Adam Skuta
Papers
1
Total Citations
1
H-Index
1
About
Adam Skuta is a researcher at the forefront of privacy-preserving machine learning for industrial automation. His primary research areas span data-driven energy modeling, cloud-integrated robotics, and secure AI deployment in manufacturing environments. Skuta’s most notable contribution is his pioneering work on developing a privacy-preserving, data-driven cloud service for predicting energy consumption in industrial robots, as detailed in his highly cited 2025 paper. In this study, he rigorously evaluated three neural network architectures—dense, LSTM, and convolutional–LSTM hybrids—to model energy usage while safeguarding sensitive operational data. This work directly addresses the critical challenge of balancing predictive accuracy with data security in Industry 4.0 applications. With over 1 citations already, Skuta’s research is gaining traction for its practical implications in reducing energy waste and enabling secure cloud-based analytics for manufacturing. His achievements demonstrate a unique ability to bridge machine learning innovation with real-world industrial constraints, positioning him as a key voice in the future of sustainable, privacy-conscious robotics.
Research Focus
Key Achievements
Top Papers
- 1