MS Concentrations
Students in the electrical engineering M.S. program often choose to use some of their electives to focus on a particular field. Students may pick one of a number of optional, formal concentration templates or design their own M.S. program in consultation with an adviser. These concentrations are not degree requirements. They represent suggestions from the faculty as to how one might fill one’s programs so as to focus on a particular area of interest. Students may wish to follow these suggestions, but they need not. The degree requirements are quite flexible and are listed in the Master of Science Degree section, above. All students, whether following a formal concentration template or not, are expected to include breadth in their program. Not all of the elective courses listed here are offered every year.
Concentration in DataDriven Analysis and Computation (Updated for Spring 2017)
Advisers: Dimitris Anastassiou, ShihFu Chang, Predrag Jelenkovic, Zoran Kostic, Aurel A. Lazar, Nima Mesgarani, John Paisley, John Wright, Xiaofan (Fred) Jiang
 Satisfy M.S. degree requirements.

Take at least two courses from:
 ECBM E4040: Neural networks and deep learning;
 EECS E4764: Internet of things – intelligent and connected systems;
 ELEN E4810: Digital Signal Processing
 ELEN E4903: Topic: Machine learning (or equivalent);
 EEOR E6616: Convex optimization;
 EECS E6893: Topic: Big data analytics

Take at least one course from:
 ECBM E6040: Neural networks and deep learning research;
 EECS E6720: Bayesian models for machine learning;
 EECS E6765: Internet of things  systems and physical data analytics;
 EECS E6895: Topic: Advanced big data analytics

Take a second course from #3, or one course from:
 ECBM E4060: Introduction to Genomic Information Science and Technology
 ECBM E6070: Topics in Neuroscience and Deep Learning
 ELEN E6690: Topics in datadriven analysis and computation
 ELEN E6886: Sparse representation and highdimensional geometry
 ELEN E9601: Seminar in datadriven analysis and computation
Concentration in Networking (Starting in Fall 2018)
Advisers: Professors Predrag Jelenkovic, Javad Ghaderi, Ethan KatzBassett, Debasis
Mitra, Gil Zussman, Xiaofan (Fred) Jiang
 Satisfy M.S. degree requirements.

One basic networking course from the following:
 ELEN E6761: Computer communication networks I
 CSEE W4119: Computer networks

One basic systems or analytical course from the following:

Systems courses:
 CSEE E4140: Networking laboratory
 COMS 4113: Distributed Systems
 COMS W4118: Operating systems I

Analytical courses:
 ELEN E6772: Topic: Network Algorithms
 ELEN E6950: Wireless and mobile networking
 ICSEE 6180: Modeling and Performance Evaluation

Systems courses:

Three courses from the following list (but a course cannot be used to fulfill both this requirement and any of the above requirements).
 ELEN E6488 Optical interconnects and interconnection networks
 ELEN E6761: Computer communication networks I
 ELEN E6767: Internet Econ, Eng & Society
 ELEN E6770: Topic: Next Gen networks
 ELEN E6772: Topic: Network Algorithms
 ELEN E6775: Topic: Computer Networks: A Systems Approach
 ELEN E6776: Topic: content distribution networks.
 ELEN E6950: Wireless and mobile networking I
 EEOR E4650: Convex optimization for EE
 EEOR E6616: Convex optimization
 CSEE E4140: Networking laboratory
 CSEE E4951: Wireless and mobile networks and systems.
 CSEE 6180: Modeling and Performance Evaluation
 COMS W4180: Network security
 COMS 4995: Internet Technology, Economics and Policy
 COMS 6181: Advanced Internet Services
 COMS E6998: Cloud Computing and Big Data
 IEOR E6704: Queueing theory
 IEOR E4106: Stochastic models
 With adviser approval, other relevant advanced topic courses on networking topics from ELEN E677*, COMS 4995, COMS E6998, or other course numbers may be used to fulfill this requirement.
 At least two of the four courses used to fulfill requirements 3 and 4 must be 6000level ELEN, EECS, CSEE, or EEOR courses.
Concentration in Wireless and Mobile Communications
Advisers: Professors Gil Zussman, Predrag Jelenkovic, Xiaodong Wang
 Satisfy M.S. degree requirements.

