Jacobs Technion-Cornell Dual Master of Science Degrees with a Concentration in Health Tech mix advanced technical coursework in computer science and engineering with hands-on project work in partnership with leading entities in the health sector. You’ll emerge from the program with the full skill set and unique insights that define leaders who innovate on the cutting edge of health technology.
You will also complete Studio courses—an essential component of every Cornell Tech program. 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 students from other Cornell Tech master’s programs to create your own startup as well as develop usable solutions for real corporations.
What Your Schedule Might Look Like
Fall Semester - Year 1
- Fall Semester - Year 1
- Spring Semester - Year 1
- Fall Semester - Year 2
- Spring Semester - Year 2
- Technical Credits 9
- Studio & Interdisciplinary Credits 6
- Semester total 15
- Technical Credits 9
- Studio & Interdisciplinary Credits 6
- Semester total 15
- Technical Credits 12
- Studio & Interdisciplinary Credits 5
- Semester total 17
- Technical Credits 9
- Studio & Interdisciplinary Credits 7
- Semester total 16
- Technical Credits
- Studio & Interdisciplinary Credits
- Semester total 0
An introduction to some fundamental algorithms and data structures used in current applications. Examples include cryptocurrencies (hashing, Merkle trees, proofs of work), AI (nearest neighbor methods, k-d trees, autoencoders), and VR/AR (gradient descent, least squares, line-drawing algorithms). Six lectures will be replaced by applied clinics taught in the evening. Programming assignments in Python or Java.
Learn and apply key concepts of modeling, analysis and validation from Machine Learning, Data Mining and Signal Processing to analyze and extract meaning from data. Implement algorithms and perform experiments on images, text, audio and mobile sensor measurements. Gain working knowledge of supervised and unsupervised techniques including classification, regression, clustering, feature selection, association rule mining, and dimensionality reduction.
Behavioral economics studies the effect of psychological, social, cognitive and emotional factors on humans decisions and behavior. This course will help students learn key concepts from behavioral economics and apply them in their daily lives, in the design of products, and in the research of human behavior. This course will explore the opportunities and challenges faced by researchers and practitioners when exploring the interplay between behavioral economics and technology.
There has been an explosion of big data in medicine and healthcare. There are four main sources of such big data – 1) administrative databases in healthcare such as electronic health records and health insurance claims, 2) biomedical imaging (e.g. MRI, CT‐Scan, X‐ray etc.) 3) sensors in smartphones, wearable and implantable devices and 4) genetics and genomics. It is difficult to navigate and critically assess the statistical methods and analytic tools that are needed to conduct analytics and research with such big biomedical data. This course will introduce the four above‐mentioned important sources of big data in medical studies, discuss the nuances and intricacies of how such data are generated and introduce tools to navigate such databases visualize and describe them. The aim of this course is to introduce students to the complexities of biomedical big data. A data scientist is typically removed from the data generating process and involved further downstream during the data analysis phase. However, a thorough and meaningful analysis of such data cannot be performed without an in‐depth understanding of how data was generated. Therefore, the students will learn about the nuances and intricacies of data generated in four typical sources of big data in medical studies, namely, 1) big administrative database for healthcare, 2) biomedical imaging, 3) genomics and 4) sensors and wearable devices.
Viewed variously as a niche currency for online criminals and a technological threat to the financial industry, Bitcoin has fueled mythmaking, financial speculation, and real technological innovation. We will study both Bitcoin and the technological landscape it has inspired and catalyzed. Topics will include: the mechanics of consensus algorithms, such as Proof of Work and Byzantine Consensus, and their role in blockchains and cryptocurrencies; cryptographic tools employed in cryptocurrencies, including digital signatures algorithm and zero-knowledge proofs; the evolution and mechanics of Bitcoin and its ecosystem; smart contracts; and special topics, such as trusted hardware in blockchain-based systems, smart contracts and real-world contract law, and cryptocurrencies and crime. Grading will be based on homework assignments and a final project.
Massive amounts of data are collected by many companies and organizations and the task of a data scientist is to extract actionable knowledge from the data – for scientific needs, to improve public health, to promote businesses, for social studies and for various other purposes. This course will focus on the practical aspects of the field and will attempt to provide a comprehensive set of tools for extracting knowledge from data.
Annual Class: required consecutive enrollment in fall (CTIV 5017 01) and in spring (CTIV 5017 03). Students must successfully complete both semesters of the course in order to receive credit.
