Zoya Meleshkova
Papers
1
Total Citations
11
H-Index
1
About
Dr. Zoya Meleshkova is a leading researcher in intelligent robotics and machine learning, with a particular focus on advancing control systems for robotic manipulators operating in unpredictable environments. Her most cited work, "Application of Neural ODE with embedded hybrid method for robotic manipulator control" (2021, 11 citations), introduces a novel approach that integrates hybrid computational methods into Neural Ordinary Differential Equations. This innovation significantly reduces the computational resources required for real-time control, enabling more efficient and adaptive robotic behavior in non-deterministic settings. By bridging the gap between continuous-depth neural networks and practical robotics, Dr. Meleshkova’s contributions are shaping the future of autonomous systems. Her research not only demonstrates technical ingenuity but also addresses critical challenges in computational efficiency, making her work highly relevant for both academic and industrial applications. As a rising figure in her field, she continues to explore the intersection of deep learning and control theory, with her 2021 paper serving as a foundational reference for researchers developing next-generation intelligent manipulators.
Research Focus
Key Achievements
Top Papers
- 1