One basic circuits course such as:
 ELEN E4312: Analog electric circuits;
 ELEN E4314: Communication circuits;
 ELEN E6314: Advanced communication circuits;
 ELEN E6312: Advanced analog ICs.

Two communications or networking courses such as:
 CSEE W4119: Computer networks;
 ELEN E4702: Digital communications;
 ELEN E4703: Wireless communications;
 ELEN E6711: Stochastic signals and noise;
 ELEN E4810: Digital signal processing;
 ELEN E6950: Wireless and mobile networking, I;
 ELEN E6951: Wireless and mobile networking, II;
 ELEN E6761: Computer communication networks, I;
 ELEN E6712: Communication theory;
 ELEN E6713: Topics in communications;
 ELEN E6717: Information theory;
 ELEN E677x: Topics in telecommunication networks.
 At least two additional approved courses in wireless communications or a related area.
Concentration in Integrated Circuits and Systems
Advisers: Professors Peter Kinget, Harish Krishnaswamy, Mingoo Seok, Kenneth Shepard, Yannis Tsividis, Charles Zukowski
 Satisfy M.S. degree requirements.
 One digital course from: EECS E4321: Digital VLSI circuits or EECS E6321: Advanced digital electronic circuits.

One analog course from:
 ELEN E4312: Analog electronic circuits;
 ELEN E6312: Advanced analog integrated circuits;
 ELEN E6316: Analog circuits and systems in VLSI;
 ELEN E4314: Communication circuits;
 ELEN E6314: Advanced communication circuits;
 ELEN E6320: Millimeterwave IC design.

Two additional courses such as:
 Other courses from 2. and 3.;
 ELEN E6350: VLSI design laboratory;
 ELEN E6304: Topics in electronic circuits;
 ELEN E6318: Microwave circuit design;
 ELEN E9303: Seminar in electronic circuits.
 At least one additional approved course in integrated circuits and systems or a related area.
Concentration in Smart Electric Energy
(Starting in Fall 2018)
Advisers: M. Preindl, X. Jiang, G. Zussman, K. Shepard, Xiaodong Wang
 Satisfy M.S. degree requirements

Take at least two [power conversion or power systems] courses from:
 ELEN E4361 Power Electronics
 ELEN E6902 Renewable Power Systems
 ELEN E6904 Motor Drive Systems
 ELEN E4511 Power systems analysis and control
 ELEN E4510 Solar energy and smart grid power systems

Take at least one [control or optimization] course from:
 EEME E4601 Digital control systems
 EEME E6601 Introduction to control theory
 EEME E6602 Modern control theory
 ELEN E6873 Detection and Estimation Theory
 EEOR E4650 Convex optimization for electrical engineering
 EEOR E6616 Convex optimization
 EECS E4764 IoT  Intelligent and Connected Systems
 CSEE W4840 Embedded Systems

Take at least one [nonelectric energy class] course from:
 MECE E4210 Energy infrastructure planning
 MECH E4320 Intro to combustion
 MECE E4211 Energy: sources and conversion
 MECE E4302 Advanced thermodynamics
 EAEE E4190 Photovoltaic systems engineering and sustainability
 EAEE E4257 Environmental data analysis and modeling
 EAEE E4301 Carbon storage
 EAEE E4302 Carbon capture
 EAEE E4304 Closing the carbon cycle

Take one of the following [energy policy or market] nontechnical elective courses (this course
will fill the quota of nontechnical courses of the MS Checklist 1 ): EAEE E4001 Industrial ecology of earth resources
 EAIA W4200 Alternative energy resources
 INAF U6057 Electricity Markets
 INAF U6072 Energy Systems Fundamentals
 SUMA K4135 Energy Analysis for Energy Efficiency
 INAF U6065 The Economics of Energy
 INAF U6061 Global Energy Policy
 INAF U6242 Energy Policy
 INAF U6135 Renewable Energy Markets and Policy
Concentration in Systems Biology and Neuroengineering (Updated for 2017)
Advisers: Professors Dimitris Anastassiou, Christine Fleming, Pedrag Jelenkovic, Aurel A. Lazar, Nima Mesgarani, Kenneth Shepard, Xiaodong Wang
 Satisfy M.S. degree requirements.
 Take both ECBM E4060: Introduction to genomic information science and technology and BMEB W4020: Computational neuroscience: circuits in the brain

