Multimodal sensor fusion
Combining acoustic spectrograms, vibration signatures, and thermal maps to improve reliability beyond single-sensor fault detection.
Academic Research · Smart Manufacturing · Embedded AI
Muhammad Fasih Waheed
Ph.D. Candidate in Electrical & Computer Engineering
Researching AI-driven fault detection in additive manufacturing, multimodal sensor fusion, edge computing, and portable quality-assurance systems for smart manufacturing.
- 5+
- Publications & papers
- 30+
- Google Scholar citations
- 2023–2026
- Teaching & mentoring outreach
About
Engineer, researcher, and technology mentor focused on practical AI systems.
I am a Ph.D. candidate at the FAMU–FSU College of Engineering. My work sits at the intersection of embedded systems, machine learning, and additive manufacturing, with a focus on low-cost, portable, and real-time monitoring systems.
Research focus
AI-enabled fault detection for additive manufacturing.
My research develops sensing and intelligence frameworks that detect print defects and process anomalies using acoustic, vibration, and thermal signals.
Portable edge intelligence
Designing low-cost data acquisition and on-device inference workflows that can operate without modifying the 3D printer.
Real-time quality assurance
Building practical tools for early detection of nozzle clogging, layer misalignment, extrusion faults, thermal drift, and other process issues.
Featured projects
Research and engineering portfolio
Research
Multimodal Sensor Fusion
Fuses acoustic, vibration, and thermal data streams to detect anomalies and improve confidence in additive-manufacturing monitoring.
Embedded AI
PrintSense Edge Device
Portable, low-cost monitoring concept for data acquisition, edge inference, and smart manufacturing analytics.
Quality assurance
Fault Detection in 3D Printing
AI-based detection of process anomalies such as extrusion issues, nozzle clogging, layer defects, and thermal irregularities.
Selected publications
Publications and scholarly output
2026
Advancing Industry 4.0: Multimodal Sensor Fusion for AI-Based Fault Detection in 3D Printing
International Journal of Engineering Research and Innovation · Accepted
2025
Real-Time Acoustic-Based Fault Detection for Additive Manufacturing Using CNN Models
IEEE SoutheastCon · Additive manufacturing, AI, acoustic monitoring
2024
Multimodal Data Fusion for Real-Time Anomaly Detection in FDM 3D Printing
IEEE SoutheastCon · Acoustic and vibration analysis for process monitoring
2025
EEG-BCI Interface for Vehicle Command and Control Applications
IEEE SoutheastCon · Brain-computer interface and embedded systems
Teaching & outreach
Mentoring the next generation of engineers.
Summer Bootcamp Instructor / Facilitator
Supported undergraduate learning and hands-on engineering training across summer bootcamp activities from 2023–2026.
Intel Foundation Semiconductor Fabrication 101
Facilitated learning in semiconductor fabrication fundamentals, cleanroom concepts, process flow, and microfabrication awareness.
Electrician Technician Training Workshop
Delivered practical technical training related to electrical safety, circuits, troubleshooting, and hands-on engineering skills.
Research Mentorship
Mentored students in embedded systems, robotics, IoT, Arduino, Python, and applied AI project development.
Media & online presence
Academic visibility and professional outreach
News
FAMU–FSU Engineering media coverage
Entrepreneurial prize and engineering innovation spotlight →
Media
WCTV AI Museum feature
Public outreach showcase at the FAMU–FSU College of Engineering →
Scholar
Google Scholar profile
Publications, citation record, and research profile →
Network
LinkedIn
Professional network and outreach updates →
Contact
Open to research collaboration, professional outreach, and academic engagement.
For research discussions, speaking opportunities, mentoring programs, media inquiries, or collaboration, reach out by email or connect online.