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Virginia's Education & Workforce
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Virginia is #1 in UMS Higher Education

Virginia has one of the largest and most prestigious higher education systems in the country, and our residents are among the most educated individuals in the nation. Virginia's newest statewide initiative, known as the New Virginia Economy, is an ambitious mission to diversify and grow a multitude of industries with careful attention and support to the fields of science, technology, and engineering.

By increasing the number of STEM degrees in our world-class public universities, we have created a massive young workforce that is ready to make Virginia the technology leader of the 21st century.

Visit DroneTrainingHQ to view Unmanned Systems Training across the nation 

Take a look at some of the courses offered in UAVs, software design, engineering, and advanced robotics in some our Virginia Higher Education colleges and universities:


Virginia Space Grant Consortium

Some description

 

The Virginia Space Grant Consortium (VSGC) in partnership with the Virginia Community College System (VCCS), NASA Langley Research Center and NASA Wallops Flight Facility and with the strong support of the Virginia Governor’s office, is offering the STEM (Science, Technology, Engineering and Math) Takes Flight at Virginia’s Community Colleges initiative. STEM Takes Flight provides a suite of programs for Virginia community college students pursuing STEM majors (exclusive of allied health and business) and faculty in STEM disciplines statewide. Opportunities include $5,000 mentored scholarships, NASA paid onsite research experiences, paid industry internships, new courses and a NASA residential faculty professional development workshop. See links below for details on each of the STEM Takes Flight opportunities. The program is underwritten in large part by a two-year NASA Space Grant competitive award.

The program deadline is February 29, 2016. Learn more at http://www.vsgc.odu.edu/STEMtakesFlight/

Averett logo

Laboratories

  • Extensive GA flight operations at Danville Regional Airport

Activities

  • Host for the 2005 NASA SATS technology demonstration

Academic courses

  • AV 216 – National Airspace Systems (3 credits) - The evolution, current state, and future of the National Airspace System with an emphasis on its current and future impact on the domestic and international aviation industry.  Defines the Federal Aviation Administration’s role in the operation, maintenance, and planned modernization of Air Traffic Control facilities, airways and navigational aids, landing aids, and airports.  The users of the system, their needs, and issues with the system’s operation and planned modernization are examined.

Academic programs

  • Bachelor of Science in Aerospace Management

GMU logo

Centers and Institutes

Laboratories

Activities

  • Robotics club

Notable faculty

Academic courses

  • ECE 460 – Introduction to Robotics (3 credits). Introduces mobile robotic systems. Topics include overview of power systems, motors, behavior-based programming, sensors, and sensor integration. Design projects conceived, developed, implemented, and presented.
  • ECE 590 – Robot Design and Implementation (3 credits). Selected topics from recent developments, and applications in various engineering disciplines. Designed to help professional engineering community keep abreast of current developments.
  • SYST 460 – Introduction to Air Traffic Control (3 credits). Introduction to Air Traffic Control (ATC) for those who plan professions in the air transportation industry. Surveys the entire field, presenting the history of ATC and how it came to be as it is, the technology on which the system is based, the procedures used by controllers to meet the safety and efficiency goals of the system, the organizational structure of the FAA, challenges facing the system, and means under investigation to meet these challenges. Some fieldwork will be required to acquire and analyze airport operational data. A brief introduction to airport design will be discussed.
  • SYST 461 – Air Transportation Systems Engineering (3 credits). Focuses on the theory and practice of system engineering in a national air transportation system. Stresses the application of mathematical techniques to analyze and design complex network transportation systems, airports, airspace, airline schedules, and traffic flow.
  • STST/OR 660 – Air Transportation Systems Modeling (3 credits). Introduces wide range of current issues in air transportation. Issues include public policy toward industry, industry economics, system capacity, current system modeling capability, human factors considerations, safety analysis and surveillance systems, and new technological developments. Develops broad understanding of contemporary and future issues. Knowledge evaluated through class discussions, take-home midterm exam, and term project to be completed by end of semester.
  • CS 580 – Introduction to Artificial Intelligence (3 credits). Principles and methods for knowledge representation, reasoning, problem solving, planning, heuristic search, reasoning, learning, probabilistic reasoning, and natural language processing and their application to building intelligent systems in a variety of domains. LISP, PROLOG, MATLAB, or expert system programming language.
  • CS 587 – Advanced Artificial Intelligence (3 credits). This course will cover several advanced topics in Artificial Intelligence beyond those covered in CS580. These topics will extend existing knowledge about search, machine learning, reasoning, and situated action. Some topics are required; others may be negotiated with the class. Topics may include planning, probabilistic reasoning, reinforcement learning, evolutionary computation, advanced neural networks, natural language processing, constraint satisfaction, reactive systems, knowledge-based learning, robotics, vision, emergent behavior, and intelligent multi-agent systems. AI is a very broad field, and the goal of this course is to provide the student with sufficient breadth beyond CS580 to act as a well-versed AI researcher.

