Control and Communications

We live in a world where data is increasingly playing a central role. If you ask your phone a question, the voice data is wirelessly communicated to the cloud, where its meaning is inferred and the relevant answers are retrieved using machine intelligence through an analysis of high-dimensional data and a discovery of structure, with the information classified using machine learning and network science. The MS-EE’s curriculum in digital communications helps lay the foundation for this wireless world. These courses prepare you for a career in reliable and high-speed data communications and data learning. Past students have joined companies such as Qualcomm and Google that are at the vanguard in communications and data science.

Control techniques are used whenever a quantity (like speed, temperature or force, for instance) must be made to behave in some desirable way over time. In the modern world, the rapid evolution of technological demands imposes extremely challenging and widely varying control problems — problems we want to help you prepare to solve. The MS-EE controls curriculum explores topics such as developing controllers for aircraft, spacecraft, information storage systems, human-machine interfaces, manufacturing processes and power systems.

Digital Communications: Foundations of Theory and Practice Specialization

Instructors: Eugene Liu and Peter Mathys

Individual courses:

  • ECEA 5200 Communication System Overview and Basic Math Preparation (0.6 credits)
  • ECEA 5201 Introduction to Error Control Coding (0.8 credits)
  • ECEA 5202 Linear Modulation and Optimal Demodulation (0.8 credits)
  • ECEA 5203 I/Q Up/Down Converter and Wireless Channels (0.8 credits)

Channel Estimation and Equalization Course

Instructors: Eugene Liu and Peter Mathys

  • ECEA 5204 Channel Estimation and Equalization (1 credit)

Control Systems Analysis Specialization

Instructor: Lucy Pao

Individual courses:

  • ECEA 5800 Modeling of Dynamic Systems and Basic Feedback Control Concepts (1 credit)
  • ECEA 5801 Analysis and Design of Feedback Control Systems Using Frequency Domain (1 credit)
  • ECEA 5802 Analysis and Design of Feedback Control Systems Using State-Space Methods (1 credit)

Sampled Data and Digital Control Specialization

Instructor: Lucy Pao

  • ECEA 5825-5828 Provides an analysis and synthesis of discrete-time systems. Studies sampling theorem and sampling process characterization, z-transform theory and z-transfer function, and stability theory. Involves data converters (A/D and D/A), dead-beat design, and digital controller design.

Electromagnetics, RF, Microwaves and Remote Sensing

The electromagnetics, RF, microwaves and remote sensing curriculum in the MS-EE invites you to explore an exciting electrical engineering field that engages topics such as active circuits and antennas for communications and radar, theoretical and numerical techniques for analysis of high-frequency circuits and antennas, RF photonics, artificial electromagnetic materials, and electromagnetic remote sensing.

Antennas Specialization

Instructor: Dejan Filipovic

Individual courses:

  • ECEA 5420 Antenna Alphabet (1 credit)
  • ECEA 5421 Wire Antennas (1 credit)
  • ECEA 5422 Microstrip, Spiral, Aperture Antennas, and Arrays (1 credit)

Stochastic Environmental Signal Processing Specialization

Instructor: Al Gasiewski

Individual courses:

  • ECEA 5445 Model-Based Parameter and Spectral Estimation (1 credit)
  • ECEA 5446 Statistical Estimation and Filtering (1 credit)
  • ECEA 5447 Statistical Detection and Advanced Applications (1 credit)

Computer Engineering

As computers continue to get smaller, cheaper and more ubiquitous, the software-hardware boundary is becoming more important to understand: High-performance network cards now write packets directly to user-space memory; secure enclaves and bootloaders must protect themselves from malicious or vulnerable operating systems; and increasingly complex systems must remain robust under faulty or buggy hardware and firmware. Computer engineering encompasses a wide range of topics surrounding this interaction between hardware and software. Computer engineers of the future will be versatile full-stack developers, comfortable with understanding the technical depths of software development while also possessing a wide knowledge of the underlying hardware implementations. The MS-EE curriculum in computer engineering emphasizes computer-aided verification and synthesis.

Computer Aided Verification Specialization

Instructors: Fabio Somenzi, Pavol Cerny, Sriram Sankaranarayanan

Individual courses:

  • ECEA 5330 Foundations of Computer Aided Verification (0.6 credits)
  • ECEA 5331 Decision Procedures and Hardware Model Checking (0.8 credits)
  • ECEA 5332 Software Verification (0.8 credits)
  • ECEA 5333 Verification of Cyberphysical Systems (0.8 credits)