery of specific subjects before your degree is complete. Thanks to shared courses across programs, students can often earn a certificate along with their degree in less time than if they earned them separately.

Certificate Program Related to This Degree

The following certificate can be earned while completing this degree program:

• Electrical Engineering (Postbaccalaureate Certificate)

Obtain skills and knowledge that can support your work as an engineer who designs electrical devices and systems that usher in the future. Courses with a grade of B or better from this 9-credit certificate can be applied to the World Campus Master of Engineering in Electrical Engineering.

Set Your Own Pace

Whether you are looking to finish your program as quickly as possible or balance your studies with your busy life, Penn State World Campus can help you achieve your education goals. Many students take one or two courses per semester.

How Quickly Can I Earn This Degree?

Our online courses typically follow a 12- to 15-week semester cycle, and there are three semesters per year (spring, summer, and fall). If you plan to take a heavy course load, you should expect your coursework to be your primary focus and discuss your schedule with your academic adviser.

To Finish Your Degree in One to Two Years

• Take 3–4 courses each semester

To Finish Your Degree in Two to Three Years

• Take 2–3 courses each semester

To Finish Your Degree in Three to Four Years

• Take 1 course each semester

Timelines may vary based on course availability.

Convenient Online Format

This program's convenient online format gives you the flexibility you need to study around your busy schedule. You can skip the lengthy commute without sacrificing the quality of your education and prepare yourself for more rewarding career opportunities without leaving your home.

A Trusted Leader in Online Education

Penn State has a history of more than 100 years of distance education, and World Campus has been a leader in online learning for more than two decades. Our online learning environment offers the same quality education that our students experience on campus.

Information for Military and Veterans

Are you a member of the military, a veteran, or a military spouse? Please visit our military website for additional information regarding financial aid, transfer credits, and application instructions.

How to Apply to Penn State

Application Instructions

Complete your application and submit all required materials by the appropriate deadline. Your deadline will depend on the semester you plan to start your courses.

• Spring Deadline: Apply by December 20 to start January 12
• Summer Deadline: Apply by May 3 to start May 18
• Fall Deadline: Apply by August 3, 2026, to start August 24, 2026

Space is limited, and you are encouraged to apply early. Applications will be reviewed until all seats are filled.

Steps to Apply

1. Review the admission requirements. For admission to the J. Jeffrey and Ann Marie Fox Graduate School, an applicant must hold either (1) a baccalaureate degree from a regionally accredited U.S. institution or (2) a tertiary (postsecondary) degree that is deemed comparable to a four-year bachelor's degree from a regionally accredited U.S. institution. This degree must be from an officially recognized degree-granting institution in the country in which it operates.

It is expected that students have an ABET accredited Bachelor of Science degree in Electrical Engineering (BSEE) with a GPA of at least 3.0 in the final two years of school. Admission decisions will also be based on relevant transcripts, personal statement, work experience, and recommendation letters.

Those applying for admission as a master of engineering candidate without an ABET accredited bachelor of science in electrical engineering (BSEE) degree may be admitted with a few stipulations: fewer than two deficiencies in background, which must be remedied in the first two semesters of the program; these prerequisite courses will be in addition to the required number of credits for the degree; the student must also maintain a GPA of at least 3.0 in all prerequisite courses; the student must have a strong background in mathematics to apply. Note: The online MENG EE program does not offer online prerequisite courses.

Prerequisite courses for students who have not earned a Bachelor of Science in Electrical Engineering degree are: Calculus I, Calculus II, Calculus III (Multivariate calculus), Differential Equations, Probability/Statistics, Electromagnetics, Electrical Communications, Control System Design, Digital Signal Processing, Power/Machines, Signal and Systems (Fourier and Laplace transforms), Physics (Calculus based), Computer Programming (C,C++ or equivalent), Electrical Circuits (Calculus based) and Electronic Circuits. It is also very helpful to have some experience in MATLAB programming.

The program contains many courses requiring a solid background in mathematics with at least three semesters of calculus including multivariate calculus, differential equations and probability/statistics. Students with a strong background in mathematics may apply. The admissions committee will consider the academic background, as evidenced by the transcript, as part of the overall application.