Academic programs

  • Applied and Engineering Physics, MS

Hampton University logo

Notable faculty

Academic courses

  • CSC 430 Artificial Intelligence (3 credits). Survey of the field of artificial intelligence. Problem solving methods and searches through solution space. Predicate calculus for logic based systems. Expert systems. Knowledge representation. Machine learning.

Academic programs

  • Aviation Computer Science, BS
  • Aviation Electronic Systems, BS
  • Electrical Engineering, BS
  • Flight Education, BS

JMU logo

Academic courses

  • CS 354 – Introduction to Autonomous Robotics (3 credits). A hands-on introduction to programming autonomous mobile robots. The focus of this course is on designing robotic systems that navigate independently in complex environments. Specific topics include localization, mapping, kinematics, path planning and computer vision.
  • PHYS 386 – Robots: Structure and Theory (3 credits). An introduction to the study of autonomous robotic platforms. Topics include robot structure, propulsion systems, robot kinematics, sensors used in robotics, and sensor integration. The course combines lectures with laboratory activities in which students will get hands-on experience in designing, building, programming, and testing autonomous robotic platforms.
  • CS/ISAT 344 – Intelligent Systems (3 credits). In-depth introduction to current and future intelligent systems, including expert systems, neural networks, hybrid intelligent systems, and other intelligent system technologies and their development, uses and limitations.
  • CS 444 – Artificial Intelligence (3 credits). Students will study the history, premises, goals, social impact and philosophical implications of artificial intelligence. Students will study heuristic algorithms for large state spaces and learn to develop recursive and non-deterministic algorithms.

Academic programs

Liberty University

Centers and Institutes

Laboratories

  • Extensive GA flight operations at Lynchburg site, see above

Activities

Notable faculty

  • John Marselus (Associate Dean of Unmanned Aerial Systems)

Academic courses

  • AVIA 230 – Unmanned Aerial Systems (3 credits) - This course provides the student with a detailed introduction into the history of unmanned flight and the current status of Unmanned Aerial Systems. The student will become knowledgeable of the capabilities and pay load of civilian Unmanned Aerial Systems.  Additionally, they will become proficient in UAS simulation and will be introduced to actual UAS flights.
  • AVIA 235 – Small Unmanned Aerial Systems Operator Certificate (3 credits) - This course is designed for small unmanned aerial systems operational certification. Each student will receive academic training on UAS systems, Simulator flights in UAS, and a series of UAS flights leading to certification.
  • AVIA 335 – Command and Control of Unmanned Aerial Systems (3 credits) - This course is designed to teach the student the many aspects of command and control of Unmanned Aerial Systems (UAS). Through academic theory and actual simulator training sessions the student will be prepared for certification in command and control in the medium UAS class of aircraft.
  • AVIA 446 – Medium UAS Commercial Flight I (3 credits) - This course is designed to provide the training required to operate a medium UAS in the national airspace system and overseas. Normal procedures will be the emphasis of this course. This course will build upon the training acquired in AVIA 335, Command and Control of UAS. Those fundamentals will then be applied to actual flying of a medium class 2 or 3 UAS. Classroom instruction will be followed by simulators each day to reinforce the learning. Once the operator demonstrates proficiency through academic tests and flights in the simulator, they will move to flying operations of the UAS in national airspace approved by the Federal Aviation Administration.
  • AVIA 447 – Medium UAS Commercial Flight II (3 credits) - This course is designed to complete the training required to operate a medium UAS in the national airspace system and overseas. Abnormal and tactical procedures will be the emphasis of this course. This course will build upon the training acquired in AVIA 446, Medium UAS Commercial Flight I. Those abnormal and tactical procedures will be applied to actual flying of a medium class 2 of 3 UAS. Classroom instruction will be followed by simulators instruction to reinforce the learning. Once the operator demonstrates proficiency through academic tests and flights in the simulator, they will move to actual flying of the UAS in airspace approved by the Federal Aviation Administration.