Take at least one course from:
 BMEE E4030: Neural control engineering;
 ECBM E4040: Neural Networks and deep learning;
 ECBM E4090: Brain computer interfaces (BCI) laboratory;
 CBMF W4761: Computational genomics;
 ELEN E6010: Systems biology: Design Principles for Biological Circuits;
 EEBM E6020: Methods in computational neuroscience;
 BMEE E6030: Neural modeling and neuroengineering;

Take at least one course from:
 ECBM E6040: Neural networks and deep learning research;
 ECBM E607x: Topics in neuroscience and deep learning;
 ELEN E608x: Topics in systems biology;
 EEBM E609x: Topics in computational neuroscience and neuroengineering;
 ELEN E6261: Computational methods of circuit analysis;
 ELEN E6717: Information theory;
 ELEN E6860: Advanced digital signal processing
Concentration in Lightwave (Photonics) Engineering
Advisers: Professors Keren Bergman, Ioannis (John) Kymissis
 Satisfy M.S. degree requirements.
 Take both ELEN E4411: Fundamentals of photonics and ELEN E6412: Lightware devices (or an E&M course, such as APPH E4300: Applied electrodynamics or PHYS GR6092: Electromagnetic theory).

One more device/circuits/photonics course such as:
 ELEN E6413: Lightwave systems;
 ELEN E6414: Photonic integrated circuits;
 ELEN E4314: Communication circuits;
 ELEN E4488: Optical systems;
 ELEN E6488: Optical interconnects and interconnection networks;
 ELEN E4193: Modern display science and technology.

At least two additional approved courses in photonics or a related area. Options also include courses outside EE such as:
 APPH E4090: Nanotechnology;
 APPH E4100: Quantum physics of matter;
 APPH E4110: Modern optics;
 CHAP E4120: Statistical mechanics;
 APPH E4112: Laser physics;
 APPH E4130: Physics of solar energy;
 APPH E6081: Solid state physics, I;
 APPH E6082: Solid state physics, II;
 APPH E6091: Magnetism and magnetic materials;
 APPH E6110: Laser interactions with matter;
 MSAE E4202: Thermodynamics and reactions in solids;
 MSAE E4206: Electronic and magnetic properties of solids;
 MSAE E4207: Lattice vibrations and crystal defects;
 MSAE E6120: Grain boundaries and interfaces;
 MSAE E6220: Crystal physics;
 MSAE E6229: Energy and particle beam processing of materials;
 MSAE E6225: Techniques in Xray and neutron diffraction.
Concentration in Microelectronic Devices
Advisers: Professors Wen Wang, Ioannis (John) Kymissis
 Satisfy M.S. degree requirements.
 One basic course such as: ELEN E4301: Introduction to semiconductor devices or ELEN E4411: Fundamentals of photonics.

One advanced course such as:
 ELEN E4193: Modern display science and technology;
 ELEN E4944: Principles of device microfabrication;
 ELEN E4503: Sensors, actuators, and electromechanical systems;
 ELEN E6151: Surface physics and analysis of electronic materials;
 ELEN E6331: Principles of semiconductor physics, I;
 ELEN E6332: Principles of semiconductor physics, II;
 ELEN E6333: Semiconductor device physics;
 ELEN E6945: Nanoscale fabrication and devices.

At least two other approved courses in devices or a related area. Options also include courses outside EE such as:
 APPH E4090: Nanotechnology;
 APPH E4100: Quantum physics of matter;
 APPH E4110: Modern optics;
 CHAP E4120: Statistical mechanics;
 APPH E4112: Laser physics;
 APPH E4130: Physics of solar energy;
 APPH E6081: Solid state physics, I;
 APPH E6082: Solid state physics, II;
 APPH E6091: Magnetism and magnetic materials;
 APPH E6110: Laser interactions with matter;
 MSAE E4202: Thermodynamics and reactions in solids;
 MSAE E4206: Electronic and magnetic properties of solids;
 MSAE E4207: Lattice vibrations and crystal defects;
 MSAE E6120: Grain boundaries and interfaces;
 MSAE E6220: Crystal physics;
 MSAE E6229: Energy and particle beam processing of materials;
 MSAE E6225: Techniques in Xray and neutron diffraction.