# Undergraduate Curriculum

Designed to Inspire

This department balances technical rigor and curricular flexibility to provide a world-class engineering education. We want to inspire our students, and we want our students to inspire their peers.

#### What to Expect

The program begins in the sophomore year with a set of unifying foundation courses (information, circuits, devices and digital logic) that cover the breadth of the discipline and prepare students for advanced electives.

Students build on this foundation with the introduction of systems and their design, followed by a set of departmental electives in a concentration area. Within these concentrations, students see the interaction of theory and application and have a choice on which aspects to focus.

Students tailor their areas of concentration in consultation with a faculty adviser. Possible areas of concentration include Data and Information, Security and Privacy, Computer Systems, Energy and Environment, Quantum Computing and Applied Physics, to name only a few. For a complete list, download the undergraduate student handbook.

Many students also pursue an interdisciplinary certificate from one of the many programs offered at Princeton. This is the equivalent of a "minor", and is optional, not required.

Graduates from this department earn a Bachelor of Science in Engineering (BSE).

#### Where to Start

To be adequately prepared for the first-year engineering program at Princeton, students should take high-school mathematics through calculus (if possible), as well as high-school physics and chemistry. Many students enter Princeton with advanced placement in one or more of these subjects, but this is not a requirement for admission or for success in the program.

Thirty-six courses are required for the four-year program. Students granted advanced standing participate in a three-year program and must complete 28 courses for the BSE (this is rare).

Questions may be directed to the Undergraduate Program Coordinator or the faculty Department Representative.

## Undergraduate Contacts

## Jean Bausmith

- Undergraduate Program Coordinator

## James Sturm

- Stephen R. Forrest Professor of Electrical Engineering
- Director of Undergraduate Studies

### Concentration

Each ELE major chooses an area of concentration within the field, which gives coherent shape to your classes over time. We have 10 suggested areas with prescribed course lists.

- Circuits and Systems
Required:

ELE 304 Electronic Circuits: Devices to ICs (S)

Two courses from:

ELE 341 Solid State Devices (F)

COS/ELE 375 Computer Architecture and Organization (S)

ELE 382 Statistical Signal Processing (not offered 19-20)

ELE 462 Design of VLSI (F)

ELE 464 Embedded Computing (S)

ELE 472 Secure Computers (S)

ELE 475 Computer Architecture (F)

ELE 481 Power Electronics (F)

ELE 482 Digital Signal Processing (F)- Data and Information
ORF 309* Probability and Stochastic Systems (F & S) is required, plus two or three courses from this list.

ELE 364** Machine Learning for Predictive Data Analysis (F)

ELE 381 Networks: Friends, Money and Bytes (S)

ELE 382 Statistical Signal Processing (not offered 19-20)

ELE 482 Digital Signal Processing (F)

ELE 486 Transmission and Compression of Information (not offered 19-20)

ELE 435** Machine Learning and Pattern Recognition (F)

COS 324** Introduction to Machine Learning (F)

COS 402** Artificial Intelligence

COS 424** Fundamentals of Machine Learning

COS 429 Computer Vision (F)

COS/ELE 432 Information Security (F & S)

ORF 350 Analysis of Big Data (S)

ORF 363 Computing and Optimization for the Physical and Social Sciences (also COS 323) (F)* ORF 309 can fulfill either the 300-level math requirement, or serve as one of the 3 Data and Information courses, but not both.

- If ORF 309 is taken to fulfill the 300-level math requirement, take at least 2 ELE courses from this list, plus any one other course from this list.
- If ORF 309 is taken as one of the 3 D&I courses (implying another 300-level math course) take any 2 ELE courses from the list.