Academic programs

Mountain Empire CC logo

Notable Faculty

  • Fred Coeburn: Information Systems Technology

Academic programs

Old Dominion Logo

Centers and Institutes

Laboratories

  • Collaborative Autonomous Systems Laboratory, MAE/MSVE

Activities

  • Held Unmanned Systems Workshop, 9/11/2014

Notable faculty

Academic courses

  • MSIM 463/563 – Design and Modeling of Autonomous Robotics Systems (3 credits). Course focuses on autonomous robotics systems with emphasis on using modeling and simulation (M&S) for system level design and testing. Fundamental concepts associated with autonomous robotic systems are discussed. Course topics include: robotic control, architectures, and sensors as well as more advanced concepts such as error propagation, localization, mapping and autonomy. Design strategies that leverage M&S to accelerate the development and testing of sophisticated autonomous robotic algorithms for individual or teams of robots are covered.
  • ECE/MSIM 607 – Machine Learning (3 credits). Course provides a practical treatment of design, analysis, implementation and applications of algorithms. Topics include multiple learning models: linear models, neural networks, support vector machines, instance-based learning, Bayesian learning, genetic algorithms, ensemble learning, reinforcement learning, unsupervised learning, etc.
  • ECE 780 – Machine Learning II (3 credits). Advanced topics in machine learning and pattern recognition systems. Data reduction techniques including principle component analysis, independent component analysis and manifold learning. Introduction to sparse coding and deep learning for data representation and feature extraction.

Academic programs

  • Aerospace Engineering (Engineering, M.S./M.E.)
  • Aerospace Engineering (Engineering, Ph.D./D.Eng.)
  • Electrical & Computer Engineering (Engineering, Ph.D.)

Some description

Activities:

  • The Hover Games- Aug 10-16 - High school students are invited to build, program, and fly a quadcopter. Open to students who have previously attended "Imagineering!",  as well as rising eighth graders through high school juniors.

Academic Courses:

  • ITEC 5100 - A+ Certified Professional  (ITEC 5100)
  • ITEC 5150 - Network + Certified Professional (ITEC 5150)
  • ITEC 5900 - Security + Certified Professional (ITEC 5900)
  • ITEC 5900 - Certified Information Systems Security Boot Camp (ITEC 5950)
  • ITEC 5965 - Certified Ethical Hacking (ITEC 5965)

Academic programs:

  • Mechanical Engineering Technology : (pdf) (excel)
    • Specialization in Marine Engineering : (pdf) (excel)
    • Specialization in Mechanical Design : (pdf) (excel)
  • Computer-Aided Drafting and Design Technology : (pdf) (excel)
  • Electronics Technology : (pdf) (excel)
    • Specialization in Electrical Engineering Technology : (pdf) (excel)

UVA logo

Activities

Notable faculty

  • David Scheffler, MAE

Academic courses

  • CS 4710 – Artificial Intelligence (3 credits). Introduces artificial intelligence. Covers fundamental concepts and techniques and surveys selected application areas. Core material includes state space search, logic, and resolution theorem proving. Application areas may include expert systems, natural language understanding, planning, machine learning, or machine perception. Provides exposure to AI implementation methods, emphasizing programming in Common LISP.
  • CS 6316/SYS 6016 – Machine Learning (3 credits). A graduate-level course on machine learning techniques and applications. Topics include: Bayesian learning, evolutionary algorithms, instance-based learning, reinforcement learning, and neural networks. Students are required to have sufficient computational background to complete several substantive programming assignments. Prerequisite: A course covering statistical techniques such as regression.
  • CS 7716/SYS 7016 – Artificial Intelligence (3 credits). In-depth study of major areas considered to be part of artificial intelligence. In particular, detailed coverage is given to the design considerations involved in automatic theorem proving, natural language understanding, and machine learning.
  • BUS 5010: Cyber Security Management Online Asynchronous (3 credits). Synchronous Sessions TBD. Provides managers with the essential framework needed to design and develop an effective cyber security program. Explores methods used to raise general security awareness, review current industry practices, and develop expertise needed to adapt policies to achieve confidentiality, integrity, and availability of organizational assets and data. James Lantzy | 3 GR credits | Required
  • BUS 5040: Creating and Conducting a Security Assessment Online Asynchronous (3 credits). Synchronous sessions TBD. Reviews the essential components of a security assessment and explores how to integrate methodology with company needs. Covers the pitfalls connected with conducting a security assessment. Addresses how to create security assessment reports, identifying threats and vulnerabilities and managing organizational audits and compliance metrics. Case studies are used to illustrate course concepts.
  • BUS 5100: Cyber Law, Regulation, and Ethics Online Asynchronous (3 credits). Synchronous sessions TBD. An overview of the ethical challenges in the information age - introduces the complex and dynamic state of the law as it applies to behavior in cyberspace. Topics include the legal pitfalls of doing business in an interconnected world and an intro to the various organizations and materials that can be turned to for assistance in understanding how to ethically and legally provide services and operate modern computer-based systems and networks.
  • BUS 5120: Securing the Internet of Things Online Asynchronous (3 credits). Synchronous sessions TBD. Examines the security and ethical issues of smart devices known as the Internet of Things (IoT). The IoT consists of smart devices that sense, anticipate, and respond to our needs as we manage them remotely. Explores IoT technology, security vulnerabilities and attacks, and mitigation controls. Assesses the health, safety, privacy, and economic impacts of IoT security events.

