Dr. Khalid Zaman | Computational Neuroscience | Neuroscience Research Excellence Award

Dr. Khalid Zaman | Institute of Intelligent Manufacturing Technology, Shenzhen Polytechnic University, Shenzhen, Guangdong | China

Dr. Khalid Zaman is a seasoned IT and research professional with over a decade of expertise in deep learning, computer vision, robotics, emotion recognition, wireless sensor networks, cloud computing, and unmanned aerial and drone networks, with a strong focus on human–robot interaction and intelligent systems. He is currently engaged in advanced research through postdoctoral training at leading institutes in China and holds a Ph.D. in Communication and Transportation Engineering, along with an MS and Bachelor’s degree in Computer Science, complemented by professional qualifications in education. Dr. Zaman has authored 21 research articles in SCIE/SCI-indexed journals, reflecting his consistent contribution to high-impact scholarly work, and his publications have received approximately 330 citations, demonstrating the relevance and influence of his research within the global scientific community. He maintains an h-index of 8 and an i10-index of 7, highlighting both productivity and citation impact across multiple studies. Recognized as an active reviewer for more than 50 prestigious journals, he plays a vital role in maintaining research quality and integrity. Proficient in MATLAB, Python, C++, and Java, Dr. Zaman combines strong technical expertise with effective communication, driving innovation across artificial intelligence, remote sensing, human activity recognition, and next-generation intelligent networked systems.

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Featured Publications

Advancements in neighboring-based energy-efficient routing protocol (NBEER) for underwater wireless sensor networks
– SM Shah, Z Sun, K Zaman, A Hussain, I Ullah, YY Ghadi, MA Khan, Sensors, 2023

Driver emotions recognition based on improved faster R-CNN and neural architectural search network
– K Zaman, Z Sun, SM Shah, M Shoaib, L Pei, A Hussain, Symmetry, 2022

A driver gaze estimation method based on deep learning
– SM Shah, Z Sun, K Zaman, A Hussain, M Shoaib, L Pei, Sensors, 2022

A novel driver emotion recognition system based on deep ensemble classification
– K Zaman, S Zhaoyun, B Shah, T Hussain, SM Shah, F Ali, US Khan, Complex & Intelligent Systems, 2023

Khalid Zaman | Computational Neuroscience | Neuroscience Research Excellence Award

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