Master of Science in Applied Artificial Intelligence

The Master of Science in Applied Artificial Intelligence degree educates students to acquire state-of-the-art knowledge and skills in artificial intelligence and its applications across a broad range of engineering domains. The program prepares students to develop a strong background in understanding the theoretical foundations of artificial intelligence and deep learning, together with the understanding of a variety of engineering applications including intelligent communication networks, autonomous robotics, image processing and computer vision, smart Internet of Things, smart health, information systems security, biomedical and bio-engineering, civil and environmental engineering, mechanical engineering, data engineering, and software engineering. The program prepares students to enter careers in engineering fields that require advanced artificial intelligence knowledge and skills.

Concentrations

  • Computer Engineering

  • Electrical Engineering

  • Software Engineering

  • Data Engineering

  • Biomedical Engineering

  • Mechanical Engineering

  • Systems Biology

  • Artificial Intelligence in Design and Construction

Program Objectives

The program prepares students to:

  • develop a strong background in understanding the theoretical foundations of artificial intelligence and deep learning.

  • understand a variety of engineering applications for AI, including intelligent communication networks, autonomous robotics, image processing and computer vision, embedded systems, smart Internet of Things, smart health, information systems security, biomedical engineering, financial engineering, transportation engineering, data engineering, and software engineering.

 

Program Outcomes

By the time of graduation, students will be able to:

  • apply knowledge in mathematics, computational science and physics to solve problems in artificial intelligence.

  • analyze real-world data inputs and information systems using engineering principles and modeling approaches.

  • design experiments and analyze results to determine process parameters, and to identify issues and methods for algorithm design and system analysis.

  • use mathematical, modeling, and engineering principles to design artificial intelligent algorithms and systems; be able to incorporate considerations such as feasibility, applicability, cost, legal/regulatory, societal impacts, etc. in designs.

  • use computer software for data acquisition, modeling, simulation, visualization and intelligent system design.

  • write and present polished technical reports at a level expected of the engineering profession and be able to critically evaluate the technical literature and use it to obtain solutions to artificial intelligence and data engineering problems.

Degree Requirements

The program is a 30-credit degree program. Students are required to complete:

  • 1 mathematical foundation course (3 credits)

  • 4 core courses (12 credits)

  • 3 concentration courses in a chosen concentration (9 credits)

  • 3 credits of project work (AAI 800) co-requisite with EE 820 (0 credit) and a 3-credit elective course, or 6-credit thesis

Students in the Master of Science program are required to complete:

  • Project Track: 3-credit project course (800 course) and a 3-credit elective course at the 500 or 600 level. Students who enroll in the 3-credit project course (800 course) are required to enroll in the 0-credit co-requisite research seminar course, EE 820. The 3-credit elective course can be any graduate level course at the 500 or 600 levels within the Department of Electrical and Computer Engineering. Elective courses that are taken outside of the department require approval by the student's faculty advisor.

OR

  • Thesis Track: 6 credit thesis course (900 course). Students need to take the first 3-credit thesis course (900 course) in their second to last semester and the second 3-credit thesis course (900 course) in their last semester.

Mathematical Foundation Courses

Students are required to select one mathematical foundation course from the list below: 

EE 602Analytical Methods in Electrical Engineering

3

Or

EE 605Probability and Stochastic Processes I

3

Core Courses

Students are required to select four core courses from the list below: 
AAI 695Applied Machine Learning

3

AAI 646Pattern Recognition and Classification

3

EE 608Applied Modeling and Optimization

3

AAI 627Data Acquisition, Modeling and Analysis: Big Data Analytics

3

AAI 628Data Acquisition, Modeling and Analysis: Deep Learning

3

AAI 672Applied Game Theory and Evolutionary Algorithms

2

Concentrations

Students are required to select three courses from one of the concentrations listed below:

Electrical Engineering Concentration Course Options

The Electrical Engineering concentration will provide students with fundamental knowledge and background on electrical engineering and will allow students to apply Artificial Intelligence algorithms to a wide array of topics including but not limited to communications, smart grids, and digital systems design.

Students who select the Electrical Engineering concentration are required to select three concentration courses from the list below: 

EE 548Digital Signal Processing

3

EE 575Introduction to Control Theory

3

EE 582Wireless Networking: Architectures, Protocols and Standards

3

EE 603Linear System Theory

3

EE 608Applied Modeling and Optimization

3

EE 609Communication Theory

3

Computer Engineering Concentration Course Options

The Computer Engineering concentration will provide students with fundamental knowledge and background on computer engineering and will allow students to apply Artificial Intelligence algorithms to a wide array of topics including but not limited to communications, networking, information networks, image processing and computer vision, security, real time and embedded systems, and robotics and control.

