Sara Aly Portfolio

Utilized C++ to implement Bluetooth technology, enhancing the integration of a foot controller into the Biomechanical Smart Prosthetic Arm, thereby improving user interface functionality and accessibility. In adittion, implemented wireless communication protocols in C++ to establish seamless connectivity between foot controller microcontrollers, ensuring efficient data transmission and synchronization.

Engineered and implemented a Verilog algorithm prioritizing efficiency and robustness, optimizing performance across diverse applications. Also, developed a secure encryption solution in Verilog tailored for versatile application scenarios, ensuring robust data confidentiality and integrity.

Engineered a machine learning model in MATLAB to facilitate early diagnosis of Parkinson’s Disease through analysis of voice recordings. Employed advanced machine learning techniques to extract and classify voice features associated with Parkinson’s Disease diagnosis.

Diagnosing Parkinson’s Disease Based on Voice Recordings: Comparative Study Using Machine Learning Techniques

This paper focuses on applying and evaluating different machine learning techniques to predict Parkinson’s disease based on patient’s voice data. The various algorithms in MATLAB were used to train models, and the better performing models among them were chosen.

Developed a JavaFX-based user interface (UI) for seamlessly reporting lost items and claiming found items, prioritizing intuitive navigation and user experience. Implemented robust database functionality in Java to ensure efficient storage and retrieval of lost and found item records, optimizing system performance and reliability.

Designed and implemented a customized traffic light system using VHDL and integrated sensors, ensuring efficient operation and responsiveness. Developed algorithms in VHDL to regulate traffic flow and optimize signal timings dynamically based on real-time sensor data, enhancing overall traffic management efficiency.