Master of Engineering in Electrical and Computer Engineering
Want to learn more?
Request InfoElectrical and Computer Engineering at Cornell Tech
Develop & Apply Your Expertise
Build
Explore
Challenge Yourself
In most traditional engineering degrees, there is delayed satisfaction. First, you have to learn all the mathematics and then you’ll see the applications at the end. In the ECE program, for every advanced, sophisticated analytical tool we cover, we also cover highly relevant industrial applications almost at the same time. That way, you immediately see the relevance of what you’re learning.”
Engineering in 360°
Fundamental Courses
Learn state-of-the-art topics in signal processing, data science, machine learning, and feedback control/reinforcement learning algorithms—as well as the most advanced mathematical methods to improve them.
Physical Computing Courses
Prototype working hardware components via lab work in embedded systems, fabrication, robotics, computer vision, laser cutting, and 3D printing.
Entrepreneurship Courses
Practice entrepreneurship, product design, startup management and other skills in cross-disciplinary teams with MBA, law, and engineering students in this required component of all Cornell Tech programs.
Computational Modeling Topics Covered
Adaptive Control & Reinforcement Learning
Applied Machine Learning
Big Data & Social Media
Decision-Support Systems
High Dimensional Signal Processing
Markov Decision Processes
Natural Language Processing (NLP)
Stochastic Simulation
Physical Computing Topics Covered
Autonomous Systems & Robotics
Computer Vision
Embedded Systems
Human-Computer Interaction (HCI)
User-Centered Design and Prototyping
Studio Topics Covered
Challenges of Entrepreneurship
Global Leadership & Multicultural Awareness
Intellectual Property
Law for Non-Lawyers
Leadership for Digital Transformation
Marketing, Sales & Distribution
Product Management
Startup Funding & Pitching
Certificate Programs in Electrical and Computer Engineering
ECE M.Eng. AI Systems Certificate
The AI Systems certificate for ECE M.Eng. students bridges the gap between AI algorithms and physical systems through a “full-stack” ECE curriculum that spans circuit/architecture, memory, physical AI, robotics, optimization, and sustainable/efficient system and infrastructure design. By integrating a selection of ECE courses in AI and its applications to critical cyber-physical systems, the program grounds technical principles in the design and implementation of complex, real-world intelligent systems.
Certificates are designed to demonstrate specialized expertise in your program and are provided by Cornell Tech following graduation.
Please note: Certificates are not part of the official university degree and will not appear on your diploma or transcript. New electives may be added to the course list. While elective courses are offered based on instructor availability, and the availability of spots in some courses may be more limited than in others, we believe most interested students will be able to complete this certificate; some flexibility may be required.
Requirements:
Choose at least three of the following, including at least one course marked with (*). Other courses will need permission from the Program Director:
- ECE 5242 Intelligent Autonomous Systems (*)
- ECE 5545 Machine Learning Hardware and Systems (*)
- ECE 5240 Robot Perception
- ECE 5290 Distributed Optimization for Machine Learning and AI
- ECE 5415 Digital Signal Processing and Learning
- ECE 5XXX Architecting Sustainable AI Infrastructure (new)
- ECE 5XXX Machine Learning for Dynamical Systems and Control (new)
- ECE 6760 Memory Technologies and Memory-Centric AI Computing
- ECE 5260 Graph-based Data Science and AI Models for Networked Systems
In addition, choose one of the courses below:
- LAW 6146 AI Law and Policy
- CS 5434 Trustworthy AI
- CS 5382/INFO 5390 Fairness in Machine Learning
Featured course
Signal and Data Processing
Credits 3
Daniel D. Lee
Tisch University Professor
Daniel Dongyuel Lee is a Professor at Cornell Tech and in the Electrical and Computer Engineering Department at Cornell University.
Areas of Research:
Artificial Intelligence and Robotics
Academic Degrees:
Ph.D., Massachusetts Institute of Technology, 1995
C. Richard Johnson
Professor, Fellow in Computational Arts and Humanities
C. Richard Johnson Jr. is the Fellow in Computational Arts and Humanities at the Jacobs Technion-Cornell Institute, as well as the Geoffrey S. M. Hedrick Senior Professor of Engineering, Electrical and Computer Engineering, Cornell University. He received a Ph.D. in Electrical Engineering from Stanford University in 1977 along with a PhD minor in Art History. He has been on the Cornell University faculty since 1981 and joined Cornell Tech in 2016.
Biosensors for Disease Detection
Vikram Krishnamurthy collaborated with Surgical Diagnostics to build and model devices out of artificial cell membranes. The ion channel biosensor, for example, is a fully functioning nanomachine that can detect ultra-low concentrations of target molecules such as HIV, Influenza viruses, and toxins.
Data & Modeling Research
The Data & Modeling Research Group at Cornell Tech includes faculty with backgrounds in computer science, electrical engineering, business, and operations research. Their research focuses on developing models for decision-making problems in a variety of areas including logistics, retail, marketing, defense, biotech, finance, and healthcare.
1 OF
Career Outcomes
Cornell Tech offers best-in-class career management services to set you up for success after graduation. Learn about our high placement rates and recent hires.
Diversity & Inclusion
Cornell Tech was founded to advance technology as a means to a better quality of life for all communities in New York City, across the nation, and around the world. Our best work results in ethical, inclusive, accessible technology for all users, especially the underserved and underrepresented. Vital to that mission is building a diverse, equitable, and inclusive community of students, faculty, and staff. We seek to build things with — not just for — real people and believe in the power of participation and representation.
The Cornell Tech curriculum has been designed to address the needs of students seeking opportunities in exciting new areas such as AI, machine learning, and robotics.”
Who Should Apply?
We welcome applications from students who have a passion for applied technology–especially robotics and machine learning–and an entrepreneurial spirit. You should also have an academic background in electrical and computer engineering, mechanical engineering, computer science, physics, applied mathematics, or a related technical field. That background should include coursework in signals and systems, linear algebra, scientific programming, probability and statistics.
Unlike the Ithaca-based ECE Master’s program, Cornell Tech does not offer a third-semester option for their ECE Master’s students.
Love Where You Live & Learn
Check out the groundbreaking Cornell Tech campus with an virtual or in-person visit.