Costas J. Spanos
Papers
3
Total Citations
267
H-Index
3
About
Costas J. Spanos is a pioneering researcher whose work lies at the intersection of cyber-physical systems, machine learning, and sustainable infrastructure. His key research areas include indoor environmental quality monitoring, WiFi-based indoor positioning, and intelligent building control. Spanos made major contributions through the development of automated mobile sensing systems for high-granularity indoor environmental quality monitoring, a foundational work that has garnered 148 citations. He also advanced location-based services with adversarial learning-enabled automatic WiFi radio map construction using mobile robots, a paper cited 116 times that addresses the critical challenge of labor-intensive fingerprinting in indoor positioning systems. More recently, Spanos has explored active reinforcement learning for robust building control, tackling the brittleness of RL agents in real-world environments. His work is characterized by a practical, systems-oriented approach that bridges theoretical machine learning advances with tangible applications in smart buildings and urban infrastructure. With a career spanning decades at the University of California, Berkeley, Spanos has established himself as a leading figure in applying AI and sensing technologies to create more efficient, responsive, and sustainable built environments.
Research Focus
Key Achievements
Top Papers
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- 3Active Reinforcement Learning for Robust Building Control3 citations · 2024