Build
Apply what you learn by building prototypes that can lead to entrepreneurial viability with real users.
Master in Electrical and Computer Engineering
Pursue what interests you most with opportunities to prototype new hardware and improve advanced algorithms in this flexible engineering master’s degree. Combine innovative laboratory projects with computational principles and rigorous theoretical understanding during your Ivy League engineering degree. Through cross-disciplinary teamwork and collaborations with industry leaders, you’ll also receive exceptional opportunities to explore your startup ideas and build your professional network within New York’s tech community.
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Explore
Study across programs and disciplines to work on what interests you most with our customizable curriculum.
Challenge Yourself
Learn from the best with top faculty mentors. Then present your work to outside influential experts from New York’s tech scene.
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
Featured course
Signal and Data Processing
Credits 3
This core ECE course covers the basics of signal processing and data analysis. The first half of the course covers the fundamentals of signals and systems, including the discrete Fourier transform, transfer functions, adaptive filtering and applications in noise cancellation and communication systems. The second half covers the basics of probabilistic models, stochastic simulation Markov processes and Bayesian inference. Finally,...
Daniel D. Lee
Tisch University Professor of Electrical and Computer Engineering
Daniel Dongyuel Lee is a Professor at Cornell Tech and in the Electrical and Computer Engineering Department at Cornell University.
Research focus: Electrical and Computer Engineering
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.
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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.
Learn & Work in NYC
With its central location in New York City, Cornell Tech students benefit from fluid interactions with some of the foremost tech companies in the country including Google, Amazon, Facebook, Qualcomm, Verizon, The New York Times, and others.
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.
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At the Intersection of Art and Technology
Jacobs Fellow C Richard Johnson combines technology with art history.