Mohammed Mouad Melouk
Assistant Instructor of Computer Engineering
Affiliation: NYU Abu Dhabi
Education: BSc, New York University Abu Dhabi
Research Areas: Deep Learning; Computer Vision; Multimodal Foundation Models; Machine Learning Security; Embedded Systems
Mohammed Mouad Melouk (Mouad) is an Assistant Instructor in Computer Engineering at New York University Abu Dhabi. He received his BSc in Computer Engineering from NYUAD in 2025, where his thesis focused on designing and implementing optimized multimodal deepfake detection in resource-constrained environments.
At NYUAD, Melouk has conducted research in the CHI Lab on agentic literature analysis pipelines using large language models, and in the eBRAIN Lab, where he developed state-of-the-art deepfake detection systems and collaborated on hardware accelerators for deep neural networks. His work spans machine learning, computer vision, and signal processing, with applications ranging from muscle signal decoding for prosthetics to explainable AI.
Melouk was awarded first place in the Generative AI Coding Competition at NYUAD’s eBRAIN Lab in 2024 for his work optimizing large language models for specialized medical tasks. Beyond research, he has also taught deep learning to engineering undergraduates as a Google Student Developer guest instructor, and his projects and teaching have engaged learners across multiple countries.