This course will introduce students to the field of mobile sensing and ubiquitous computing (Ubicomp) - an emerging CS research area that aims to design and develop disruptive technologies with hardware and software systems for real-world messy, noisy and mobile scenarios. The students will learn how to build mobile sensing systems, how to implement it with ubiquitous computing tools, how to make sense of the sensor data and model the target variables.

This course will introduce students to the field of mobile sensing and ubiquitous computing (Ubicomp) - an emerging CS research area that aims to design and develop disruptive technologies with hardware and software systems for real-world messy, noisy and mobile scenarios. The students will learn how to build mobile sensing systems, how to implement it with ubiquitous computing tools, how to make sense of the sensor data and model the target variables.

Introduces students to the principal activities and state-of-the-art techniques involved in developing high-quality software systems. Topics include: requirements engineering, formal specification methods, design principles & patterns, verification & validation, debugging, and automated software engineering.

Introduces students to the principal activities and state-of-the-art techniques involved in developing high-quality software systems. Topics include: requirements engineering, formal specification methods, design principles & patterns, verification & validation, debugging, and automated software engineering.

Mathematical and algorithmic foundations of big data processing. Study of methods for sampling, sketching, and distributed processing of large scale databases, graphs, and data streams for purposes of scalable statistical description, querying, pattern mining, and learning.

Mathematical and algorithmic foundations of big data processing. Study of methods for sampling, sketching, and distributed processing of large scale databases, graphs, and data streams for purposes of scalable statistical description, querying, pattern mining, and learning.

Informed by critical, cultural, social and technological theories, texts and ideas covered in this course target the intersections of computing and ethical reasoning. Students will be presented with questions to ask, possible theories to draw from, and best practices to consult in considering the ethical impacts of computing. Course materials reflect diversity in authorship, perspective, and epistemology.

Introduction to formal language theory. Topics include finite state languages, context-free languages, the relationship between language classes and formal machine models, the Turing Machine model of computation, theories of computability, resource-bounded models, and NP-completeness. It is recommended that students have a B- or better in COMPSCI 311 in order to attempt COMPSCI 501.

Introduction to formal language theory. Topics include finite state languages, context-free languages, the relationship between language classes and formal machine models, the Turing Machine model of computation, theories of computability, resource-bounded models, and NP-completeness. It is recommended that students have a B- or better in COMPSCI 311 in order to attempt COMPSCI 501.

The Commonwealth Honors College thesis or project is intended to provide students with the opportunity to work closely with faculty members to define and carry out in-depth research or creative endeavors. It provides excellent preparation for students who intend to continue their education through graduate study or begin their professional careers. The student works closely with their 499Y Honors Research sponsor to pursue research on a topic or question of special interest to them in preparation for writing a 499T Honors Thesis or completing a 499P Honors Project.