Muhammad Zeeshan Babar

Muhammad Zeeshan Babar is a Researcher at Heriot-Watt University's School of Engineering & Physical Sciences, affiliated with the Institute of Photonics and Quantum Sciences. His work bridges machine learning, control systems, and robotics, with contributions to medical imaging, autonomous systems, and optimization.

Research focuses on neural networks (e.g., CNNs for Diabetic Retinopathy diagnosis), resilient control in multi-agent systems, and adaptive robotics (e.g., LLMBot). He has explored predictive maintenance via LSTM networks and fractional-order system control. Recent work emphasizes medical AI applications and UAV guidance systems.

Publications highlight interdisciplinary innovation across healthcare, aerospace, and IoT, with notable contributions to V2X networks and elevator maintenance prediction. Collaborations span global institutions, reflecting his expertise in both theoretical and applied engineering domains.

No scientific awards are explicitly listed. His research aligns with UN Sustainable Development Goals related to health and technology innovation, leveraging cutting-edge methods like deep learning and model predictive control.