A class demonstration
Connect a concept to a visible physical response. Include a prediction question and a short reflection.
For Howard faculty and students
Connect computing and engineering with physical systems.
AVRC welcomes teaching and project collaboration in electrical engineering, computer engineering, computer science, mechanical engineering, civil and environmental engineering, and chemical engineering. Faculty and students across Howard University can arrange activities with the laboratory team.
Start small. Build around your learning objectives.
A platform can support a single demonstration, a guided laboratory exercise, a capstone component, or a longer research sequence. Faculty and the lab team agree on access, preparation, supervision, and assessment before scheduling.
A guided investigation
Give students a baseline model, variables to investigate, and a structured way to report evidence.
An open design problem
Ask a team to define requirements, compare approaches, and justify a tested solution.
Common laboratory foundations
Instrumentation and interfacing
Read sensor measurements, interpret units and sampling, and connect software commands to the platform’s actuator interfaces.
Modeling and feedback
Develop a model, compare predicted and measured behavior, and study how a controller changes the system’s response.
Robotics and system integration
Connect coordinate frames, motion commands, communication, and software components in a defined robotic task.
Connections to computer science and engineering
AVRC can support computing and engineering education through programming, software and hardware integration, instrumentation, data acquisition and analysis, sensing and actuation, dynamic and digital systems, feedback control, mobile robotics, and autonomous-vehicle coordination. Faculty select activities that fit the course objectives, student preparation, and available laboratory resources.
Potential course connections
The following courses provide starting points for faculty discussion. Activities and equipment are selected with the instructor; inclusion here does not indicate a scheduled AVRC laboratory component.
Computer science
- CSCI-165: Scientific Computing for Engineers
- CSCI-452: Network and Web Programming
- CSCI-475: Intro to Machine Learning
- CSCI-476: Intro to Artificial Intelligence
- CSCI-498: Special Topics: Robotics Programming
Electrical engineering
- EECE-333: Fundamentals of Signals & Systems
- EECE-408: Linear Control Systems
- EECE-453: Communications Theory
- EECE-495: Signal Processing
Computer engineering
- EECE-212: Fundamentals of Digital Systems
- EECE-406: Advanced Digital Systems Design
- EECE-410: Introduction to Computer Networks
- EECE-416: Microcomputer Design
- EECE-456: Embedded Systems Design Lab
Mechanical engineering
- MEEG-207: Introduction to Engineering Computations
- MEEG-301: System Dynamics
- MEEG-316: Instrumentation and Experimentation Lab
- MEEG-444: Robotics
Civil and environmental engineering
- EGPP-101: Introduction to Engineering
- CIEG-104: Civil Engineering Software & Design
- CIEG-302: Dynamics
- CIEG-407: Intelligent Transportation Systems
Chemical engineering
- EGPP-101: Introduction to Engineering
- CHEG-306: Chemical Engineering Analysis
- CHEG-402: Process Control
Course names follow Howard’s published descriptions. Special Topics offerings, including CSCI-498 Robotics Programming, depend on the section and term. Electrical and computer engineering share EECE course offerings.
Introduction to engineering
EGPP-101 sections across engineering programs, including civil and chemical engineering, can use supervised lab visits, demonstrations, simulation, and introductory design activities. Instructors determine the concepts, preparation, and level of technical detail appropriate for their students.
Capstone and senior design across departments
Capstone and senior design teams from all departments are welcome to discuss suitable projects with AVRC. The laboratory can support modeling, software development, hardware interfacing, instrumentation, experimental testing, and interdisciplinary collaboration. The course instructor and faculty mentor define the project scope, learning outcomes, and assessment.
| Program | Design sequence |
|---|---|
| Computer science | CSCI-491 / CSCI-492 — Senior Project I / II |
| Electrical and computer engineering | EECE-401 / EECE-404 — Senior Design I / II |
| Mechanical engineering | MEEG-441 / MEEG-442 — Senior Project I / II |
| Civil and environmental engineering | CIEG-439 / CIEG-441 — Senior Design I / II |
| Chemical engineering | CHEG-407 / CHEG-414 — Process Design I / II |
A practical course integration workflow
01
Define
Choose a question, learning objective, and measurable outcome.
02
Simulate
Explore a model or digital twin and document a baseline.
03
Experiment
Test on hardware after orientation and approval.
04
Reflect
Compare evidence, explain limitations, and improve the design.
What to bring to the first conversation
- Course topic, student level, and intended learning outcomes
- Class size, preferred dates, and available preparation time
- Relevant platform or software needs
- Supervision plan and the work students will submit
Evidence students can produce
- A model and an explicit set of assumptions
- Code or controller settings with version information
- Measured plots compared with a baseline
- An explanation of limitations and next steps
Bring your course or project to the lab.
Discuss the learning goals, platform, team size, and supervision needed for a practical lab experience.