All applicants are expected to have earned a junior/senior grade point average of 3.0 or higher.

2. Gather your required materials. Applications are submitted electronically and include a nonrefundable application fee. You will need to upload the following items as part of your application:

• Official transcripts from each institution attended, regardless of the number of credits or semesters completed. Transcripts not in English must be accompanied by a certified translation. If you are a Penn State alum, you do not need to request transcripts for credits earned at Penn State but must list Penn State as part of your academic history.
• GPA and Test Scores — Postsecondary (undergraduate), junior/senior (last two years) GPA is required. Official GRE or GMAT test scores will be considered if submitted, but are NOT required.
• English Proficiency — The language of instruction at Penn State is English. With some exceptions, international applicants must take and submit scores for the Test of English as a Foreign Language (TOEFL) or International English Language Testing System (IELTS). Minimum test scores and exceptions are found in the English Proficiency section on the Fox Graduate School's "Requirements for Graduate Admission" page. Visit the TOEFL website for testing information. Penn State's institutional code is 2660.
• References (3) — You will need to initiate the process through the online application by entering names, email addresses, and mailing addresses of three references. Upon submission of your application, an email will be sent to each reference requesting they complete a brief online recommendation regarding your commitment for success in an online program. Please inform all recommenders they must submit the form in order for your application to be complete.

Program-Specific Questions/Materials

• Résumé — Upload your résumé to the online application.
• Personal Statement — A one- to two-page statement of purpose outlining personal career goals and reasons for wanting to enroll in the program. This statement should be specific and include information about your short- and long-term goals and how enrolling in the program may help to achieve them. The statement of purpose also offers you the opportunity to demonstrate your writing and communication skills, specify examples of leadership, and provide pertinent information that will assist the committee in selecting candidates who can benefit from and contribute to the electrical engineering program.

3. Create a Penn State login account. To begin the online application, you will need a Penn State account.
4. Read the application instructions. You can begin your online application at any time. Your progress within the online application system will be saved as you go, allowing you to return at any point as you gather additional information and required materials.
5. Complete the application.

Admissions Help

If you have questions about the admissions process, contact an admissions counselor.

Contact Us

To learn more about the Master of Engineering in Electrical Engineering, please contact:

• For general questions about Penn State World Campus: World Campus Admissions Counselors
• For general questions about the program: Dr. Nashwa Elaraby, Professor-in-Charge, Penn State Harrisburg, School of Science, Engineering, and Technology, 777 West Harrisburg Pike, Olmsted Building, W256, Middletown PA 17057

Learn from the Best

The Master of Engineering in Electrical Engineering is offered in partnership with the Penn State Harrisburg School of Science, Engineering, and Technology, and Penn State Department of Electrical Engineering.

