Dr. Nadia S. Shamshad is a Software Engineer and Scholar in Software Engineering at Dalian University of Technology, China, with a strong research background in machine learning, reinforcement learning, deep learning, and multi-agent systems. Her work primarily focuses on adaptive control, localization, and optimization in dynamic and underwater sensor network environments, leveraging intelligent algorithms for precision and energy efficiency. She has contributed to several high-impact journals, including Scientific Reports, IEEE Access, and the IEEE Internet of Things Journal, where her research explores neural network-based localization, routing resilience, and machine learning-driven network adaptation. Her technical expertise spans Python, C++, MATLAB, NS 3, and network simulation, complemented by experience in both teaching and applied research. In academia, she has guided students in machine learning and cybersecurity applications, fostering critical thinking and innovation. Her professional experience also includes network administration and IT systems management, emphasizing performance optimization and cybersecurity. Dr. Shamshad’s research aims to bridge theoretical advancements and real world applications, contributing to intelligent, sustainable, and energy aware communication systems. She has received multiple academic honors, including prestigious scholarships and social service awards, and continues to advance interdisciplinary research at the intersection of artificial intelligence, wireless communication, and underwater sensing technologies.
Profiles: Scopus | Google Scholar
Featured Publications
Shamshad, N., Sarwr, D., Almogren, A., Saleem, K., Munawar, A., Rehman, A. U., et al. (2024). Enhancing brain tumor classification by a comprehensive study on transfer learning techniques and model efficiency using MRI datasets. IEEE Access, 63, 1.
Ahmad, I., Liu, Y., Javeed, D., Shamshad, N., Sarwr, D., & Ahmad, S. (2020). A review of artificial intelligence techniques for selection & evaluation. IOP Conference Series: Materials Science and Engineering, 853(1), 012055.
Shamshad, N., Wang, L., Saleem, K., Sarwr, D., Bharany, S., Almogren, A., et al. (2025). Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks. Scientific Reports, 15(1), 2182.
Shamshad, N., Wang, L., Sarwr, D., & Mohsan, S. A. H. (2025). Deeploc: A CNN-LSTM framework for NLOS-aware localization in underwater sensor networks. The Journal of Supercomputing, 81(16), 1–24.
Shamshad, N. D. S. (2020). A review of traffic flow prediction based on machine learning approaches. International Journal of Scientific & Engineering Research, 11(3), 5.