2021 — 2022
Multimodal Deep Learning for Mental Health Analysis
Master's Thesis · Mohammed V University
Research-led thesis combining text and signal modalities to detect mental health indicators using deep learning architectures.
A reverse chronological view of roles, with a focus on the work that produced lasting business impact.
A selection of academic work spanning deep learning research, computer vision, and signal processing.
Research-led thesis combining text and signal modalities to detect mental health indicators using deep learning architectures.
Built a ResNet-based convolutional network with TensorFlow and Keras for multi-class sports video classification, trained with SGD on a 75/25 split.
Developed a Matlab application simulating an end-to-end digital transmission chain, covering encoding, modulation, and signal reconstruction.