Moustafa Eshra

• Model Based Development of rapid prototyped and production code AUTOSAR application layer Software Components of Gasoline Engine management systems for PSA(Peugeot Citroën) using MATLAB/Simulink RTW embedded coder following the main Auto-coding approach processes: Model Architecture Validation, MIL tests (Model in the Loop) SIL tests (Software in the Loop) according to Software data specifications. • Matlab tooling development to improve and automate processes. • Polyspace/QAC Running and Analysis.

-Elimination of the spikes signals that occur in the APDs (Avalanche Photo Diode) of the CMS (The Compact Muon Solenoid) detector, one of the two main detectors of the LHC (Large Hadron Collider) at CERN. -Using neural Network to solve the saturation problem that happens in the crystals of the CMS detector by predicting the energy of the dead crystals. -Working with big data to analysis data using CERN Grid.

-Elimination of Spikes signals that occur in the APDs of the CMS detector. -Using neural Network to solviethe saturation problem that happens in the crystals of the CMS detector

-Teaching tutorials of “Pattern Recognition” subject for computer and communication department. -Assigning home works, programming assignments, lab work, and course projects. -Grading all of the year work delivered from students.

Assertion Based IP for LPDDR3 memory protocol using OVM. This project developed innovative OVM (Open verification Methedology) testbench to support testing of LPDDR3 Memory Protocol model and verify its operation using verification techniques like assertion-based verification, coverage driven verification (CDV) and constrained random testing (CRT) to achieve more verification goals.

The goal of the project was to develop a hardware design of the three main blocks of the H.264 according to the standard, implement it using Verilog and make a hardware simulation.

Studied many different algorithms for feature detection, description and matching of images - SIFT, SURF, RANSAC, KNN, and FLANN - to achieve object detection system using OpenCV library.