Academic programs

VCU logo

Laboratories

Activities

Notable faculty

  • Milos Manic, CS; see Laboratories above
  • Robert Klenke; see Laboratories above

Academic programs

VMI Logo

Centers and Institutes

  • VMI's Cooperative Engineering Center

Notable faculty

Academic courses

  • ME 413 - Aircraft Propulsion Systems
  • ME 415 - Flight Mechanics
  • ME 416 - Fundamentals of Aerodynamics
  • ME 417 - Aircraft Structural Analysis
  • ME 481 - Computational Modeling and Virtual Design

Academic programs

  • Aerospace Engineering Concentration
  • Mechanical Engineering Program
  • Electrical and Computer Engineering Program
Virginia Tech logo

Centers and Institutes

Laboratories

Activities

Notable faculty

Academic Courses

  • AE/ECE/MA 5914 – Autonomous Systems Seminar (1 credit). Weekly technical presentations from local and visiting scholars on current topics related to the theory, design and development, and application of autonomous vehicle systems.
  • ME 4524 – Introduction to Robotics and Automation (3 credits). Automation, robot technology, kinematics, dynamics, trajectory planning, and control of two-dimensional and spatial robots; robot programming; design and simulation of robotic devices.
  • ME 4864 – Micro/Nano-Robotics (3 credits). Overview of Micro/Nano-robotic systems. Physics of reduced length scales (scaling effects in the physical parameters, surface forces, contact mechanics, and micro/nano-scale dynamical phenomena), Basics of micro/nano-manufacturing, micro-fabrication and soft lithography, Bio-mimetic design strategies for mobile micro-robots, Principle of transduction, material properties and characteristics of Micro/nano-actuators (piezoelectric, shape-memory alloy, and a variety of MEMS and polymer actuators), Control requirements and challenges of micro/nano-actuators, Micro/nano sensors for mobile micro-robotic applications, Micro/nano-manipulation (scanning probe microscopy, operation principles, designing experiments for nanoscale mechanical characterization of desired samples).
  • ME 5524 – Bayesian Robotics (3 credits). Principles of autonomous robotics control for unstructured environments. Probability theory, numerical techniques for recursive Bayesian estimation and multi-sensor data fusion, simultaneous localization and mapping, quantification of belief, Bayesian control
  • ME 5864G – Advanced Micro/Nano-Robotics (3 credits). Overview of micro/nano-robotic systems, physics of reduced length scales (scaling effects in the physical parameters, surface forces, contact mechanics, and micro/nano-scale dynamical phenomena), basics of micro/nano manufacturing, micro-fabrication and soft lithography, biomimetic design strategies for mobile micro-robots, principle of transduction, material properties and characteristics of micro/nano-actuators (piezoelectric, shape memory alloy, and a variety of MEMS and polymer actuators), control requirements and challenges of micro/nano-actuators, micro/nano sensors for mobile micro-robotic applications, micro/nano-manipulation (scanning probe microscopy, operation principles, designing experiments for nanoscale mechanical characterization of desired samples)
  • CS 6804 – Advanced Topics in Intelligent Systems (3 credits). This course treats a specific advanced topic of current research interest in the area of intelligent systems. Papers from the current literature or research monographs are likely to be used instead of a textbook. Student participation in a seminar style format may be expected.

Academic Programs (credit or non-credit)