Navigating ECSE

Majors within ECSE are comprised of a variety of concentration areas ranging from large physical and conceptual frameworks to work at nanoscale. You can explore the majors and their associated concentration areas below. The Program Templates combine the majors and concentrations into a checklist and schedule to guide you through your program at ECSE.

Choosing Electives

Depending on your major, electives (Restricted, Lab, Technical, and Free) are used to:

  1. Gain a breadth of knowledge across different sub-disciplines (concentrations) of Electrical Engineering or Computer and Systems Engineering, OR
  2. Gain depth of knowledge within a particular sub-discipline (concentrations) of Electrical Engineering or Computer and Systems Engineering, OR
  3. Fulfill the course requirements of a dual major.

Though concentrations are provided here to provide guidance to courses a student may wish to take to develop a focus in a particular area, they are not required. Please see Program Templates for specific information toward your major regarding concentrations.

Concentration Areas

(Comp Sci)
This area provides the foundation needed for effective computing. Foundations learned affects the future of networks of all kinds (computer networks, social networks, information networks, sensor networks); machine learning and data mining; distributed algorithms; graph algorithms; algorithmic game theory and computational economics; independent and strategic agents; voting and social choice; computational finance; security; and bioinformatics.
(Comp Sci)
This area tackles the theoretical and applied sides of extracting knowledge from data.  Within the Big Data arena, efficient, scalable, and parallel algorithms for data mining and data management tasks (association rules, classification, clustering, sequence mining, etc.) are emphasized. For small data sets, the emphasis is on robust learning systems (supervised, unsupervised and reinforcement). Several application areas include: computational biology (bioinformatics, computational genomics); biomedical engineering; public health informatics; cheminformatics, web mining; geographic information systems; computational finance; natural language processing, and, multi-agent social data aggregation into informed actions (such as in recommendation systems like Yelp and TripAdvisor).
Computer networking addresses the development of protocols and architectures for both wired and wireless networks and their modeling for performance evaluation. Emerging technologies for wireless and optical last mile access, wireless sensors networks, network management, traffic management, congestion control, traffic engineering, and quality-of-service (QoS) architectures are basic applications.
Technical advancement in energy sources and systems is becoming critically important to meet the world's increasing energy needs and demands within the environmental, economic, and national security constraints today. Our faculty are conducting active research programs and projects in electric and magnetic field computation, electrical transients and switching technology, power system analysis and optimization, energy harvesting electromechanical devices, photovoltaic devices and systems, and semiconductor power devices and electronics. Power electronics and electromechanics play critical roles in ensuring energy security and achieving high energy efficiency. These energy converters provide the foundation for the utilization and integration of renewable energy resources, and enable energy-efficient technologies such as solid-state lighting, variable-speed motor drives, and more-electric transportation systems. Current interests and research activities include smart power semiconductor devices and ICs; efficient ac-dc and dc-dc power conversion for IT, lighting and other electronics applications; renewable energy systems and smart grids; autonomous and mobile power systems and vibration-based energy harvesting systems enabled by power electronics; as well as multilevel modeling and analysis of complex power electronics and electromechanical systems.
Advanced manufacturing is accelerating the translation of American innovations in science and technology to increase productivity, profitability and domestic and international competitiveness. Students will study the underlying theory, technology, and standard industrial practice for advanced manufacturing processes and systems with a focus on robotics and control.

Faculty interests include advanced control algorithms development in the areas of nonlinear control, adaptive control, multivariable control, robust control, distributed control, and optimal control. These algorithms are applied to robotics, automation systems, robotic multi-vehicle (ground, air, water) coordination, power generation and transmission systems, power electronics, networked systems, micro and nano-systems, biomedical and biological systems, and discrete-event systems. Current projects include planning and control for advanced manufacturing systems, multi-robot actuator and sensor networks for coordinated monitoring and manipulation, and precision motion and force control with vision guidance in micro- and nano-assembly manufacturing and distributed robotics for environmental observation and monitoring. Another area of interest is nonlinear control of large-scale interconnected systems (communication and power networks, vehicle formations, etc.) with limited, local information available to each component of the system. Discrete-event systems theory is a modeling and control discipline relevant to computer-communication systems, transportation systems, as well as the modeling and control of automated manufacturing systems.

Recent advances in biotechnology have transformed the field of biology in a profound way. Large quantities of data obtainable from measurements of biomolecular compounds and interactions necessitate the development of novel methods of analysis to extract meaningful information. This leads to more quantitative methods by which various cellular biological phenomena are analyzed using mathematical models. Systems biology is the study of an organism, viewed as an integrated and interacting network of genes, proteins, and biochemical reactions that give rise to life.

