Antoni J. Woss
Papers
1
Total Citations
3
H-Index
1
About
Dr. Antoni J. Woss is a leading researcher in embedded intelligence and battery management systems, with a focus on advancing the safety and efficiency of battery-powered technologies. His work bridges the gap between machine learning and real-time embedded systems, particularly in the critical domain of State of Charge (SoC) and State of Health (SoH) estimation for lithium-ion batteries. His most-cited paper, "Embedded strategy for battery module states estimation using tiny machine learning models" (2026, 3 citations), introduces a scalable, practical algorithm that enables accurate state estimation directly on low-power microcontrollers. This contribution is pivotal for the next generation of Battery Management Systems (BMS), where computational efficiency and reliability are paramount. Dr. Woss’s research is instrumental in enabling safer, more efficient operation of electric vehicles and portable electronics. His work exemplifies the integration of tinyML into energy systems, offering a pathway to smarter, more autonomous battery diagnostics. With a growing citation footprint, Dr. Woss is establishing himself as a key innovator at the intersection of embedded AI and sustainable energy technology.
Research Focus
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Top Papers
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