** Only one Machine Learning course may be applied to this concentration.

- Computer Systems
Required:

COS/ELE 375 Computer Architecture and Organization (S)

Two courses from:

ELE 462 Design of VLSI (F)

ELE 464 Embedded Computing (S)

ELE 470 Smartphone Security and Architecture (not offered 19-20)

ELE 472 Secure Computers (S)

ELE 475 Computer Architecture (F)

COS 318 Operating Systems (F)

COS 320 Compiling Techniques (S)

COS 461 Computer Networks (S)- Robotics and Cyberphysical Systems
Three courses from:

ELE 304 Electronic Circuits: Devices to ICs (S)

COS/ELE 375 Computer Architecture and Organization (S)

ELE 364** Machine Learning for Predictive Data Analysis (F)

ELE 435** Machine Learning and Pattern Recognition (F)

ELE 464 Embedded Computing (S)

ELE 481 Power Electronics (F)

COS 324** Introduction to Machine Learning (F)

COS 402** Artificial Intelligence

COS 429 Computer Vision (F)

MAE 345 Robotics and Intelligent Systems (F)

MAE 433 Automatic Control Systems (F)****Only one Machine Learning course may be used for this concentration.

- Quantum Information and Applied Physics
Required:

ELE 342** Principles of Quantum Engineering (S)

Two courses from:

ELE 396 Introduction to Quantum Computing (F)

ELE 441 Solid-State Physics I (F)

ELE 453 Optical Electronics (F)

ELE 456 Quantum Optics (S)

ELE 568 Implementations of Quantum Information (F)**PHY 208 and 305 can be taken in lieu of ELE 342, but are counted as one course for the concentration requirement.

- Security and Privacy
Required:

COS/ELE 432 Information Security (F & S)

Two courses from:

COS/ELE 375 Computer Architecture and Organization (S)

ELE 364** Machine Learning for Predictive Data Analysis (F)

ELE 435** Machine Learning and Pattern Recognition (F)

ELE 464 Embedded Computing (S)

ELE 470 Smartphone Security & Architecture (not offered 19-20)

ELE 472 Secure Computers (S)

COS 324** Introduction to Machine Learning (F)

COS 402** Artificial Intelligence

COS 424** Fundamentals of Machine Learning

COS 433 Cryptography (S)

COS 461 Computer Networks (S)**Only one Machine Learning course may be applied towards this concentration.

- Electronic Devices and Materials
Required:

ELE 308 Electronic and Photonic Devices (F)**

ELE 341 Solid State Devices (F)Two courses from:

ELE 304* Electronic Circuits: Devices to ICs (S)

ELE 342 Principles of Quantum Engineering (S)

ELE 431 Solar Energy Conversion (F)

ELE 441 Solid-State Physics I (F)

ELE 481* Power Electronics (F)

ELE 557 Solar Cells (S 20)

MAE 324 Structure and Properties of Materials (F)

MAE 424Energy Storage Systems (S)

MSE 301 Materials Science and Engineering (S)

MSE 302 Laboratory Techniques in Materials Science (F)

MSE 505 Characterization of Materials (S)* Only one circuits (304 or 481) course may be applied towards this concentration.

**ELE308 does not count if taken as part of the Foundation Requirement- Biomedical Engineering
Three courses from:

ELE 304 Electronic Circuits: Devices to ICs (S)

ELE 452 Biomedical Imaging (S)

ELE 480 fMRI Decoding: Reading Minds (not offered 19-20)

COS 429 Computer Vision (F)

COS 455 Genomics & Computational Molecular Biology

MAE 344 Biomechanics and Biomaterials (S)

NEU 427 Systems Neuroscience (S)

NEU 437 Computational Neuroscience (S)- Optics and Photonics
Required:

ELE 351 Foundations of Modern Optics (F)

Two courses from:

ELE 342 Principles of Quantum Engineering (S)

ELE 452 Biomedical Imaging (S)

ELE 453 Optical Electronics (F)

ELE 458 Photonics and Light Wave Communications (F)

ELE 456 Quantum Optics (S)

MAE 521 Optics and Lasers (F)- Energy and the Environment
Three courses from:

ELE 341 Solid State Devices (F)

ELE 431 Solar Energy Conversion (F)

ELE 481 Power Electronics (F)

ELE 557 Solar Cells: Physics, Materials, and Technology (S)

MAE 424 Energy Storage Systems