This area covers a range of technologies and applications. They include image reconstruction, pattern recognition, computer vision, image and video processing, artificial intelligence, computer graphics, machine learning, computational geometry, geographic information science and computational cartography. Primary application areas include systems biology, bioinformatics, computer-assisted surgery, radiation treatment planning, diffuse optical and optical coherence tomography, synthetic aperture imaging, distributed RF imaging, camera networks, range data processing, large geometric datasets, image and video processing for human viewers including visual effects in movies and television, image analysis aids to neurobiology, and multimodality imaging and analysis.
The development of advanced computer systems and their interconnection to facilitate ubiquitous and pervasive computing capabilities is the primary focus of this area. Research topics related to the design, implementation, layout, and testing of hardware systems include the design and testing of digital and mixed-signal chips and the development of computer-aided design tools. Other topics, many in conjunction with Electrophysical Devices and Systems (below), include error correcting coding system design and VLSI implementation for magnetic and holographic storage, algorithm/architecture co-design for wireless multi-antenna signal processing, fault tolerance for semiconductor and molecular nanoelectronic memory. Work in this group includes broadband multi-Gb/s communications circuits and wafer-level 3D integration for millimeter wave smart antennas. RF-powered wireless communications circuits for bio-implantable microsystems and methodologies to enable inexpensive portable platforms for reliable, fast, safe environmental assessment and biomedical diagnostics are of particular interest.
Computer Hardware
 
Advanced study and research in this field deals with the encoding, transmission, retrieval, and interpretation of information in many forms. Students may pursue programs of study focusing on mathematical foundations, improved algorithms, and hardware/software implementation. Communications research focuses on the transmission of information over wireless, optical, and wired channels. Telecommunications engineering creates wired and wireless systems that satisfy desirable societal, bandwidth, and hardware constraints. Research in statistical communications aims at reducing adverse effects on signal transmission in such systems through probabilistic modeling. The channels considered range from subminiature networks inside a computer chip, through broadband cable and communications satellites.
Electronics
 

The discovery of new devices and improvement of existing ones led to the modern electronic industry. These new devices are the basic building blocks of any new systems that positively impact our daily lives. Many of our faculty work in developing such new devices using cutting edge technology and then employ them in building state of the art systems. State of the art laboratory facilities and a clean room are available to carry out advanced study and research in these areas.

One of the new projects involves investigation of a new regime of transistor operation in the terahertz range using the excitation and rectification of plasma waves in the transistor channel. Several specialized laboratories are available that are equipped to meet industrial standards for advanced research techniques. The electronic materials laboratory includes several state-of-the-art bulk crystal growth systems, wafer slicing and chemical-mechanical polishing facilities, liquid phase epitaxy system for multilayer hetero-epitaxial growth, and cold wall epitaxial reactors for the growth of single crystal III-V, II-VI semiconductors.

We are at the threshold of a new era in how humankind harnesses the enormous capabilities of light. We are developing light sources based on semiconductors that exhibit very high efficiency as well as detailed controllability. The controllability, by design or by real-time tunability, includes the emission spectrum, the color temperature, the polarization, the spatial emission pattern, and the temporal modulation. The controllability of semiconductor-based smart lighting sources based on the dynamic environmental characteristics of where they are deployed is a unique feature that is not shared by any other light source.

In contrast to conventional light sources, the efficiency of semiconductor-based solid-state lighting devices is not determined by fundamental limits. Instead the efficiency of solid-state lighting devices is limited only by our own creativity. Overcoming current limitations enables solid-state lighting devices to be up to 20 times more efficient than conventional light bulbs. As a result, gigantic quantities of energy and financial resources could be saved by the global introduction of solid-state lighting. In addition, solid-state lighting technology can dramatically reduce the emission of greenhouse gases, acid-rain gases and highly toxic mercury. An equally important aspect of solid-state lighting devices is their ability to be tunable, interactive, responsive, and intelligent, thereby making them truly smart devices.

Concentration Areas by ECSE Major

Courses by Major

The following charts show the basic, core, and elective courses you will take for each major in ECSE. The color key follows the same pattern as found in the Program Templates.

