I am Dr. Junyang Zhou—an industrial AI leader connecting algorithmic research, production engineering and measurable business value across intelligent manufacturing.
25+ years across computer science, statistics and applied mathematics; 15+ years leading industrial AI transformation.
I translate advanced AI into reliable quality, shorter R&D cycles and more productive factories. As a C-level reporting executive working with CTOs, CIOs, VPs and presidents, I have built AI organizations from zero, architected enterprise platforms and delivered production-grade systems across lithium batteries, new energy, consumer electronics, robotics, smart homes and smartphone manufacturing.
< /div>Connecting vision, agents and physical systems in production-grade industrial architectures.
A real-time runtime for perception, reasoning, decisions and execution
LLM/VLM, workflows and manufacturing intelligence in one operating loop
Camera, AGV, robot, PLC, MES and digital-twin closed-loop safety
Industrial robotics, contextual perception and adaptive action
BAK Power
Led AI transformation across battery R&D, production and lifecycle management.
SVOLT Energy
Built an enterprise AI platform and scaled intelligent-factory capabilities.
Anker Innovations
Delivered unified AI SDKs and detection frameworks across consumer product lines.
Industrial AI Knowledge Portal
A connected body of work spanning AI agents, vision runtimes, CUDA acceleration, industrial safety and future manufacturing.
LLM · Bayesian
Agent · Infrastructure
Agent · Evolution
Engineering · LLM
CUDA · Real-Time
Safety · Physical AI
Ph.D. in Computer Science, Hong Kong Baptist University (2007); M.Sc. in Probability & Mathematical Statistics (2003) and B.Sc. in Applied Mathematics (2000), Sun Yat-sen University.
Member #80407788; long-standing work in computing, pervasive systems and industrial intelligence.
CIO Era recognition for industrial digitalization leadership.
Enterprise AI platform and intelligent-factory program at SVOLT.
Recognition for AI innovation and industrial application at Midea.
Self-supervised enhancement for industrial prediction and classification.