This is a two‐part series that will provide a fundamental understanding of immunology. Immunology I will give a comprehensive overview of basic immunology beginning with innate immune responses followed by a study of the main aspects of acquired immunity. Important topics include the following: organization of lymphoid tissues and immune cell migration, cellular and molecular aspects of innate immunity, specific interactions of target cells and T cells that are regulated by the MHC molecule and peptide antigens on the target cell and the antigen specific T cell receptor; generation and molecular structure of B and T cell antigen receptors; signaling through immune receptors; the development of antigen specific T and B cells; and specific roles of some cytokines/lymphokines. The second part of the series is Immunology II, held in the Spring semester, which focuses on aspects of T and B effector cell generation, immune response generation and regulation in the context of infection, autoimmunity, tumor immunity, and transplant.
Human-Computer Interaction (HCI) and design theory and techniques. Methods for designing, prototyping, and evaluating user interfaces to computing applications. Basics of visual design, graphic design, and interaction design. Understanding human capabilities, interface technology, interface design methods, prototyping tools, and interface evaluation tools and techniques.
An in-depth introduction to computer vision. The goal of computer vision is to compute properties of our world-the 3D shape of an environment, the motion of objects, the names of people or things-through analysis of digital images or videos. The course covers a range of topics, including 3D reconstruction, image segmentation, object recognition, and vision algorithms fro the Internet, as well as key algorithmic, optimization, and machine learning techniques, such as graph cuts, non-linear least squares, and deep learning. This course emphasizes hands-on experience with computer vision, and several large programming projects.
This course constitutes an introduction to natural language processing (NLP), the goal of which is to enable computers to use human languages as input, output, or both. NLP is at the heart of many of today’s most exciting technological achievements, including machine translation, automatic conversational assistants and Internet search. Possible topics include summarization, machine translation, sentiment analysis and information extraction as well as methods for handling the underlying phenomena (e.g., syntactic analysis, word sense disambiguation, and discourse analysis).
This course covers algorithmic and computational tools for solving optimization problems with the goal of providing decision-support for business intelligence. We will cover the fundamentals of linear, integer and nonlinear optimization. We will emphasize optimization as a large-scale computational tool, and show how to link programming languages with optimization software to develop industrial-strength decision-support systems. We will demonstrate how to incorporate uncertainty into optimization problems. Throughout the course, we will cover a variety of modern applications, including pricing and marketing for e-commerce, ad auctions on the web, and on-line ride-sharing.
This course will give students a technical and social understanding of how and why security and privacy matter, help them think adversarially and impart how (and how not) to design systems and products. Less attention will be paid to specific skills such as hacking, writing secure code and security administration. Topics will include user authentication, cryptography, malware, behavioral economics in security, human factors in security, privacy and anonymity, side channels, decoys and deception and adversarial modeling. We will explore these concepts by studying real-world systems and attacks, including Bitcoin, Stuxnet, retailer breaches, implantable medical devices, and health apps — and we will consider future issues that may arise in personal genomics, virtual worlds, and autonomous vehicles.
The Specialization Project is your opportunity to explore, apply, deepen, and demonstrate your applied technical skills. Each small student team (2-4) will match with an advisor and project based on subject matter interests and anchored in the skills you develop in your technical courses. The Spec project is begun in the first Spring semester and completed in the second Fall semester.
Two of your semesters will be devoted to an in-depth specialization project. During this time, company advisors will work with you or your team once a week. This is the deepest form of engagement you and your participating external companies will have throughout your time at Cornell Tech. Your ultimate goal here is to create a high-tech paper presentation and demo to pitch to company stakeholders at your mentoring company.
Augmented and virtual reality technologies and applications are becoming increasingly popular. This course presents an introduction to this exciting area, with an emphasis on designing and developing virtual and augmented reality applications. The course will cover the history of the area, hardware technologies involved, interaction techniques, design guidelines, evaluation methods, and specific application areas. Students will be tasked with designing, developing, and evaluating their own augmented or virtual reality application as a course project.
Studio & Interdisciplinary Courses
Successfully innovating inside of a large company takes a new set of skills. In BigCo Studio, you will learn how to build products in a complex environment at scale and navigate business development, M&A, and other corporate activities to drive strategic initiatives within large companies. Working in teams, you’ll be matched with a C-suite or VP advisor from a real BigCo to research, prototype, and present a new product that helps the company achieve its mission.
