Muhammad Zeeshan Baig

Northumbria University, Wentworth Institute of Technology

Papers

Total Citations

238

H-Index

About

Muhammad Zeeshan Baig is a leading researcher at the intersection of brain-computer interfaces (BCI), affective computing, and autonomous robotics. His work focuses on decoding human intent and physiological states to create more intuitive and adaptive human-machine systems. Baig’s seminal survey, “Filtering techniques for channel selection in motor imagery EEG applications” (163 citations), is a foundational resource for optimizing BCI performance by identifying the most informative neural signals, directly impacting the development of communication and neuroprosthetic devices for disabled individuals. He further advanced the field with his comprehensive review of psycho-physiological analysis methods (73 citations), establishing frameworks for integrating multimodal signals like EEG, ECG, and skin conductance to detect affective states in real-time. More recently, Baig has extended his expertise to robotics, developing novel path-planning algorithms that incorporate adaptive autonomy, enabling mobile robots to handle unforeseen scenarios through a fusion of improved A* search and dynamic programming. His work uniquely bridges the gap between neural signal processing and intelligent robotic control, paving the way for next-generation assistive and autonomous systems that can truly understand and respond to their human users.