Electrical Engineering Majors

Science Credits
  • CSCI 1100 - Computer Science 1
  • Science Electives* (choose one)
    • BIOL 1010 - Introduction to Biology
    • BIOL 2120 - Introduction to Cell and Molecular Biology
    • CHEM 1100 - Chemistry 1
  • PHYS 1100 - Physics 1
  • PHYS 1200 - Physics 2
Mathematics Credits
  • MATH 1010 - Calculus 1
  • MATH 1020 - Calculus 2
  • MATH 2400 - Introduction to Differential Equations
  • MATH 2010 - Multivariable Calculus & Matrix Algebra
Basic
Core Engineering Credits
  • ENGR 1200 - Engineering Graphics & CAD
  • ENGR 2350 - Embedded Control
  • ENGR 2050 - Introduction to Engineering Design
  • ENGR 4010 - Professional Development 3
Core ECSE Credits
  • ECSE 1010- Introduction to ECSE
  • ECSE 2610 - Computer Components and Operations
  • ECSE 2010 - Electrics Circuits
  • ECSE 2050 - Introduction to Electronics
  • ECSE 2410 - Signals & Systems
  • ECSE 2500 - Engineering Probability
  • ECSE 2100 - Fields and Waves
  • ECSE 2110 - Electrical Energy Systems
  • ECSE 2210 - Microelectronics Technology
  • ECSE 2900 - ECSE Enrichment Seminar
  • ECSE 4900 - Multidisciplinary Capstone
Core
Communications and Information Processing
ECSE Elective Credits
  • Lab Elective
    • ECSE 4760 – Real-Time Applications in Control and Communications
  • Technical
    • MATH 4300 – Introduction to Complex Variables: Theory and Applications
    • MATH 4100 – Linear Algebra
Restricted or Free Elective Credits
  • ECSE 4520 – Communication Systems
  • ECSE 4560 - Digital Communications
  • ECSE 4530 – Digital Signal Processing
  • ECSE 4540 – Introduction to Image Processing
  • ECSE 4800 – Subsurface Sensing and Imaging Systems
Control and Robotics
ECSE Elective Credits
  • Lab Elective
    • ECSE 4760 – Real-Time Applications in Control and Communications
  • Technical Elective
    • MATH 4100 – Linear Algebra
Restricted or Free Elective Credits
  • ECSE 4440 - Control Systems Engineering
  • ECSE 4510 – Digital Control Systems
  • ECSE 4480 – Robotics I
  • ECSE 4490 – Robotics II
  • ECSE 4530 – Digital Signal Processing
Electric Power and Energy
ECSE Elective Credits
  • Lab Elective
    • ECSE 4130 – EPE Laboratory
Restricted or Free Elective Credits
  • ECSE 4080 – Semiconductor Power Electronics
  • ECSE 4110 – Power Engineering Fundamentals
  • ECSE 4120 – Electromechanics
  • ECSE 4180 – Industrial Power System Design
Electronics
ECSE Elective Credits
  • Lab Elective
    • ECSE 4220 – VLSI Design
Restricted or Free Elective Credits
  • ECSE 4040 – Digital Electronics
  • ECSE 4050 – Advanced Electronics
  • ECSE 4080 – Semiconductor Power Electronics
  • ECSE 4090 – Mechatronics
Manufacturing
ECSE Elective Credits
  • Lab Elective
    • ENGR 4710 – Advanced Manufacturing Laboratory I
Restricted or Free Elective Credits
  • ENGR 4720 – Advanced Manufacturing Laboratory II
  • ECSE 4440 – Control Systems Engineering
  • ECSE 4480 – Robotics I
  • ECSE 4490 – Robotics II
Microelectronics and Electromagnetics
ECSE Elective Credits
  • Lab Elective
    • ECSE 4220 – VLSI Design
  • Technical Elective
    • MATH 4600 – Advanced Calculus
Restricted or Free Elective Credits
  • ECSE 4250 – Integrated Circuit Processing and Design
  • ECSE 4630 – Lasers and Optical Systems
  • ECSE 4720 – Solid State Physics
  • ECSE 4160 – Fields & Waves II
  • ECSE 4320 – Plasma Engineering
Photonics, Optics, and Optoelectronics
ECSE Elective Credits
  • Lab Elective
    • ECSE 4220 – VLSI Design
  • Technical Elective
    • MATH 4600 – Advanced Calculus
Restricted or Free Elective Credits
  • ECSE 4250 – Integrated Circuit Processing and Design
  • ECSE 4630 – Lasers and Optical Systems
  • ECSE 4640 – Optical Communications and Integrated Optics
  • ECSE 4720 – Solid State Physics
  • ECSE 4961 – Introduction to Optoelectronics Technology
  • ECSE 4964 – Fundamentals of Solid State Lighting Systems
Concentration Areas