This hands-on course will prepare you to be future innovators by teaching you Design Thinking, the human-centered design methodology pioneered by IDEO and Stanford d.school founder, David Kelley. You will work on a team with peers from other disciplines so as to experience the importance of “radical collaboration.” All teams will work on the same challenge, and you will be asked to design an innovative solution to this complex problem.
This is a 3‐credit, course designed for students, fellows, residents and faculty. Course objectives: Evaluate research questions critically; discuss core epidemiological concepts applied in clinical research, including bias and confounding; assess the appropriateness, strengths, and weaknesses of different study designs for answering a variety of clinical research questions; and demonstrate preference for evidence over authority in the evaluation of clinical research literature interventions.
This course is designed to give students hands on experience applying health tech tools and methods to real world clinical challenges. Students will work (individually or in pairs) with a clinical advisor to assess a particular clinical need for application of digital technology and based on that assessment students will develop a feasibility prototype. Through the implementation process, students will have the opportunity to shadow their clinical advisor in a clinical or research setting.
This course is a survey of the computing systems, technologies, and data sets used throughout the healthcare system–spanning provider, patient, payer, and pharma. Students will gain an understanding of the functional requirements and constraints placed on these digital systems and to provide a basis for future innovation.
The goal of this course is to help students understand the complexity and nuances of healthcare delivery. The course will include seminar-style lectures and discussions, along with opportunities to directly observe healthcare in such settings as a pediatric outpatient clinic, an adult emergency department and a pathology lab. Lectures and discussions will not summarize healthcare; rather, they will analyze healthcare — through themes such as people, time, money, communication, decision making and others. Students will come away from the course with a deeper appreciation of why it is difficult to change healthcare. They will then be able to anticipate the intended and unintended consequences of interventions and policies that they and others might implement.
This class introduces the principal legal issues involved in starting, managing and operating a technology-oriented business by entrepreneurs. It is intended to provide non-law students with an understanding of many of the laws and regulations to which developing businesses in the United States tech sector are typically subject—from the time an entrepreneur conceives and begins to build a business, implements a business plan, and obtains financing, to when she begins operations in anticipation of managing a mature company and considering possible exit strategies. The instructor, a former corporate partner in a large New York City law firm, will adopt the role of a general counsel to a start-up company advising his client/students about how laws and regulations affect their businesses at various stages of development, as well as about typical key contractual terms and negotiating strategies. Practicing lawyers will serve as guest lecturers. The course is designed to impart an understanding not only about substantive areas of the law that intersect with tech businesses but also about the role that lawyers should—and should not—play in burgeoning business enterprises. Students will gain insights into how lawyers approach business problems and the benefits and limitations of such a perspective.
This studio-based course helps students learn about and develop product management (PM) skills by putting those abilities immediately to use on their Startup Studio projects. In each session, students learn about a different aspect of product management, product design, or technology development, then practice applying it to their Startup Studio projects, working in the Studio with their project teams and with the help and critique of the practitioner instructors and sometimes visiting practitioners. By the end of the semester, students will have developed and practiced many of the fundamental product management skills required to develop new technology products, and their Startup Studio projects will have greatly benefited from the practice.
Product Studio is the foundational studio course for product development at Cornell Tech. Students form semester-long teams and select a “How Might We” question posed by a company. During the semester students learn the basics of product development so they can apply the knowledge and skills from their degree program: identifying impactful problems to solve, product ideation and design, development process, and constructing a meaningful product narrative and complete product loop. Students present their working product, narrative, and thought process four times during the semester, after completing each of three 24-hour “studio sprints” where they will focus on developing their product and a final product presentation at the end of the semester.
This course explores the behavioral foundations of communication technology and the information sciences, and the ways in which theories and methods from the behavioral sciences play a role in understanding people’s use of, access to and interactions with information and communication technologies. Multiple levels of analysis—individual, small group, and larger collectives—will be included, along with multiple disciplinary perspectives. Course topics will include: human perception and cognition; cognitive perspectives on design, attention and memory; psychological theories of language use and self-presentation in computer-mediated communication; social psychological perspectives on coordination and group work, social science theories of social ties and relationships; user motivation, persuasion, and more. The course will also provide a high-level view of methodologies used in the behavioral and social sciences.
In Startup Studio you and a team of your classmates will develop your own new product or startup idea. You’ll experience the entire process, from developing your idea, to prototyping and testing, to pitching to investors. You can even apply for a Startup Award that will provide funding and other support to help you turn your Startup Studio project to a real business.