Dong Cheng
Papers
1
Total Citations
3
H-Index
1
About
Dr. Dong Cheng is a pioneering researcher at the intersection of embedded artificial intelligence and the Internet of Things, with a primary focus on Tiny Machine Learning (TinyML). His most-cited work, a comprehensive 2023 survey on machine learning-oriented TinyML, has already garnered significant attention, establishing him as a leading voice in this emerging field. Dr. Cheng’s major contribution lies in systematically mapping the co-design of resource-constrained hardware and learning-based software architectures—a critical challenge for enabling AI on low-power devices. By highlighting how TinyML revolutionizes the fourth and fifth industrial revolutions, his research provides a foundational roadmap for deploying intelligent systems at the edge. This work not only synthesizes the state of the art but also identifies key bottlenecks, guiding future innovations in energy-efficient, on-device intelligence. Dr. Cheng’s insights are instrumental for students and researchers seeking to bridge the gap between advanced machine learning and practical, real-world IoT deployments, making him a vital contributor to the next wave of pervasive AI.
Research Focus
Key Achievements
Top Papers
- 1A Machine Learning-oriented Survey on Tiny Machine Learning3 citations · 2023