Faculty

• Shayan Behzadirafi
  • Degree: Ph.D., University of North Dakota
  • Degree: Post-Doctoral, New York University
  • Dr. Shayan Behzadirafi is currently with the Research and System Planning Department at the New York Power Authority. He is also an adjunct faculty member with NYU. His research interests include power flow controllers, power system protection, power system reliability, power system transients, and electrical machinery.
• Nashwa Elaraby
  • Degree: Ph.D., Electrical Engineering, Temple University
  • Degree: M.S., Electrical Engineering, Alexandria University, Egypt
  • Degree: B.S., Electrical Engineering, Alexandria University, Egypt
  • Dr. Nashwa Elaraby teaches courses in programmable logic devices, electronic circuit design, electrical circuits, data acquisition, logic design, and switching circuits. Her research interests include real-time parallel computations on field programmable gate arrays, multi-gigabit transceivers, brain-machine interface, and hardware design.
• Peter Idowu
  • Degree: Ph.D., Electrical Engineering, The University of Toledo
  • Dr. Peter Idowu's research interests include hardware-based microgrid test beds, MAS control of microgrids, induction motor current signature analysis, adaptive stabilizers for multimachine power systems, and power engineering education. Dr. Idowu teaches graduate and undergraduate courses in power systems analysis and operation and control of power systems. He manages the PPL Electric Utilities Power Lab research facility at Penn State Harrisburg.
• Kiana Karami
  • Degree: Ph.D., Electrical and Computer Engineering, University of Calgary
  • Degree: M.S., Electrical and Computer Engineering, University of Colorado Colorado Springs
  • Degree: B.S., Electrical and Computer Engineering, Shiraz University
  • Dr. Kiana Karami is an assistant professor in the electrical engineering department at Penn State Harrisburg, where she has been a faculty member since 2020. She teaches both undergraduate and graduate courses, focusing on control systems, optimal control, and senior design projects. Her research interests lie in the areas of system identification, control systems, and optimization. She is dedicated to advancing engineering education and research through innovative methodologies and hands-on learning experiences.
• David J. Miller
  • Degree: Ph.D., Electrical and Computer Engineering, University of California, Santa Barbara
  • Degree: M.S., Electrical Engineering, University of Pennsylvania
  • Degree: B.Sc. E., Electrical Engineering and Computer Science, Princeton University
  • Dr. David J. Miller's research interests include machine learning, source coding, network security, and bioinformatics. Dr. Miller is a member of the IEEE Signal Processing Society Conference Board and a member of the Machine Learning for Signal Processing (MLSP) Technical Committee; he was the chair of the committee from 2007–2009. He was general chair for the 2001 IEEE Workshop on Neural Networks for Signal Processing. From 2004–2007, he was associate editor for IEEE Transactions on Signal Processing. He received the National Science Foundation CAREER Award in 1996.
• Aldo Morales
  • Degree: Ph.D., Electrical and Computer Engineering, State University of New York at Buffalo
  • Degree: M.S., Electrical and Computer Engineering, State University of New York at Buffalo
  • Degree: B.Sc. E. E., Northern University (Now University of Tarapaca), Arica, Chile
  • Degree: Thesis: “Discriminator for Telemetry”
  • Dr. Aldo Morales' research interests include signal integrity, FPGA implementation for high-speed applications, communications, digital signal, image and video processing, wavelets, mathematical morphology and nonlinear signal processing, and neural networks. He teaches courses in digital signal processing, topics in digital signal processing, random variables and stochastic processes, wavelets, signal and systems, neural networks (undergraduate), and communications.
• Victor P. Pasko
  • Degree: Ph.D., Electrical Engineering, Stanford University
  • Dr. Victor P. Pasko's research interests include atmospheric electrodynamics, atmospheric acoustic-gravity waves, gas discharge phenomena, computational plasma physics, and electromagnetics. He teaches undergraduate and graduate courses in the areas of engineering electromagnetics, plasmas, and plasma-assisted materials processing. From 2005 to 2008, Dr. Pasko served as chair of Atmospheric and Space Electricity Focus Group of American Geophysical Union. He served as a chair of U.S. Commission of International Union of Radio Science from 2011 to 2014.
• Mohammad-Reza Tofighi
  • Degree: Ph.D., Electrical Engineering, Electrophysics, Drexel University
  • Degree: M.S., Electrical Engineering, Communications, Iran University of Science and Technology
  • Degree: B.S., Electrical Engineering, Electronics, Sharif University of Technology
  • Dr. Mohammad-Reza Tofighi’s research interests are in radio frequency (RF) and microwave technology. A member of Penn State Harrisburg’s electrical engineering faculty since 2004, he teaches undergraduate and graduate courses on RF and microwave engineering, engineering electromagnetics, antennas, communication systems, and electronics.
• Scott van Tonningen
  • Degree: Ph.D., Electrical Engineering, University of Colorado
  • Degree: M.S., Electrical Engineering, University of Illinois
  • Degree: B.S., Electrical Engineering, United States Air Force Academy
  • Dr. Scott van Tonningen teaches courses in the areas of electrical power, control systems, optimal control, linear signals and systems, and electronics. His research interests include the areas of optimal control, numerical methods, and nonlinear systems.

News

Penn State featured in U.S. News’ 2025 ‘Best Online Programs’ rankings

New online electrical engineering certificate offers full course flexibility

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This is the real Penn State. You will take courses with curriculum developed by the same professors who teach on campus. You can expect the same caliber of academic quality that you associate with Penn State.

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