Mohamed Mazloum Elshahat Mohamed Mohamed Salem
@mans.edu.eg
Faculty of Computer & Information Sciences
Mansoura University
I am an early-career researcher in Artificial Intelligence with focus on efficient generative models, multilingual healthcare applications, and adaptive learning frameworks. My work combines computer science and real-world problem solving, and I aim to develop research outputs that are impactful, open-source, and collaborative.
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Science, Artificial Intelligence, Computer Engineering, Computational Theory and Mathematics
FUTURE PROJECTS
Ultra-Efficient Generative Models for On-Device Intelligence
This project aims to design lightweight generative AI architectures optimized for mobile and edge devices. The research will focus on reducing parameters and computation while preserving state of-the art performance in image, text, and multimodal tasks. Potential applications include healthcare diagnostics, low-resource language processing, and real-time creativity tools.
Applications Invited
Collaborators with expertise in model compression, quantization, and mobile AI deployment.
X-MedFuse: Multilingual and Efficient Multimodal Transformers for Healthcare
This project explores early mortality prediction and clinical decision support by fusing clinical notes (English, Arabic, French), structured EHR data, and medical images. The goal is to create efficient multimodal transformers suitable for low-resource environments.
Applications Invited
Students in NLP, multimodal learning, and healthcare data science.
NeuroLace: Sparse and Interpretable Continual-Learning Architecture for Edge AI
This project develops a new architecture for AI systems that can learn continuously without catastrophic forgetting, with built-in interpretability and fairness mechanisms. Target applications include robotics, autonomous agents, and sustainable AI deployment.
Applications Invited
Collaborators in reinforcement learning, continual learning, and neuroscience-inspired AI.
RECENT SCHOLAR PUBLICATIONS
GRANT DETAILS
None yet.
Industry, Institute, or Organisation Collaboration
Not yet, open to collaborations.
SOCIAL, ECONOMIC, or ACADEMIC BENEFITS
My work focuses on healthcare and accessibility, aiming to reduce inequalities in low-resource environments by creating lightweight AI systems accessible on mobile devices.