Master of Engineering in Computer Science
Computer Science at Cornell Tech
Learn, Launch, Lead
Build & Test
Learn & Leverage
In one semester, I went from starting research to speaking at the biggest Smart Contracts conference in London. That makes me feel really confident about taking what I’ve learned here out into the field.”
About the Master of Engineering in Computer Science Degree
Designed with input from leading tech industry advisors, the Master of Engineering in Computer Science at Cornell Tech offers a flexible course of study with rigorous technical courses in both fundamental and advanced emerging areas of computing. Your academic coursework will give you exceptional training in engineering software, systems, platforms, and products for complex business challenges and human needs.
These courses focus on preparing you for innovation within major tech companies or entrepreneurship within startup ventures. In cross-disciplinary teams, you’ll work with business, law, and other Cornell Tech students to create your own startup as well as develop usable solutions for real corporations. In the process, you’ll develop the business savvy and communication skills—as well as peerless technical know-how—that have made previous graduates prime recruiting targets of companies like Google, Facebook, and numerous startups.
Technical Topics Covered
Algorithms and Data Structures for Applications
Applied Machine Learning
Blockchains & Cryptocurrencies
Data Mining & Signal Processing
Human-Computer Interaction (HCI)
Natural Language Processing (NLP)
Networks & Markets
Studio Topics Covered
Law for Non-Lawyers
Leadership for Digital Transformation
Startup Funding & Pitching
Algorithms and Data Structures for Applications
Bill & Melinda Gates Foundation
Vitaly Shmatikov is a Professor at Cornell Tech and in the Computer Science Department at Cornell University. His research areas are security and privacy. He received the PET Award for Outstanding Research in Privacy Enhancing Technologies twice, in 2008 and 2014. Vitaly’s research group won the Best Practical Paper or Best Student Paper Awards at the 2012, 2013 and 2014 IEEE Symposiums on Security and Privacy (“Oakland”), as well as the NYU-Poly AT&T Best Applied Security Paper Award, NDSS Best Student Paper Award, and the CCS Test-of-Time Award. Vitaly holds a PP-ASEL/ASES-IA pilot certificate, drinks 10 cups of coffee a day, and is known as a taco connoisseur.
Yoav Artzi is an Assistant Professor at Cornell Tech and in the Computer Science Department at Cornell University. Professor Artzi’s Language in Context group studies representations and learning algorithms for language understanding in context. Language understanding is a complex challenge that requires reasoning about linguistic meaning and its use in context, for example to resolve references to objects in the environment when instructing a robotic systems. The main focus of the group is developing methods for computer systems to learn to understand natural language through interaction with users and experimenting in the world. The goal is to create natural language systems that continuously learn, improve their language understanding, and acquire new language uses.
Noah Snavely is an Associate Professor at Cornell Tech and in the Computer Science Department at Cornell University. Professor Noah Snavely’s group explores the use of massive, unstructured collections of online photos to understand our world. In the aggregate, the trillions of photos uploaded to the web each year reveal a rich portrait of the world – the cities and environments that surround us, and the patterns of activity that make up our everyday lives. Snavely’s research group develops new technology for tapping these unorganized image collections to model the world in 3D, to analyze images for computer graphics applications, and to detect trends in social media photos.
Rafael Pass is a Professor at Cornell Tech and in the Computer Science Department at Cornell University. His research focuses on cryptography and game theory and their interplay with computational complexity. He is a recipient of the NSF Career Award, the AFOSR Young Investigator Award, and the Google Faculty Award. He was named an Alfred P Sloan Fellow, a Microsoft Faculty Fellow, and a Wallenberg Academy Fellow.
Computer Science Research at Cornell Tech
Security & Privacy
Cornell Tech has one of the world’s leading academic research groups specializing in security, privacy and cryptography. Its faculty is known for their for their highly cited and award-winning research results as well as their influence on various industry, non-profit, and government practices.
Data & Modeling
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 support in a variety of areas including logistics, retail, marketing, defense, biotech, finance, and healthcare.
Human-Computer Interaction (HCI) & Social Computing
Several faculty at Cornell Tech study the design, implementation, impact, and broader implications of computing technologies in everyday human activities. Particular areas of research interest include accessibility, educational technology, Computer Science education, Information and Communication Technologies and Development (ICTD), Computer-supported Cooperative Work (CSCW) and social computing.
Companies Hiring Recent Graduates
Cornell Tech offers best-in-class career management services to set you up for success after graduation. 90% of recent job seekers (versus startup founders) from the Computer Science program accepted Software Developer roles at mature companies or startups, while others accepted roles such as Product Manager, Program Manager, Data Analyst or Data Scientist.
Intellectual Property Agreements
The Cornell Standard Project (CSP) agreements make it easy for students and organizations to collaborate in a manner that will enable the intellectual property created in that collaboration to be used by the students outside the collaboration, for example, in a commercial context after they graduate from school.
Who Should Apply?
The Master of Engineering in Computer Science welcomes candidates who have an academic background in computer science or a related technical field, a strong entrepreneurial streak, and a passion to lead in the tech industry. If you do not have a technical academic background, your application should demonstrate coursework in software engineering and linear algebra and a working knowledge of data structures and algorithms.
I set out to start my own software company and I’m doing just that.”
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