Special Topics Courses

Spring 2023 Undergraduate Special Topics Classes & Electives

CSCE 4013 002 – Special Topics: Wearable & Ubiquitous Computing – Dr. Alexander Nelson

This course will introduce wearable and ubiquitous computing paradigms with emphasis on the engineering and development. Three key themes that will be taught during this course the systems and infrastructures which compose IoT and wearable systems, the devices, and techniques for gathering data and communicating with the user, and the applications of these technologies including the user experience.  Students cannot receive credit for both CSCE 4013 and CSCE 5013 sections of this class.  Prerequisite: CSCE 3193 Programming Paradigms.

CSCE 4013 003 – Special Topics: Machine Learning in Medical Imagine – Dr. Ukash Nakarmi

This course focuses on medical imaging technology such as X-Ray, CT, and Magnetic Resonance Imaging (MRI) and how computational tools and machine learning (ML) techniques enable the creation of high-quality medical images from raw sensor measurements.  The course will introduce the basic principles of X-Ray, CT, MRI, and computational and ML tools such as low-rankness, sparsity, compressed sensing, constrained optimization, and deep learning framework in medical imaging.  Students will be introduced to how these computational and ML tools are used for image formation, reconstruction, and enhancement in medical imaging.

Spring 2023 Graduate Special Topics Classes & Electives

CSCE 5013 001 – Security Operations – Dr. Qinghua Li.

This course introduces cyber security operations. Students will study the goals, tasks, and challenges of security operations in modern information, network, and industrial control systems, as well as the technologies and resources available in the commercial market, literature, and public domains. Students will also enhance their skills in managing the security of modern systems through hands-on assignments and class projects.

CSCE 5013 002 – Advanced Special Topics: Wearable & Ubiquitous Computing – Dr. Alexander Nelson.

This course will introduce wearable and ubiquitous computing paradigms with emphasis on the engineering and development. Three key themes that will be taught during this course the systems and infrastructures which compose IoT and wearable systems, the devices, and techniques for gathering data and communicating with the user, and the applications of these technologies including the user experience. Students cannot receive credit for both CSCE 4013 and CSCE 5013 sections of this class. Prerequisite: CSCE Graduate Standing.

CSCE 5013 003 – Advanced Special Topics: Advanced Network Security – Dr. Kevin Jin.

This course will teach various topics in computer network security. It will provide a thorough grounding in cyber security for students who are interested in conducting research and development work on network and system security, and for students who are more broadly interested in real-world security issues and techniques. Students will also be looking at various case studies of attacks and defense strategies, including known exploit proofs-of-concept, published papers, and documents from security agencies and cyber security research firms.

CSCE 5013 005 – Advanced Special Topics: Machine Learning in Medical Imaging– Dr. Ukash Nakarmi

This course focuses on medical imaging technology such as X-Ray, CT, and Magnetic Resonance Imaging (MRI) and how computational tools and machine learning (ML) techniques enable the creation of high-quality medical images from raw sensor measurements. The course will introduce the basic principles of X-Ray, CT, MRI, and computational and ML tools such as low-rankness, sparsity, compressed sensing, constrained optimization, and deep learning framework in medical imaging. Students will be introduced to how these computational and ML tools are used for image formation, reconstruction, and enhancement in medical imaging.

CSCE 5013 006 – Advanced Special Topics: Post Moore’s Law Computer Architectures – Dr. David Andrews

The end of Dennard scaling and slowdown of Moore’s law has ushered in a new era called Post Moore’s Law Computing. This course will look at the trends, applications, and emerging architectures that are defining this new era. The course will look at how big data analytics and machine learning applications are driving innovation in large scale near memory architectures, domain specific accelerators, and neuromorphic computing. The course will also survey new proposed technologies that are emerging to augment and replace CMOS as our computing base. Course materials will be drawn from the literature. Students will be required to make presentations during the semester and submit a final project.  Prerequisite: CSCE Graduate Standing.