Students who select the Computer Engineering concentration are required to select three concentration courses from the list below:

CPE 517Digital and Computer Systems Architecture

3

CPE 555Real-Time and Embedded Systems

3

CPE 593Applied Data Structures and Algorithms

3

CPE 679Computer and Information Networks

3

CPE 690Introduction to VLSI Design

3

EE 608Applied Modeling and Optimization

3

Data Engineering Concentration Course Options

The Data Engineering concentration will provide students with fundamental knowledge and background necessary for analysis, management and classification of Big Data for a variety of application domains, including information systems security, and data management for web applications.

Students who select the Data Engineering concentration are required to select three concentration courses from the list below: 

AAI 551Engineering Programming: Python

3

AAI 627Data Acquisition, Modeling and Analysis: Big Data Analytics

3

AAI 628Data Acquisition, Modeling and Analysis: Deep Learning

3

CPE 593Applied Data Structures and Algorithms

3

Software Engineering Concentration Course Options

The Software Engineering concentration will provide students with fundamental knowledge and background on software development with an emphasis on developing software for AI applications.

Students who select the Software Engineering concentration are required to select three concentration courses from the list below: 

AAI 551Engineering Programming: Python

3

EE 552Engineering Programming: Java

3

EE 553Engineering Programming: C++

3

AAI 627Data Acquisition, Modeling and Analysis: Big Data Analytics

3

AAI 628Data Acquisition, Modeling and Analysis: Deep Learning

3

CPE 593Applied Data Structures and Algorithms

3

CPE 810Special Topics in Computer Engineering

3-6

Biomedical Engineering Concentration Course Options

The Biomedical Engineering concentration will provide students with the engineering skills needed to extract and process biomedical signals, compute and analyze medical data, and build new user friendly healthcare applications.

Students who select the Biomedical Engineering concentration are required to select three concentration courses from the list below: 

BME 810Special Topics in Biomedical Engineering

1-6

BME 558Introduction to Brain-Machine Interfaces

3

BME 504Medical Instrumentation and Imaging

3

Or

CPE 585Medical Instrumentation and Imaging

3

Systems Biology Concentration Course Options

The Systems Biology concentration will provide students with sufficient knowledge and background to perform mathematical and computational modeling of complex biological systems in a wide range of areas including genetics and bioinformatics.

Students who select the Systems Biology concentration are required to select three concentration courses from the list below: 

BIO 687Molecular Genetics

3

CH 580Biochemistry I - Cellular Metabolism and Regulation

3

BIO 668Computational Biology

3

Mechanical Engineering Concentration Course Options

The Mechanical Engineering concentration will provide students with fundamental knowledge and background in design and manufacturing to perform mathematical and computational modeling of complex mechanical systems including but not limited to robotics.

Students who select the Mechanical Engineering concentration are required to select three concentration courses from the list below: 

ME 598Introduction to Robotics

3

ME 621Introduction to Modern Control Engineering

3

ME 644Computer-Integrated Design and Manufacturing

3

Artificial Intelligence in Design and Construction Concentration Course Options

Students who complete this concentration will acquire a practical grounding in artificial intelligence as applied to the Design and Construction Industry, including its potential to transform organizations by increasing productivity and efficiency while enhancing safety and profitability. By evaluating current trends and applications, students will be able to investigate and conclude the capital investments and project-specific feasibility necessary to incorporate AI throughout the design and construction process.

Students who select the Artificial Intelligence in Design and Construction concentration are required to select three concentration courses from the list below: 

OE 511Urban Oceanography

3

CM 521Leading Construction Organizations

3

CM 530Strategic Responses to Cyclical Environments

3

CM 560Sustainable Design

3

Project or Thesis

Students in the Master of Science program are required to complete:

  • Project Track: 3 credit project course (800 course) and a 3 credit elective course at the 500 or 600 level. Students who enroll in the 3 credit project course (800 course) are required to enroll in the 0-credit co-requisite research seminar course, EE 820. The 3 credit elective course can be any graduate level course at the 500 or 600 levels within the Department of Electrical and Computer Engineering. Elective courses that are taken outside of the department require approval by the faculty advisor.

OR

  • Thesis Track: 6 credit thesis course (900 course). Students need to take the first 3 credit thesis course (900 course) in the third semester and the second 3 credit thesis course (900 course) in the fourth semester.