Mohamed Bouallegue

• Conducted research on controlling robot arms using EEG signals generated from the upper limb movements of a person. • Developed a deep learning model for analyzing and processing EEG signals to control robot arms • Collaborated with a multidisciplinary team to bridge the gap between neuroscience and robotics, advancing the frontier of Human-computer interaction

-Developed and Deployed an object detection model to detect logistics-specific objects adapted to the ROS environment. -Transformed these detected objects into a 3D object and visualize them in RVIZ -Enhanced the resources by reducing the model CPU usage, computing power, and memory.

Development of a website for doctors who treat the disease of low back pain with the ability to represent patient data, classify an incoming patient, and generate a Word document with patient details.

Documentation on exploiting and maximizing Bluetooth Low Energy. Data rate analysis and Testing on different devices and operating systems

Development of an E-learning site that uses the technique of emotional recognition by deep learning to identify if the user is satisfied with the content.