Computer Systems Majors

Science Credits
  • CSCI 1100 - Computer Science 1
  • CSCI 1200 – Data Structures
  • CSCI 2200 – Foundations of Computer Science
  • CSCI 2300 – Introductions to Algorithms
  • Science Electives* (choose one)
    • BIOL 1010 - Introduction to Biology
    • BIOL 2120 - Introduction to Cell and Molecular Biology
    • CHEM 1100 - Chemistry 1
  • PHYS 1100 - Physics 1
  • PHYS 1200 - Physics 2
Mathematics Credits
  • MATH 1010 - Calculus 1
  • MATH 1020 - Calculus 2
  • MATH 2400 - Introduction to Differential Equations
  • MATH 2010 - Multivariable Calculus & Matrix Algebra
Basic
Core Engineering Credits
  • ENGR 1200 - Engineering Graphics & CAD
  • ENGR 2350 - Embedded Control
  • ENGR 2050 - Introduction to Engineering Design
  • ENGR 4010 - Professional Development 3
Core ECSE Credits
  • ECSE 1010- Introduction to ECSE
  • ECSE 2610 - Computer Components and Operations
  • ECSE 2660 – Computer Architecture, Networks, and Operating Systems
  • ECSE 2010 - Electrics Circuits
  • ECSE 2410 - Signals & Systems
  • ECSE 2500 - Engineering Probability
  • ECSE 2900 - ECSE Enrichment Seminar
  • ECSE 4900 - Multidisciplinary Capstone
Core
Computer Graphics & Applications
ECSE Elective Credits
  • Computer Engineering Electives
    • ECSE 4750 – Computer Graphics
    • CSCI 4380 – Database Systems
  • Technical
    • MATH 4300 – Introduction to Complex Variables: Theory and Applications
Restricted or Free Elective Credits
  • CSCI 4530 - Advanced Computer Graphics
  • CSCI 4520 - Game Development
Computer Hardware
ECSE Elective Credits
  • Computer Engineering Elective
    • ECSE 4790 – Microprocessor Systems (*also Lab Elective)
Restricted or Free Elective Credits
  • ECSE 4220- VLSI Design
  • ECSE 4760 – Computer Hardware Design
  • ECSE 4770 – Advanced Computer Hardware Design
Computer Networks
ECSE Elective Credits
  • Computer Engineering Elective
    • ECSE 4670 – Computer Communications Networks
Restricted or Free Elective Credits
  • CSCI 4220 – Network Programming
  • CSCI 4650 – Networking Laboratory I
  • CSCI 4660 – Networking Laboratory II
  • CSCI 4670 – Networking Security Laboratory
Computer Systems
ECSE Elective Credits
  • Computer Engineering Elective
    • ECSE 4790 – Microprocessor Systems (*also Lab Elective)
Restricted or Free Elective Credits
  • ECSE 4770 – Computer Hardware Design (Lab Elective)
  • CSCI 4050 – Computability and Complexity
  • CSCI 4210 – Operating Systems
  • CSCI 4220 – Network Programming
  • CSCI 4320 – Parallel Programming
  • ECSE 4740 – Applied Parallel Computing for Engineering
  • MATH 4800/CSCI 4800 – Numerical Computing
  • MATH 4150/CSCI 4260 – Graph Theory
Concentration Areas

Computer Systems and Computer Science Dual Majors

Science Credits
  • CSCI 1100 - Computer Science 1
  • CSCI 1200 – Data Structures
  • CSCI 2200 – Foundations of Computer Science
  • CSCI 2300 – Introductions to Algorithms
  • Science Electives* (choose one)
    • BIOL 1010 - Introduction to Biology
    • BIOL 2120 - Introduction to Cell and Molecular Biology
    • CHEM 1100 - Chemistry 1
  • PHYS 1100 - Physics 1
  • PHYS 1200 - Physics 2
Mathematics Credits
  • MATH 1010 - Calculus 1
  • MATH 1020 - Calculus 2
  • MATH 2400 - Introduction to Differential Equations
  • MATH 2010 - Multivariable Calculus & Matrix Algebra
Basic
Core Engineering Credits
  • ENGR 1200 - Engineering Graphics & CAD
  • ENGR 2350 - Embedded Control
  • ENGR 2050 - Introduction to Engineering Design
  • ENGR 4010 - Professional Development 3
Core ECSE Credits
  • ECSE 1010– Introduction to ECSE
  • ECSE 2610 – Computer Components and Operations
  • ECSE 2660 – Computer Architecture, Networks, and Operating Systems
  • ECSE 2010 – Electric Circuits
  • ECSE 2410 – Signals & Systems
  • ECSE 2500 – Engineering Probability
  • ECSE 2900 – ECSE Enrichment Seminar
  • CSCI-4430 – Programming Languages
  • CSCI 2600 – Principles of Software
  • CSCI 4210 – Operating Systems
  • ECSE 4900 – Multidisciplinary Capstone
Core
Artificial Intelligence and Data
ECSE Elective Credits
Theory and Algorithms
ECSE Elective Credits
Vision, Graphics, Robotics, and Games
ECSE Elective Credits
Systems and Software
ECSE Elective Credits
Restricted or Free Elective Credits
Concentration Areas