Artificial Intelligence and Machine Learning

This interdisciplinary concentration provides the students with the required knowledge to develop intelligent techniques and systems. Students are exposed to topics such as machine learning, deep learning, computer vision, and natural language processing. Furthermore, it also covers classification, regression, clustering, dimensionality reduction, perception, motion and manipulation, reinforcement learning, and various types of neural networks. It promotes interdisciplinary education where computer science intersects with mathematics and engineering. The applications of this concentration are wide-ranging and include automatic image and video processing, healthcare, financial data and trading, speech recognition, facial identification, and seismic survey processing.

Prerequisite: ICS 381

Hosting Department: ICS

Cybersecurity and Blockchain

This interdisciplinary program covers topics related to secure and trusted computing, including data and information assurance, identification of cyber assets and related security risks and threats, measurement of system resilience against cyber-attacks, and security policy compliance and governance. Students learn the fundamental pillars of computer security and data privacy and how they affect complex engineering systems (e.g. manufacturing plants). Topics include cryptology, access control models and mechanisms, intrusion detection systems, and integrity verification mechanisms. Students also learn the fundamentals of Blockchain technology, including record and hash replication, types of blockchains (public, private, and hybrid), as well the applications in cryptocurrency and various other scientific, engineering, and business use cases.

Hosting Department: ICS

Robotics and Autonomous Systems

This interdisciplinary program covers subjects related to mechatronics, robotics, and UAVs (drones). Students develop the skills required to understand, design, and implement smart systems and robots to solve engineering problems. Topics include the fundamentals of autonyms systems, including sensing, reasoning, and acting, in addition to robotics-specific topics, such as power sources, machine vision, actuation (e.g. linear actuators and electric motors), manipulation, locomotion (walking, rolling, climbing, etc.), environmental navigation, and human-robot interaction (including speech recognition and gestures). Applications are wide-ranging and include industrial robots, as well as those used in the military, construction, agriculture, and medical fields.

Prerequisite: CISE 305

Hosting Department: SE

Quantum Information & Computing

This interdisciplinary program covers an emerging discipline in computing that utilizes quantum theory and how to apply it in the fields of computing and communication. The program covers the concepts of qubits, superposition, entanglement, quantum gates, and quantum algorithms to understand the difference between classical and quantum computing. Other topics include quantum electrodynamics, including cavity and circuit qubits, quantum superconductivity, non-linear harmonic oscillators, etc. Students are introduced to quantum computing concepts such as quantum hardware, processors, circuits, instruction sets, quantum programming languages, quantum error correction, algorithms, and quantum cryptography. Students learn how to design, simulate, and test the core parts of a superconducting Qubit.

Hosting Department: PHYS

Data Science & Analytics

This interdisciplinary program focuses on the analysis and handling of data from multiple sources and for various applications in order to draw inferences from it, combining topics from mathematics, statistics, and computer science. These topics include probability theory, inference, least-square estimation, maximum likelihood estimation, finding local and globally optimal solutions (gradient descent, genetic algorithms, etc.), and generalized additive models. It also covers machine learning topics such as classification, conditional probability estimation, clustering, dimensionality reduction (e.g. discriminant factor and principal component analyses), and decision support systems. The program also covers big data analysis, including big data collection, preparation, preprocessing, warehousing, interactive visualization, analysis, scrubbing, mining, management, modeling, and tools such as Hadoop, MapReduce, Apache Spark, etc.

Hosting Department: MATH