Basic problems in the translation of programming languages focusing on theory and common implementation techniques for compiling traditional (Pascal-like) programming languages to produce assembly or object code for typical machines. Involves a substantial laboratory project in which the student constructs a working compiler for a considerable subset of a realistic programming language within a provided skeleton.

Basic problems in the translation of programming languages focusing on theory and common implementation techniques for compiling traditional (Pascal-like) programming languages to produce assembly or object code for typical machines. Involves a substantial laboratory project in which the student constructs a working compiler for a considerable subset of a realistic programming language within a provided skeleton.

This course is intended to serve as an advanced overview of robotics spanning the complete autonomy loop: perception, planning, and control. We will study the theory, algorithms, and efficient implementations related to these topics, with focus on open discussions for how to do research to go beyond the state of the art. Students will gain hands-on experience in implementing, and extending such algorithms using simulations.

Students will work collaboratively to construct a production-grade image processing system.

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Not available at this time

This is a project based course, focusing on the science connecting the field of neural network with human brain mechanism, as well as advancements which are at the front of the field. We start by introducing a few neural network architectures with their learning paradigms, including deep feed-forward and recurrent networks, Hopfield's memory, and Kohonen's self organizing maps.

This is a project based course, focusing on the science connecting the field of neural network with human brain mechanism, as well as advancements which are at the front of the field. We start by introducing a few neural network architectures with their learning paradigms, including deep feed-forward and recurrent networks, Hopfield's memory, and Kohonen's self organizing maps.

This course introduces the discipline of health informatics and data science to prepare our students as forerunners of the future of digital health care systems. Followed by an overview of the health informatics industry, it covers a broad range of introductory topics related to the context of health care systems, such as the structure of current health care systems, various types of health data, theoretical framework and practice use of quantitative analytic methodologies, and ethics.

This course introduces the discipline of health informatics and data science to prepare our students as forerunners of the future of digital health care systems. Followed by an overview of the health informatics industry, it covers a broad range of introductory topics related to the context of health care systems, such as the structure of current health care systems, various types of health data, theoretical framework and practice use of quantitative analytic methodologies, and ethics.