M Javid
Papers
1
Total Citations
4
H-Index
1
About
M. Javid is a researcher advancing the intersection of robotics and machine learning, with a primary focus on intelligent control systems for dexterous manipulation. Their most notable contribution is the development of a real-time physics-informed neural network (PINN) for torque tracking position control of the DLR-HIT II robotic hand, a cutting-edge platform for prosthetic and industrial applications. This work, published in 2025 and already garnering 4 citations, demonstrates a novel approach that integrates physical laws directly into neural network training, enabling more accurate and efficient control of complex robotic systems. By bridging model-based and data-driven methods, Javid’s research addresses critical challenges in robotic hand control, such as real-time adaptability and precision under dynamic loads. Their work holds promise for advancing prosthetics, teleoperation, and autonomous manipulation. With a growing citation record, Javid is establishing a reputation for innovative, application-driven research that pushes the boundaries of how robots interact with their environments.
Research Focus
Key Achievements
Top Papers
- 1